ALBERT

Description: We aim to construct higher order tau-leaping methods for numerically simulating stochastic chemical kinetic systems in this paper. By adding a random correction to the primitive tau-leaping scheme in each time step, we greatly improve the accuracy of the tau-leaping approximations. This gain in accuracy actually comes from the reduction in the local truncation error of the scheme in the order of τ , the marching time step size. While the local truncation error of the primitive tau-leaping method is O ( τ 2 ) for all moments, our Poisson random correction tau-leaping method, in which the correction term is a Poisson random variable, can reduce the local truncation error for the mean to O ( τ 3 ) , and both Gaussian random correction tau-leaping methods, in which the correction term is a Gaussian random variable, can reduce the local truncation error for both the mean and covariance to O ( τ 3 ) . Numerical results demonstrate that these novel methods more accurately capture crucial properties such as the mean and variance than existing methods for simulating chemical reaction systems. This work constitutes a first step to construct high order numerical methods for simulating jump processes. With further refinement and appropriately modified step-size selection procedures, the random correction methods should provide a viable way of simulating chemical reaction systems accurately and efficiently.

Description: Coherence oscillations measured in two-dimensional (2D) electronic spectra of pigment-protein complexes may have electronic, vibrational, or mixed-character vibronic origins, which depend on the degree of electronic-vibrational mixing. Oscillations from intrapigment vibrations can obscure the inter-site coherence lifetime of interest in elucidating the mechanisms of energy transfer in photosynthetic light-harvesting. Huang-Rhys factors ( S ) for low-frequency vibrations in Chlorophyll and Bacteriochlorophyll are quite small ( S ≤ 0.05), so it is often assumed that these vibrations influence neither 2D spectra nor inter-site coherence dynamics. In this work, we explore the influence of S within this range on the oscillatory signatures in simulated 2D spectra of a pigment heterodimer. To visualize the inter-site coherence dynamics underlying the 2D spectra, we introduce a formalism which we call the “site-probe response.” By comparing the calculated 2D spectra with the site-probe response, we show that an on-resonance vibration with Huang-Rhys factor as small as S = 0.005 and the most strongly coupled off-resonance vibrations ( S = 0.05) give rise to long-lived, purely vibrational coherences at 77 K. We moreover calculate the correlation between optical pump interactions and subsequent entanglement between sites, as measured by the concurrence. At 77 K, greater long-lived inter-site coherence and entanglement appear with increasing S . This dependence all but vanishes at physiological temperature, as environmentally induced fluctuations destroy the vibronic mixing.

Description: We address the problem of simulating biochemical reaction networks with time-dependent rates and propose a new algorithm based on our rejection-based stochastic simulation algorithm (RSSA) [Thanh et al. , J. Chem. Phys. 141 (13), 134116 (2014)]. The computation for selecting next reaction firings by our time-dependent RSSA (tRSSA) is computationally efficient. Furthermore, the generated trajectory is exact by exploiting the rejection-based mechanism. We benchmark tRSSA on different biological systems with varying forms of reaction rates to demonstrate its applicability and efficiency. We reveal that for nontrivial cases, the selection of reaction firings in existing algorithms introduces approximations because the integration of reaction rates is very computationally demanding and simplifying assumptions are introduced. The selection of the next reaction firing by our approach is easier while preserving the exactness.

Description: Reference interaction site model (RISM) has recently become a popular approach in the study of thermodynamical and structural properties of the solvent around macromolecules. On the other hand, it was widely suggested that there exists water density depletion around large hydrophobic solutes (〉1 nm), and this may pose a great challenge to the RISM theory. In this paper, we develop a new analytical theory, the Reference Interaction Site Model with Hydrophobicity induced density Inhomogeneity (RISM-HI), to compute solvent radial distribution function (RDF) around large hydrophobic solute in water as well as its mixture with other polyatomic organic solvents. To achieve this, we have explicitly considered the density inhomogeneity at the solute-solvent interface using the framework of the Yvon-Born-Green hierarchy, and the RISM theory is used to obtain the solute-solvent pair correlation. In order to efficiently solve the relevant equations while maintaining reasonable accuracy, we have also developed a new closure called the D2 closure. With this new theory, the solvent RDFs around a large hydrophobic particle in water and different water-acetonitrile mixtures could be computed, which agree well with the results of the molecular dynamics simulations. Furthermore, we show that our RISM-HI theory can also efficiently compute the solvation free energy of solute with a wide range of hydrophobicity in various water-acetonitrile solvent mixtures with a reasonable accuracy. We anticipate that our theory could be widely applied to compute the thermodynamic and structural properties for the solvation of hydrophobic solute.

Description: Recently proposed methods for DNA sequencing involve the use of cleavage-based enzymes attached to the opening of a nanopore. The idea is that DNA interacting with either an exonuclease or polymerase protein will lead to a small molecule being cleaved near the mouth of the nanopore, and subsequent entry into the pore will yield information about the DNA sequence. The prospects for this approach seem promising, but it has been shown that diffusion related effects impose a limit on the capture probability of molecules by the pore, which limits the efficacy of the technique. Here, we revisit the problem with the goal of optimizing the capture probability via a step decrease in the nucleotide diffusion coefficient between the pore and bulk solutions. It is shown through random walk simulations and a simplified analytical model that decreasing the molecule’s diffusion coefficient in the bulk relative to its value in the pore increases the nucleotide capture probability. Specifically, we show that at sufficiently high applied transmembrane potentials (≥100 mV), increasing the potential by a factor f is equivalent to decreasing the diffusion coefficient ratio D bulk / D pore by the same factor f . This suggests a promising route toward implementation of cleavage-based sequencing protocols. We also discuss the feasibility of forming a step function in the diffusion coefficient across the pore-bulk interface.

Description: Large-scale domain motions in alcohol dehydrogenase (ADH) have been observed previously by neutron spin-echo spectroscopy (NSE). We have extended the investigation on the dynamics of ADH in solution by using high-resolution neutron time-of-flight (TOF) and neutron backscattering (BS) spectroscopy in the incoherent scattering range. The observed hydrogen dynamics were interpreted in terms of three mobility classes, which allowed a simultaneous description of the measured TOF and BS spectra. In addition to the slow global protein diffusion and domain motions observed by NSE, a fast internal process could be identified. Around one third of the protons in ADH participate in the fast localized diffusive motion. The diffusion coefficient of the fast internal motions is around two third of the value of the surrounding D 2 O solvent. It is tempting to associate the fast internal process with solvent exposed amino acid residues with dangling side chains.

Description: We analyse the effect of intrinsic fluctuations on the properties of bistable stochastic systems with time scale separation operating under quasi-steady state conditions. We first formulate a stochastic generalisation of the quasi-steady state approximation based on the semi-classical approximation of the partial differential equation for the generating function associated with the chemical master equation. Such approximation proceeds by optimising an action functional whose associated set of Euler-Lagrange (Hamilton) equations provides the most likely fluctuation path. We show that, under appropriate conditions granting time scale separation, the Hamiltonian can be re-scaled so that the set of Hamilton equations splits up into slow and fast variables, whereby the quasi-steady state approximation can be applied. We analyse two particular examples of systems whose mean-field limit has been shown to exhibit bi-stability: an enzyme-catalysed system of two mutually inhibitory proteins and a gene regulatory circuit with self-activation. Our theory establishes that the number of molecules of the conserved species is order parameters whose variation regulates bistable behaviour in the associated systems beyond the predictions of the mean-field theory. This prediction is fully confirmed by direct numerical simulations using the stochastic simulation algorithm. This result allows us to propose strategies whereby, by varying the number of molecules of the three conserved chemical species, cell properties associated to bistable behaviour (phenotype, cell-cycle status, etc.) can be controlled.

Description: We report a facile method of doping cations from an electrospray ionization (ESI) source into superfluid helium droplets. By decelerating and stopping the ion pulse of reserpine and substance P from an ESI source in the path of the droplet beam, about 10 4 ion-doped droplets (one ion per droplet) can be recorded, corresponding to a pickup efficiency of nearly 1 out of 1000 ions. We attribute the success of this simple approach to the long residence time of the cations in the droplet beam. The resulting size of the doped droplets, on the order of 10 5 /droplet, is measured using deflection and retardation methods. Our method does not require an ion trap in the doping region, which significantly simplifies the experimental setup and procedure for future spectroscopic and diffraction studies.

Description: A number of important cellular functions rely on the formation of intracellular protein concentration gradients. Experimental studies discovered a number of mechanisms for the formation of such gradients. One of the mechanisms relies on the intracellular shuttling of a protein that interconverts between the two states with different diffusivities, under the action of two enzymes, one of which is localized to the plasma membrane, whereas the second is uniformly distributed in the cytoplasm. Recent work reported an analytical solution for the steady state gradient in this mechanism, obtained in the framework of a one-dimensional reaction-diffusion model. Here, we study the dynamics in this model and derive analytical expressions for the Laplace transforms of the time-dependent concentration profiles in terms of elementary transcendental functions. Inverting these transforms numerically, one can obtain time-dependent concentration profiles of the two forms of the protein.

Description: Using the probabilistic language of conditional expectations, we reformulate the force matching method for coarse-graining of molecular systems as a projection onto spaces of coarse observables. A practical outcome of this probabilistic description is the link of the force matching method with thermodynamic integration. This connection provides a way to systematically construct a local mean force and to optimally approximate the potential of mean force through force matching. We introduce a generalized force matching condition for the local mean force in the sense that allows the approximation of the potential of mean force under both linear and non-linear coarse graining mappings (e.g., reaction coordinates, end-to-end length of chains). Furthermore, we study the equivalence of force matching with relative entropy minimization which we derive for general non-linear coarse graining maps. We present in detail the generalized force matching condition through applications to specific examples in molecular systems.

Description: We introduce a set of charged patchy particle models (CPPMs) in order to systematically study the influence of electrostatic charge patchiness and multipolarity on macromolecular interactions by means of implicit-solvent, explicit-ion Langevin dynamics simulations employing the Gromacs software. We consider well-defined zero-, one-, and two-patched spherical globules each of the same net charge and (nanometer) size which are composed of discrete atoms. The studied mono- and multipole moments of the CPPMs are comparable to those of globular proteins with similar size. We first characterize ion distributions and electrostatic potentials around a single CPPM. Although angle-resolved radial distribution functions reveal the expected local accumulation and depletion of counter- and co-ions around the patches, respectively, the orientation-averaged electrostatic potential shows only a small variation among the various CPPMs due to space charge cancellations. Furthermore, we study the orientation-averaged potential of mean force (PMF), the number of accumulated ions on the patches, as well as the CPPM orientations along the center-to-center distance of a pair of CPPMs. We compare the PMFs to the classical Derjaguin-Verwey-Landau-Overbeek theory and previously introduced orientation-averaged Debye-Hückel pair potentials including dipolar interactions. Our simulations confirm the adequacy of the theories in their respective regimes of validity, while low salt concentrations and large multipolar interactions remain a challenge for tractable theoretical descriptions.

Description: The formation of aggregates in many protein systems can be significantly accelerated by secondary nucleation, a process where existing assemblies catalyse the nucleation of new species. In particular, secondary nucleation has emerged as a central process controlling the proliferation of many filamentous protein structures, including molecular species related to diseases such as sickle cell anemia and a range of neurodegenerative conditions. Increasing evidence suggests that the physical size of protein filaments plays a key role in determining their potential for deleterious interactions with living cells, with smaller aggregates of misfolded proteins, oligomers, being particularly toxic. It is thus crucial to progress towards an understanding of the factors that control the sizes of protein aggregates. However, the influence of secondary nucleation on the time evolution of aggregate size distributions has been challenging to quantify. This difficulty originates in large part from the fact that secondary nucleation couples the dynamics of species distant in size space. Here, we approach this problem by presenting an analytical treatment of the master equation describing the growth kinetics of linear protein structures proliferating through secondary nucleation and provide closed-form expressions for the temporal evolution of the resulting aggregate size distribution. We show how the availability of analytical solutions for the full filament distribution allows us to identify the key physical parameters that control the sizes of growing protein filaments. Furthermore, we use these results to probe the dynamics of the populations of small oligomeric species as they are formed through secondary nucleation and discuss the implications of our work for understanding the factors that promote or curtail the production of these species with a potentially high deleterious biological activity.

Description: Salt bridges and ionic interactions play an important role in protein stability, protein-protein interactions, and protein folding. Here, we provide the classical MD simulations of the structure and IR signatures of the arginine (Arg)–glutamate (Glu) salt bridge. The Arg-Glu model is based on the infinite polyalanine antiparallel two-stranded β -sheet structure. The 1 μ s NPT simulations show that it preferably exists as a salt bridge (a contact ion pair). Bidentate (the end-on and side-on structures) and monodentate (the backside structure) configurations are localized [Donald et al. , Proteins 79 , 898–915 (2011)]. These structures are stabilized by the short + N–H⋯O − bonds. Their relative stability depends on a force field used in the MD simulations. The side-on structure is the most stable in terms of the OPLS-AA force field. If AMBER ff99SB-ILDN is used, the backside structure is the most stable. Compared with experimental data, simulations using the OPLS all-atom (OPLS-AA) force field describe the stability of the salt bridge structures quite realistically. It decreases in the following order: side-on 〉 end-on 〉 backside. The most stable side-on structure lives several nanoseconds. The less stable backside structure exists a few tenth of a nanosecond. Several short-living species (solvent shared, completely separately solvated ionic groups ion pairs, etc.) are also localized. Their lifetime is a few tens of picoseconds or less. Conformational flexibility of amino acids forming the salt bridge is investigated. The spectral signature of the Arg-Glu salt bridge is the IR-intensive band around 2200 cm −1 . It is caused by the asymmetric stretching vibrations of the + N–H⋯O − fragment. Result of the present paper suggests that infrared spectroscopy in the 2000–2800 frequency region may be a rapid and quantitative method for the study of salt bridges in peptides and ionic interactions between proteins. This region is usually not considered in spectroscopic studies of peptides and proteins.

Description: Data assimilation is a statistical method designed to improve the quality of numerical simulations in combination with real observations. Here, we develop a sequential data assimilation method that incorporates one-dimensional time-series data of smFRET (single-molecule Förster resonance energy transfer) photon-counting into conformational ensembles of biomolecules derived from “replicated” molecular dynamics (MD) simulations. A particle filter using a large number of “replicated” MD simulations with a likelihood function for smFRET photon-counting data is employed to screen the conformational ensembles that match the experimental data. We examine the performance of the method using emulated smFRET data and coarse-grained (CG) MD simulations of a dye-labeled polyproline-20. The method estimates the dynamics of the end-to-end distance from smFRET data as well as revealing that of latent conformational variables. The particle filter is also able to correct model parameter dependence in CG MD simulations. We discuss the applicability of the method to real experimental data for conformational dynamics of biomolecules.

Description: The relevance of neglecting three- and four-body interactions in the coarse-grained version of the Asakura–Oosawa model is examined. A mapping between the first few virial coefficients of the binary nonadditive hard-sphere mixture representative of this model and those arising from the coarse-grained (pairwise) depletion potential approximation allows for a quantitative evaluation of the effect of such interactions. This turns out to be especially important for large size ratios and large reservoir polymer packing fractions.

Description: The characteristic properties of graphene make it useful in an assortment of applications. One particular application—the use of graphene in biosensors—requires a thorough understanding of graphene-peptide interactions. In this study, the binding of glycine (G) capped amino acid residues (termed GXG tripeptides) to trilayer graphene surfaces in aqueous solution was examined and compared to results previously obtained for peptide binding to single-layer free-standing graphene [A. N. Camden, S. A. Barr, and R. J. Berry, J. Phys. Chem. B 117 , 10691–10697 (2013)]. In order to understand the interactions between the peptides and the surface, binding enthalpy and free energy values were calculated for each GXG system, where X cycled through the typical 20 amino acids. When the GXG tripeptides were bound to the surface, distinct conformations were observed, each with a different binding enthalpy. Analysis of the binding energy showed the binding of peptides to trilayer graphene was dominated by van der Waals interactions, unlike the free-standing graphene systems, where the binding was predominantly electrostatic in nature. These results demonstrate the utility of computational materials science in the mechanistic explanation of surface-biomolecule interactions which could be applied to a wide range of systems.

Description: An accurate method for predicting the amide I vibrational spectrum of a given protein structure has been sought for many years. Significant progress has been made recently by sampling structures from molecular dynamics simulations and mapping local electrostatic variables onto the frequencies of individual amide bonds. Agreement with experiment, however, has remained largely qualitative. Previously, we used dipeptide fragments and isotope-labeled constructs of the protein G mimic NuG2b as experimental standards for developing and testing amide I frequency maps. Here, we combine these datasets to test different frequency-map models and develop a novel method to produce an optimized four-site potential (4P) map based on the CHARMM27 force field. Together with a charge correction for glycine residues, the optimized map accurately describes both experimental datasets, with average frequency errors of 2–3 cm −1 . This 4P map is shown to be convertible to a three-site field map which provides equivalent performance, highlighting the viability of both field- and potential-based maps for amide I spectral modeling. The use of multiple sampling points for local electrostatics is found to be essential for accurate map performance.

Description: Multidimensional potential energy surfaces based on reproducing kernel-interpolation are employed to explore the energetics and dynamics of free and bound nitric oxide in myoglobin (Mb). Combining a force field description for the majority of degrees of freedom and the higher-accuracy representation for the NO ligand and the Fe out-of-plane motion allows for a simulation approach akin to a mixed quantum mechanics/molecular mechanics treatment. However, the kernel-representation can be evaluated at conventional force-field speed. With the explicit inclusion of the Fe-out-of-plane (Fe-oop) coordinate, the dynamics and structural equilibrium after photodissociation of the ligand are correctly described compared to experiment. Experimentally, the Fe-oop coordinate plays an important role for the ligand dynamics. This is also found here where the isomerization dynamics between the Fe–ON and Fe–NO state is significantly affected whether or not this co-ordinate is explicitly included. Although the Fe–ON conformation is metastable when considering only the bound 2 A state, it may disappear once the 4 A state is included. This explains the absence of the Fe–ON state in previous experimental investigations of MbNO.

Description: Experimental data of the DNA cyclization (J-factor) at short length scales exceed the theoretical expectation based on the wormlike chain (WLC) model by several orders of magnitude. Here, we propose that asymmetric bending rigidity of the double helix in the groove direction can be responsible for extreme bendability of DNA at short length scales and it also facilitates DNA loop formation at these lengths. To account for the bending asymmetry, we consider the asymmetric elastic rod (AER) model which has been introduced and parametrized in an earlier study [B. Eslami-Mossallam and M. R. Ejtehadi, Phys. Rev. E 80 , 011919 (2009)]. Exploiting a coarse grained representation of the DNA molecule at base pair (bp) level and using the Monte Carlo simulation method in combination with the umbrella sampling technique, we calculate the loop formation probability of DNA in the AER model. We show that the DNA molecule has a larger J-factor compared to the WLC model which is in excellent agreement with recent experimental data.

Description: Time-resolved wide-angle X-ray scattering (TR-WAXS) is an emerging experimental technique used to track chemical reactions and conformational transitions of proteins in real time. Thanks to increased time resolution of the method, anisotropic TR-WAXS patterns were recently reported, which contain more structural information than isotropic patterns. So far, however, no method has been available to compute anisotropic WAXS patterns of biomolecules, thus limiting the structural interpretation. Here, we present a method to compute anisotropic TR-WAXS patterns from molecular dynamics simulations. The calculations accurately account for scattering of the hydration layer and for thermal fluctuations. For many photo-excitable proteins, given a low intensity of the excitation laser, the anisotropic pattern is described by two independent components: (i) an isotropic component, corresponding to common isotropic WAXS experiments and (ii) an anisotropic component depending on the orientation of the excitation dipole of the solute. We present a set of relations for the calculation of these two components from experimental scattering patterns. Notably, the isotropic component is not obtained by a uniform azimuthal average on the detector. The calculations are illustrated and validated by computing anisotropic WAXS patterns of a spheroidal protein model and of photoactive yellow protein. Effects due to saturated excitation at high intensities of the excitation laser are discussed, including opportunities to extract additional structural information by modulating the laser intensity.

Description: For a general two-cluster network, a new methodology of the cluster-based generalized quantum kinetic expansion (GQKE) is developed in the matrix formalism under two initial conditions: the local cluster equilibrium and system-bath factorized states. For each initial condition, the site population evolution follows exactly a distinct closed equation, where all the four terms involved are systematically expanded over inter-cluster couplings. For the system-bath factorized initial state, the numerical investigation of the two models, a biased (2, 1)-site system and an unbiased (2, 2)-site system, verifies the reliability of the GQKE and the relevance of higher-order corrections. The time-integrated site-to-site rates and the time evolution of site population reveal the time scale separation between intra-cluster and inter-cluster kinetics. The population evolution of aggregated clusters can be quantitatively described by the approximate cluster Markovian kinetics.

Description: Sorting of microswimmers based on their mobility properties is of utmost importance for various branches of science and engineering. In this paper, we proposed a novel sorting method, where the mixed chiral particles can be separated by applying two opposite rotary obstacles. It is found that when the angular speed of the obstacles, the angular speed of active particles, and the self-propulsion speed satisfy a certain relation, the mixed particles can be completely separated and the capture efficiency takes its maximal value. Our results may have application in capture or sorting of chiral active particles, or even measuring the chirality of active particles.

Description: Several studies in the past have generated Markov State Models (MSMs), i.e., kinetic models, of biomolecular systems by post-analyzing long standard molecular dynamics (MD) calculations at the temperature of interest and focusing on the maximally ergodic subset of states. Questions related to goodness of these models, namely, importance of the missing states and kinetic pathways, and the time for which the kinetic model is valid, are generally left unanswered. We show that similar questions arise when we generate a room-temperature MSM (denoted MSM-A) for solvated alanine dipeptide using state-constrained MD calculations at higher temperatures and Arrhenius relation — the main advantage of such a procedure being a speed-up of several thousand times over standard MD-based MSM building procedures. Bounds for rate constants calculated using probability theory from state-constrained MD at room temperature help validate MSM-A. However, bounds for pathways possibly missing in MSM-A show that alternate kinetic models exist that produce the same dynamical behaviour at short time scales as MSM-A but diverge later. Even in the worst case scenario, MSM-A is found to be valid longer than the time required to generate it. Concepts introduced here can be straightforwardly extended to other MSM building techniques.

Description: Ligand diffusion through a protein interior is a fundamental process governing biological signaling and enzymatic catalysis. A complex topology of channels in proteins leads often to difficulties in modeling ligand escape pathways by classical molecular dynamics simulations. In this paper, two novel memetic methods for searching the exit paths and cavity space exploration are proposed: Memory Enhanced Random Acceleration (MERA) Molecular Dynamics (MD) and Immune Algorithm (IA). In MERA, a pheromone concept is introduced to optimize an expulsion force. In IA, hybrid learning protocols are exploited to predict ligand exit paths. They are tested on three protein channels with increasing complexity: M2 muscarinic G-protein-coupled receptor, enzyme nitrile hydratase, and heme-protein cytochrome P450cam. In these cases, the memetic methods outperform simulated annealing and random acceleration molecular dynamics. The proposed algorithms are general and appropriate in all problems where an accelerated transport of an object through a network of channels is studied.

Description: We computationally investigate the deformation of a closed bilayer membrane (vesicle) in a DC electric pulse with a goal of understanding cell electroporation. The electric stresses exerted on the area-incompressible interface generate non-uniform tension that can exceed the membrane lysis tension and drive pore opening. Using the two-dimensional boundary integral method, we track the spatial and temporal evolution of the highest membrane tension. Our simulations highlight the dynamic nature of electrotension and, in contrast to the common assumption, a possibility of electroporation away from the poles.

Description: Adhesion processes of biological membranes that enclose cells and cellular organelles are essential for immune responses, tissue formation, and signaling. These processes depend sensitively on the binding constant K 2D of the membrane-anchored receptor and ligand proteins that mediate adhesion, which is difficult to measure in the “two-dimensional” (2D) membrane environment of the proteins. An important problem therefore is to relate K 2D to the binding constant K 3D of soluble variants of the receptors and ligands that lack the membrane anchors and are free to diffuse in three dimensions (3D). In this article, we present a general theory for the binding constants K 2D and K 3D of rather stiff proteins whose main degrees of freedom are translation and rotation, along membranes and around anchor points “in 2D,” or unconstrained “in 3D.” The theory generalizes previous results by describing how K 2D depends both on the average separation and thermal nanoscale roughness of the apposing membranes, and on the length and anchoring flexibility of the receptors and ligands. Our theoretical results for the ratio K 2D / K 3D of the binding constants agree with detailed results from Monte Carlo simulations without any data fitting, which indicates that the theory captures the essential features of the “dimensionality reduction” due to membrane anchoring. In our Monte Carlo simulations, we consider a novel coarse-grained model of biomembrane adhesion in which the membranes are represented as discretized elastic surfaces, and the receptors and ligands as anchored molecules that diffuse continuously along the membranes and rotate at their anchor points.

Description: We study the effect of curvature inducing macroion condensation on the shapes of charged deformable fluid interfaces using dynamically triangulated Monte Carlo simulations. In the weak electrostatic coupling regime, surface charges are weakly screened and the conformations of a vesicle, with fixed spherical topology, depend on the charge-charge interaction on the surface. While in the strong coupling regime, condensation driven curvature induction plays a dominant role in determining the conformations of these surfaces. Condensation itself is observed to be dependent on the induced curvature, with larger induced curvatures favoring increased condensation. We show that both curvature generation and curvature sensing, induced by the interplay of electrostatics and curvature energy, contribute to determination of the vesicle configurations.

Description: The adhesion of biological membranes is mediated by the binding of membrane-anchored receptor and ligand proteins. Central questions are how the binding kinetics of these proteins is affected by the membranes and by the membrane anchoring of the proteins. In this article, we (i) present detailed data for the binding of membrane-anchored proteins from coarse-grained molecular dynamics simulations and (ii) provide a theory that describes how the binding kinetics depends on the average separation and thermal roughness of the adhering membranes and on the anchoring, lengths, and length variations of the proteins. An important element of our theory is the tilt of bound receptor-ligand complexes and transition-state complexes relative to the membrane normals. This tilt results from an interplay of the anchoring energy and rotational entropy of the complexes and facilitates the formation of receptor-ligand bonds at membrane separations smaller than the preferred separation for binding. In our simulations, we have considered both lipid-anchored and transmembrane receptor and ligand proteins. We find that the binding equilibrium constant and binding on-rate constant of lipid-anchored proteins are considerably smaller than the binding constant and on-rate constant of rigid transmembrane proteins with identical binding domains.

Description: Several recent experiments suggest that rather generally the diffusion of enzymes may be augmented through their activity. We demonstrate that such swimming motility can emerge from the interplay between the enzyme energy landscape and the hydrodynamic coupling of the enzyme to its environment. Swimming thus occurs during the transit time of a transient allosteric change. We estimate the velocity during the transition. The analysis of such a swimming motion suggests the final stroke size is limited by the hydrodynamic size of the enzyme. This limit is quite a bit smaller than the values that can be inferred from the recent experiments. We also show that one proposed explanation of the experiments based on reaction heat effects can be ruled out using an extended hydrodynamic analysis. These results lead us to propose an alternate explanation of the fluorescence correlation measurements.

Description: Multiple time scales in cellular chemical reaction systems often render the tau-leaping algorithm inefficient. Various model reductions have been proposed to accelerate tau-leaping simulations. However, these are often identified and deployed manually, requiring expert knowledge. This is time-consuming and prone to error. In previous work, we proposed a methodology for automatic identification and validation of model reduction opportunities for tau-leaping simulation. Here, we show how the model reductions can be automatically and adaptively deployed during the time course of a simulation. For multiscale systems, this can result in substantial speedups.

Description: High-resolution photoelectron spectra of the gas phase pyrimidine-type nucleobases, thymine, uracil, and cytosine, were collected using synchrotron radiation over the photon energy range 17 ≤ hν ≤ 150 eV. These data provide the highest resolution photoelectron spectra of thymine, uracil, and cytosine published to date. By comparing integrated regions of the energy dependent photoelectron spectra of thymine, the ionization potentials of the first four ionic states of thymine were estimated to be 8.8, 9.8, 10.3, and 10.8 eV. The thymine data also show evidence for low energy shape resonances in three of the outermost valence electronic states. Comparing the uracil spectrum with the thymine spectrum, the four outermost valence electronic states of uracil likely begin at binding energies 9.3, 9.9, 10.5, and 11.0 eV. High-resolution spectra indicate only one tautomeric form of cytosine contributes significantly to the spectrum with the four outermost valence electronic states beginning at binding energies 8.9, 9.9, 10.4, and 10.85 eV.

Description: In this work, we have studied the stochastic response of a single voltage-gated potassium ion channel to a periodic external voltage that keeps the system out-of-equilibrium. The system exhibits memory, resulting from time-dependent driving, that is reflected in terms of dynamic hysteresis in the current-voltage characteristics. The hysteresis loop area has a maximum at some intermediate voltage frequency and disappears in the limits of low and high frequencies. However, the (average) dissipation at long-time limit increases and finally goes to saturation with rising frequency. This raises the question: how diminishing hysteresis can be associated with growing dissipation? To answer this, we have studied the nonequilibrium thermodynamics of the system and analyzed different thermodynamic functions which also exhibit hysteresis. Interestingly, by applying a temporal symmetry analysis in the high-frequency limit, we have analytically shown that hysteresis in some of the periodic responses of the system does not vanish. On the contrary, the rates of free energy and internal energy change of the system as well as the rate of dissipative work done on the system show growing hysteresis with frequency. Hence, although the current-voltage hysteresis disappears in the high-frequency limit, the memory of the ion channel is manifested through its specific nonequilibrium thermodynamic responses.

Description: Conventional studies of biomolecular behaviors rely largely on the construction of kinetic schemes. Since the selection of these networks is not unique, a concern is raised whether and under which conditions hierarchical schemes can reveal the same experimentally measured fluctuating behaviors and unique fluctuation related physical properties. To clarify these questions, we introduce stochasticity into the traditional lumping analysis, generalize it from rate equations to chemical master equations and stochastic differential equations, and extract the fluctuation relations between kinetically and thermodynamically equivalent networks under intrinsic and extrinsic noises. The results provide a theoretical basis for the legitimate use of low-dimensional models in the studies of macromolecular fluctuations and, more generally, for exploring stochastic features in different levels of contracted networks in chemical and biological kinetic systems.

Description: The behavior of water molecules at the surface of nonionic surfactant (monomyristolein) and effects of monovalent ions on the behavior are investigated using the heterodyne-detected vibrational sum frequency generation spectroscopy. It is found that water molecules at the surface are oriented with their hydrogen atoms pointing to the bulk, and that the degree of orientation depends on the anion strongly but weakly on the cation. With measured surface potentials in those saline solutions, it is concluded that the heterogeneous distribution of anions and cations in combination with the nonionic surfactant causes the water orientation. This heterogeneous distribution well explains the contrasting order of anions and cations with respect to the ion size in the Hofmeister series.

Description: Providing experimental values for absolute Dissociative Electron Attachment (DEA) cross sections for nucleobases at realistic biological conditions is a considerable challenge. In this work, we provide the temperature dependence of the cross section, σ, of the dehydrogenated thymine anion (T − H) − produced via DEA. Within the 393-443 K temperature range, it is observed that σ varies by one order of magnitude. By extrapolating to a temperature of 313 K, the relative DEA cross section for the production of the dehydrogenated thymine anion at an incident energy of 1 eV decreases by 2 orders of magnitude and the absolute value reaches approximately 6 × 10 −19 cm 2 . These quantitative measurements provide a benchmark for theoretical prediction and also a contribution to a more accurate description of the effects of ionizing radiation on molecular medium.

Description: The so-called extended law of corresponding states, as proposed by Noro and Frenkel [J. Chem. Phys. 113 , 2941 (2000)], involves a mapping of the phase behaviors of systems with short-range attractive interactions. While it has already extensively been applied to various model potentials, here we test its applicability to protein solutions with their complex interactions. We successfully map their experimentally determined metastable gas–liquid binodals, as available in the literature, to the binodals of short-range square-well fluids, as determined by previous as well as new Monte Carlo simulations. This is achieved by representing the binodals as a function of the temperature scaled with the critical temperature (or as a function of the reduced second virial coefficient) and the concentration scaled by the cube of an effective particle diameter, where the scalings take into account the attractive and repulsive contributions to the interaction potential, respectively. The scaled binodals of the protein solutions coincide with simulation data of the adhesive hard-sphere fluid. Furthermore, once the repulsive contributions are taken into account by the effective particle diameter, the temperature dependence of the reduced second virial coefficients follows a master curve that corresponds to a linear temperature dependence of the depth of the square-well potential. We moreover demonstrate that, based on this approach and cloud-point measurements only, second virial coefficients can be estimated, which we show to agree with values determined by light scattering or by Derjaguin-Landau-Verwey-Overbeek (DLVO)-based calculations.

Description: In order to identify two-step chemical mechanisms, we propose a method based on a small temperature modulation and on the analysis of the concentration oscillations of a single tagged species involved in the first step. The thermokinetic parameters of the first reaction step are first determined. Then, we build test functions that are constant only if the chemical system actually possesses some assumed two-step mechanism. Next, if the test functions plotted using experimental data are actually even, the mechanism is attributed and the obtained constant values provide the rate constants and enthalpy of reaction of the second step. The advantage of the protocol is to use the first step as a probe reaction to reveal the dynamics of the second step, which can hence be relieved of any tagging. The protocol is anticipated to apply to many mechanisms of biological relevance. As far as ligand binding is considered, our approach can address receptor conformational changes or dimerization as well as competition with or modulation by a second partner. The method can also be used to screen libraries of untagged compounds, relying on a tracer whose concentration can be spectroscopically monitored

Description: The hydration free energy (HFE) is a crucially important physical quantity to discuss various chemical processes in aqueous solutions. Although an explicit-solvent computation with molecular dynamics (MD) simulations is a preferable treatment of the HFE, huge computational load has been inevitable for large, complex solutes like proteins. In the present paper, we propose an efficient computation method for the HFE. In our method, the HFE is computed as a sum of 〈 U UV 〉/2 (〈 U UV 〉 is the ensemble average of the sum of pair interaction energy between solute and water molecule) and the water reorganization term mainly reflecting the excluded volume effect. Since 〈 U UV 〉 can readily be computed through a MD of the system composed of solute and water, an efficient computation of the latter term leads to a reduction of computational load. We demonstrate that the water reorganization term can quantitatively be calculated using the morphometric approach (MA) which expresses the term as the linear combinations of the four geometric measures of a solute and the corresponding coefficients determined with the energy representation (ER) method. Since the MA enables us to finish the computation of the solvent reorganization term in less than 0.1 s once the coefficients are determined, the use of the MA enables us to provide an efficient computation of the HFE even for large, complex solutes. Through the applications, we find that our method has almost the same quantitative performance as the ER method with substantial reduction of the computational load.

Description: X-ray absorption near edge structure (XANES) was measured at energies around the N K-edge of the pyrimidine-containing nucleotides, cytidine 5′-monophosphate (CMP), 2′-deoxythymidine 5′-monophosphate (dTMP), and uridine 5′-monophosphate (UMP), in aqueous solutions and in dried films under various pH conditions. The features of resonant excitations below the N K-edge in the XANES spectra for CMP, dTMP, and UMP changed depending on the pH of the solutions. The spectral change thus observed is systematically explained by the chemical shift of the core-levels of N atoms in the nucleobase moieties caused by structural changes due to protonation or deprotonation at different proton concentrations. This interpretation is supported by the results of theoretical calculations using density functional theory for the corresponding nucleobases in the neutral and protonated or deprotonated forms.

Description: This work investigates the computational design of a pH induced protein fold switch based on a self-consistent mean-field approach by identifying the ensemble averaged characteristics of sequences that encode a fold switch. The primary challenge to balance the alternative sets of interactions present in both target structures is overcome by simultaneously optimizing two foldability criteria corresponding to two target structures. The change in pH is modeled by altering the residual charge on the amino acids. The energy landscape of the fold switch protein is found to be double funneled. The fold switch sequences stabilize the interactions of the sites with similar relative surface accessibility in both target structures. Fold switch sequences have low sequence complexity and hence lower sequence entropy. The pH induced fold switch is mediated by attractive electrostatic interactions rather than hydrophobic-hydrophobic contacts. This study may provide valuable insights to the design of fold switch proteins.

Description: Molecular dynamics simulations in the NPT ensemble have been carried out to investigate the effect of two room temperature ionic liquids (RTILs), on stacks of phospholipid bilayers in water. We consider RTIL compounds consisting of chloride ([bmim][Cl]) and hexafluorophosphate ([bmim][PF 6 ]) salts of the 1-buthyl-3-methylimidazolium ([bmim] + ) cation, while the phospholipid bilayer is made of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC). Our investigations focus on structural and dynamical properties of phospholipid and water molecules that could be probed by inelastic and quasi-elastic neutron scattering measurements. The results confirm the fast incorporation of [bmim] + into the lipid phase already observed in previous simulations, driven by the Coulomb attraction of the cation for the most electronegative oxygens in the POPC head group and by sizeable dispersion forces binding the neutral hydrocarbon tails of [bmim] + and of POPC. The [bmim] + absorption into the bilayer favours the penetration of water into POPC, causes a slight but systematic thinning of the bilayer, and further stabilises hydrogen bonds at the lipid/water interface that already in pure samples (no RTIL) display a lifetime much longer than in bulk water. On the other hand, the effect of RTILs on the diffusion constant of POPC ( D POPC ) does not reveal a clearly identifiable trend, since D POPC increases upon addition of [bmim][Cl] and decreases in the [bmim][PF 6 ] case. Moreover, because of screening, the electrostatic signature of each bilayer is only moderately affected by the addition of RTIL ions in solution. The analysis of long wavelength fluctuations of the bilayers shows that RTIL sorption causes a general decrease of the lipid/water interfacial tension and bending rigidity, pointing to the destabilizing effect of RTILs on lipid bilayers.

Description: Markov state models are a widely used method for approximating the eigenspectrum of the molecular dynamics propagator, yielding insight into the long-timescale statistical kinetics and slow dynamical modes of biomolecular systems. However, the lack of a unified theoretical framework for choosing between alternative models has hampered progress, especially for non-experts applying these methods to novel biological systems. Here, we consider cross-validation with a new objective function for estimators of these slow dynamical modes, a generalized matrix Rayleigh quotient (GMRQ), which measures the ability of a rank- m projection operator to capture the slow subspace of the system. It is shown that a variational theorem bounds the GMRQ from above by the sum of the first m eigenvalues of the system’s propagator, but that this bound can be violated when the requisite matrix elements are estimated subject to statistical uncertainty. This overfitting can be detected and avoided through cross-validation. These result make it possible to construct Markov state models for protein dynamics in a way that appropriately captures the tradeoff between systematic and statistical errors.

Description: The hydration process of side chain analogue molecules differs from that of the actual amino acid side chains in peptides and proteins owing to the effects of the peptide backbone on the aqueous solvent environment. A recent molecular simulation study has provided evidence that all nonpolar side chains, attached to a short peptide backbone, are considerably less hydrophobic than the free side chain analogue molecules. In contrast to this, the hydrophilicity of the polar side chains is hardly affected by the backbone. To analyze the origin of these observations, we here present a molecular simulation study on temperature dependent solvation free energies of nonpolar and polar side chains attached to a short peptide backbone. The estimated solvation entropies and enthalpies of the various amino acid side chains are compared with existing side chain analogue data. The solvation entropies and enthalpies of the polar side chains are negative, but in absolute magnitude smaller compared with the corresponding analogue data. The observed differences are large; however, owing to a nearly perfect enthalpy-entropy compensation, the solvation free energies of polar side chains remain largely unaffected by the peptide backbone. We find that a similar compensation does not apply to the nonpolar side chains; while the backbone greatly reduces the unfavorable solvation entropies, the solvation enthalpies are either more favorable or only marginally affected. This results in a very small unfavorable free energy cost, or even free energy gain, of solvating the nonpolar side chains in strong contrast to solvation of small hydrophobic or nonpolar molecules in bulk water. The solvation free energies of nonpolar side chains have been furthermore decomposed into a repulsive cavity formation contribution and an attractive dispersion free energy contribution. We find that cavity formation next to the peptide backbone is entropically favored over formation of similar sized nonpolar side chain cavities in bulk water, in agreement with earlier work in the literature on analysis of cavity fluctuations at nonpolar molecular surfaces. The cavity and dispersion interaction contributions correlate quite well with the solvent accessible surface area of the nonpolar side chains attached to the backbone. This correlation however is weak for the overall solvation free energies owing to the fact that the cavity and dispersion free energy contributions are almost exactly cancelling each other.

Description: Synthetic nanomotors powered by chemical reactions have potential uses as cargo transport vehicles in both in vivo and in vitro applications. In many situations, motors will have to operate in out-of-equilibrium complex chemically reacting media, which supply fuel to the motors and remove the products they produce. Using molecular simulation and mean-field theory, this paper describes some of the new features that arise when a chemically powered nanomotor, operating through a diffusiophoretic mechanism, moves in an environment that supports an oscillatory chemical reaction network. It is shown how oscillations in the concentrations in chemical species in the environment give rise to oscillatory motor dynamics. More importantly, since the catalytic reactions on the motor that are responsible for its propulsion couple to the bulk phase reaction network, the motor can change its local environment. This process can give rise to distinctive spatiotemporal structures in reaction-diffusion media that occur as a result of active motor motion. Such locally induced nonequilibrium structure will play an important role in applications that involve motor dynamics in complex chemical media.

Description: A steady-state analysis for the catalytic turnover of molecules containing two substrate sites is presented. A broad class of Markovian dynamic models, motivated by the action of DNA modifying enzymes and the rich variety of translocation mechanisms associated with these systems (e.g., sliding, hopping, intersegmental transfer, etc.), is considered. The modeling suggests an elementary and general method of data analysis, which enables the extraction of the enzyme’s processivity directly and unambiguously from experimental data. This analysis is not limited to the initial velocity regime. The predictions are validated both against detailed numerical models and by revisiting published experimental data for EcoRI endonuclease acting on DNA.

Description: The process of protein search for specific binding sites on DNA is fundamentally important since it marks the beginning of all major biological processes. We present a theoretical investigation that probes the role of DNA sequence symmetry, heterogeneity, and chemical composition in the protein search dynamics. Using a discrete-state stochastic approach with a first-passage events analysis, which takes into account the most relevant physical-chemical processes, a full analytical description of the search dynamics is obtained. It is found that, contrary to existing views, the protein search is generally faster on DNA with more heterogeneous sequences. In addition, the search dynamics might be affected by the chemical composition near the target site. The physical origins of these phenomena are discussed. Our results suggest that biological processes might be effectively regulated by modifying chemical composition, symmetry, and heterogeneity of a genome.

Description: To interpret molecular dynamics simulations of complex systems, systematic dimensionality reduction methods such as principal component analysis (PCA) represent a well-established and popular approach. Apart from Cartesian coordinates, internal coordinates, e.g., backbone dihedral angles or various kinds of distances, may be used as input data in a PCA. Adopting two well-known model problems, folding of villin headpiece and the functional dynamics of BPTI, a systematic study of PCA using distance-based measures is presented which employs distances between C α -atoms as well as distances between inter-residue contacts including side chains. While this approach seems prohibitive for larger systems due to the quadratic scaling of the number of distances with the size of the molecule, it is shown that it is sufficient (and sometimes even better) to include only relatively few selected distances in the analysis. The quality of the PCA is assessed by considering the resolution of the resulting free energy landscape (to identify metastable conformational states and barriers) and the decay behavior of the corresponding autocorrelation functions (to test the time scale separation of the PCA). By comparing results obtained with distance-based, dihedral angle, and Cartesian coordinates, the study shows that the choice of input variables may drastically influence the outcome of a PCA.

Description: Importance sampling of trajectories has proved a uniquely successful strategy for exploring rare dynamical behaviors of complex systems in an unbiased way. Carrying out this sampling, however, requires an ability to propose changes to dynamical pathways that are substantial, yet sufficiently modest to obtain reasonable acceptance rates. Satisfying this requirement becomes very challenging in the case of long trajectories, due to the characteristic divergences of chaotic dynamics. Here, we examine schemes for addressing this problem, which engineer correlation between a trial trajectory and its reference path, for instance using artificial forces. Our analysis is facilitated by a modern perspective on Markov chain Monte Carlo sampling, inspired by non-equilibrium statistical mechanics, which clarifies the types of sampling strategies that can scale to long trajectories. Viewed in this light, the most promising such strategy guides a trial trajectory by manipulating the sequence of random numbers that advance its stochastic time evolution, as done in a handful of existing methods. In cases where this “noise guidance” synchronizes trajectories effectively, as the Glauber dynamics of a two-dimensional Ising model, we show that efficient path sampling can be achieved for even very long trajectories.

Description: Stochastic simulation for in silico studies of large biochemical networks requires a great amount of computational time. We recently proposed a new exact simulation algorithm, called the rejection-based stochastic simulation algorithm (RSSA) [Thanh et al. , J. Chem. Phys. 141 (13), 134116 (2014)], to improve simulation performance by postponing and collapsing as much as possible the propensity updates. In this paper, we analyze the performance of this algorithm in detail, and improve it for simulating large-scale biochemical reaction networks. We also present a new algorithm, called simultaneous RSSA (SRSSA), which generates many independent trajectories simultaneously for the analysis of the biochemical behavior. SRSSA improves simulation performance by utilizing a single data structure across simulations to select reaction firings and forming trajectories. The memory requirement for building and storing the data structure is thus independent of the number of trajectories. The updating of the data structure when needed is performed collectively in a single operation across the simulations. The trajectories generated by SRSSA are exact and independent of each other by exploiting the rejection-based mechanism. We test our new improvement on real biological systems with a wide range of reaction networks to demonstrate its applicability and efficiency.

Description: Recently, new insights into the relation between the geometry of the vessel that confines a fluid and its thermodynamic properties were traced through the study of cluster integrals for inhomogeneous fluids. In this work, I analyze the thermodynamic properties of fluids confined in wedges or by edges, emphasizing on the question of the region to which these properties refer. In this context, the relations between the line-thermodynamic properties referred to different regions are derived as analytic functions of the dihedral angle α , for 0 〈 α 〈 2 π , which enables a unified approach to both edges and wedges. As a simple application of these results, I analyze the properties of the confined gas in the low-density regime. Finally, using recent analytic results for the second cluster integral of the confined hard sphere fluid, the low density behavior of the line thermodynamic properties is analytically studied up to order two in the density for 0 〈 α 〈 2 π and by adopting different reference regions.

Description: The native state of a protein consists of an equilibrium of conformational states on an energy landscape rather than existing as a single static state. The co-existence of conformers with different ligand-affinities in a dynamical equilibrium is the basis for the conformational selection model for ligand binding. In this context, the development of theoretical methods that allow us to analyze not only the structural changes but also changes in the fluctuation patterns between conformers will contribute to elucidate the differential properties acquired upon ligand binding. Molecular dynamics simulations can provide the required information to explore these features. Its use in combination with subsequent essential dynamics analysis allows separating large concerted conformational rearrangements from irrelevant fluctuations. We present a novel procedure to define the size and composition of essential dynamics subspaces associated with ligand-bound and ligand-free conformations. These definitions allow us to compare essential dynamics subspaces between different conformers. Our procedure attempts to emphasize the main similarities and differences between the different essential dynamics in an unbiased way. Essential dynamics subspaces associated to conformational transitions can also be analyzed. As a test case, we study the glutaminase interacting protein (GIP), composed of a single PDZ domain. Both GIP ligand-free state and glutaminase L peptide-bound states are analyzed. Our findings concerning the relative changes in the flexibility pattern upon binding are in good agreement with experimental Nuclear Magnetic Resonance data.

Description: Evolution of proteins in bacteria and archaea living in different conditions leads to significant correlations between amino acid usage and environmental temperature. The origins of these correlations are poorly understood, and an important question of protein theory, physics-based prediction of types of amino acids overrepresented in highly thermostable proteins, remains largely unsolved. Here, we extend the random energy model of protein folding by weighting the interaction energies of amino acids by their frequencies in protein sequences and predict the energy gap of proteins designed to fold well at elevated temperatures. To test the model, we present a novel scalable algorithm for simultaneous energy calculation for many sequences in many structures, targeting massively parallel computing architectures such as graphics processing unit. The energy calculation is performed by multiplying two matrices, one representing the complete set of sequences, and the other describing the contact maps of all structural templates. An implementation of the algorithm for the CUDA platform is available at http://www.github.com/kzeldovich/galeprot and calculates protein folding energies over 250 times faster than a single central processing unit. Analysis of amino acid usage in 64-mer cubic lattice proteins designed to fold well at different temperatures demonstrates an excellent agreement between theoretical and simulated values of energy gap. The theoretical predictions of temperature trends of amino acid frequencies are significantly correlated with bioinformatics data on 191 bacteria and archaea, and highlight protein folding constraints as a fundamental selection pressure during thermal adaptation in biological evolution.

Description: Single molecule experiments and simulations have been widely used to characterize the unfolding and folding pathways of different proteins. However, with few exceptions, these tools have not been applied to study prion protein, PrP C , whose misfolded form PrP Sc can induce a group of fatal neurodegenerative diseases. Here, we apply novel atomistic modeling based on potential energy surface exploration to study the constant force unfolding of human PrP at time scales inaccessible with standard molecular dynamics. We demonstrate for forces around 100 pN, prion forms a stable, three-stranded β -sheet-like intermediate configuration containing residues 155-214 with a lifetime exceeding hundreds of nanoseconds. A mutant without the disulfide bridge shows lower stability during the unfolding process but still forms the three-stranded structure. The simulations thus not only show the atomistic details of the mechanically induced structural conversion from the native α -helical structure to the β -rich-like form but also lend support to the structural theory that there is a core of the recombinant PrP amyloid, a misfolded form reported to induce transmissible disease, mapping to C-terminal residues ≈160-220.

Description: The Saffman-Delbrück hydrodynamic model for lipid-bilayer membranes is modified to account for the periodic boundary conditions commonly imposed in molecular simulations. Predicted lateral diffusion coefficients for membrane-embedded solid bodies are sensitive to box shape and converge slowly to the limit of infinite box size, raising serious doubts for the prospects of using detailed simulations to accurately predict membrane-protein diffusivities and related transport properties. Estimates for the relative error associated with periodic boundary artifacts are 50% and higher for fully atomistic models in currently feasible simulation boxes. MARTINI simulations of LacY membrane protein diffusion and LacY dimer diffusion in DPPC membranes and lipid diffusion in pure DPPC bilayers support the underlying hydrodynamic model.

Description: Recent evidence suggests that quantum effects may have functional importance in biological light-harvesting systems. Along with delocalized electronic excitations, it is now suspected that quantum coherent interactions with certain near-resonant vibrations may contribute to light-harvesting performance. However, the actual quantum advantage offered by such coherent vibrational interactions has not yet been established. We investigate a quantum design principle, whereby coherent exchange of single energy quanta between electronic and vibrational degrees of freedom can enhance a light-harvesting system’s power above what is possible by thermal mechanisms alone. We present a prototype quantum heat engine which cleanly illustrates this quantum design principle and quantifies its quantum advantage using thermodynamic measures of performance. We also demonstrate the principle’s relevance in parameter regimes connected to natural light-harvesting structures.

Description: Recently, mid-infrared free-electron laser technology has been developed to dissociate amyloid fibrils. Here, we present a theoretical framework for this type of experiment based on laser-induced nonequilibrium all-atom molecular dynamics simulations. We show that the fibril is destroyed due to the strong resonance between its amide I vibrational modes and the laser field. The effects of laser irradiation are determined by a balance between fibril formation and dissociation. While the overall rearrangements of the fibril finish over short time scales, the interaction between the peptides and the solvent continues over much longer times indicating that the waters play an important role in the dissociation process. Our results thus provide new insights into amyloid fibril dissociation by laser techniques and open up new venues to investigate the complex phenomena associated with amyloidogenesis.

Description: The dynamics of the human oligonucleotide AG 3 (T 2 AG 3 ) 3 has been investigated by incoherent neutron scattering in the sub-nanosecond timescale. A hydration-dependent dynamical activation of thermal fluctuations in weakly hydrated samples was found, similar to that of protein powders. The amplitudes of such thermal fluctuations were evaluated in two different exchanged wave-vector ranges, so as to single out the different contributions from intra- and inter-nucleotide dynamics. The activation energy was calculated from the temperature-dependent characteristic times of the corresponding dynamical processes. The trends of both amplitudes and activation energies support a picture where oligonucleotides possess a larger conformational flexibility than long DNA sequences. This additional flexibility, which likely results from a significant relative chain-end contribution to the average chain dynamics, could be related to the strong structural polymorphism of the investigated oligonucleotides.

Description: Experimental studies (circular dichroism and ultra-violet (UV) absorption spectra) and large scale atomistic molecular dynamics simulations (accompanied by order parameter analyses) are combined to establish a number of remarkable (and unforeseen) structural transformations of protein myoglobin in aqueous ethanol mixture at various ethanol concentrations. The following results are particularly striking. (1) Two well-defined structural regimes, one at x EtOH ∼ 0.05 and the other at x EtOH ∼ 0.25, characterized by formation of distinct partially folded conformations and separated by a unique partially unfolded intermediate state at x EtOH ∼ 0.15, are identified. (2) Existence of non-monotonic composition dependence of (i) radius of gyration, (ii) long range contact order, (iii) residue specific solvent accessible surface area of tryptophan, and (iv) circular dichroism spectra and UV-absorption peaks are observed. Interestingly at x EtOH ∼ 0.15, time averaged value of the contact order parameter of the protein reaches a minimum, implying that this conformational state can be identified as a molten globule state. Multiple structural transformations well known in water-ethanol binary mixture appear to have considerably stronger effects on conformation and dynamics of the protein. We compare the present results with studies in water-dimethyl sulfoxide mixture where also distinct structural transformations are observed along with variation of co-solvent composition.

Description: We develop a fully stochastic theory for coagulation and fragmentation (CF) in a finite system with a maximum cluster size constraint. The process is modeled using a high-dimensional master equation for the probabilities of cluster configurations. For certain realizations of total mass and maximum cluster sizes, we find exact analytical results for the expected equilibrium cluster distributions. If coagulation is fast relative to fragmentation and if the total system mass is indivisible by the mass of the largest allowed cluster, we find a mean cluster-size distribution that is strikingly broader than that predicted by the corresponding mass-action equations. Combinations of total mass and maximum cluster size under which equilibration is accelerated, eluding late-stage coarsening, are also delineated. Finally, we compute the mean time it takes particles to first assemble into a maximum-sized cluster. Through careful state-space enumeration, the scaling of mean assembly times is derived for all combinations of total mass and maximum cluster size. We find that CF accelerates assembly relative to monomer kinetic only in special cases. All of our results hold in the infinite system limit and can be only derived from a high-dimensional discrete stochastic model, highlighting how classical mass-action models of self-assembly can fail.

Description: Fundamental biological processes of development of tissues and organs in multicellular organisms are governed by various signaling molecules, which are called morphogens. It is known that spatial and temporal variations in the concentration profiles of signaling molecules, which are frequently referred as morphogen gradients, lead to a cell differentiation via activating specific genes in a concentration-dependent manner. It is widely accepted that the establishment of the morphogen gradients involves multiple biochemical reactions and diffusion processes. One of the critical elements in the formation of morphogen gradients is a degradation of signaling molecules. We develop a new theoretical approach that provides a comprehensive description of the degradation mechanisms. It is based on the idea that the degradation works as an effective potential that drives the signaling molecules away from the source region. Utilizing the method of first-passage processes, the dynamics of the formation of morphogen gradients for various degradation mechanisms is explicitly evaluated. It is found that linear degradation processes lead to a dynamic behavior specified by times to form the morphogen gradients that depend linearly on the distance from the source. This is because the effective potential due to the degradation is quite strong. At the same time, nonlinear degradation mechanisms yield a quadratic scaling in the morphogen gradients formation times since the effective potentials are much weaker. Physical-chemical explanations of these phenomena are presented.

Description: The study of correlated mutations in alignments of homologous proteins proved to be successful not only in the prediction of their native conformation but also in the development of a two-body effective potential between pairs of amino acids. In the present work, we extend the effective potential, introducing a many-body term based on the same theoretical framework, making use of a principle of maximum entropy. The extended potential performs better than the two-body one in predicting the energetic effect of 308 mutations in 14 proteins (including membrane proteins). The average value of the parameters of the many-body term correlates with the degree of hydrophobicity of the corresponding residues, suggesting that this term partly reflects the effect of the solvent.

Description: The application of temperature replica exchange molecular dynamics (REMD) simulation on protein motion is limited by its huge requirement of computational resource, particularly when explicit solvent model is implemented. In the previous study, we developed a velocity-scaling optimized hybrid explicit/implicit solvent REMD method with the hope to reduce the temperature (replica) number on the premise of maintaining high sampling efficiency. In this study, we utilized this method to characterize and energetically identify the conformational transition pathway of a protein model, the N-terminal domain of calmodulin. In comparison to the standard explicit solvent REMD simulation, the hybrid REMD is much less computationally expensive but, meanwhile, gives accurate evaluation of the structural and thermodynamic properties of the conformational transition which are in well agreement with the standard REMD simulation. Therefore, the hybrid REMD could highly increase the computational efficiency and thus expand the application of REMD simulation to larger-size protein systems.

Description: We use computer simulations and a simple free energy model to study the response of a bilayer membrane to the application of a negative (compressive) mechanical tension. Such a tension destabilizes the long wavelength undulation modes of giant vesicles, but it can be sustained when small membranes and vesicles are considered. Our negative tension simulation results reveal two regimes—(i) a weak negative tension regime characterized by stretching-dominated elasticity and (ii) a strong negative tension regime featuring bending-dominated elastic behavior. This resembles the findings of the classic Evans and Rawicz micropipette aspiration experiment in giant unilamellar vesicles (GUVs) [E. Evans and W. Rawicz, Phys, Rev. Lett. 64 , 2094 (1990)]. However, in GUVs the crossover between the two elasticity regimes occurs at a small positive surface tension, while in smaller membranes it takes place at a moderate negative tension. Another interesting observation concerning the response of a small membrane to negative surface tension is related to the relationship between the mechanical and fluctuation tensions, which are equal to each other for non-negative values. When the tension decreases to negative values, the fluctuation tension γ drops somewhat faster than the mechanical tension τ in the small negative tension regime, before it saturates (and becomes larger than τ ) for large negative tensions. The bending modulus exhibits an “opposite” trend. It remains almost unchanged in the stretching-dominated elastic regime, and decreases in the bending-dominated regime. Both the amplitudes of the thermal height undulations and the projected area variations diverge at the onset of mechanical instability.

Description: Dielectric boundary based implicit-solvent models provide efficient descriptions of coarse-grained effects, particularly the electrostatic effect, of aqueous solvent. Recent years have seen the initial success of a new such model, variational implicit-solvent model (VISM) [Dzubiella, Swanson, and McCammon Phys. Rev. Lett. 96 , 087802 (2006) and J. Chem. Phys. 124 , 084905 (2006)], in capturing multiple dry and wet hydration states, describing the subtle electrostatic effect in hydrophobic interactions, and providing qualitatively good estimates of solvation free energies. Here, we develop a phase-field VISM to the solvation of charged molecules in aqueous solvent to include more flexibility. In this approach, a stable equilibrium molecular system is described by a phase field that takes one constant value in the solute region and a different constant value in the solvent region, and smoothly changes its value on a thin transition layer representing a smeared solute-solvent interface or dielectric boundary. Such a phase field minimizes an effective solvation free-energy functional that consists of the solute-solvent interfacial energy, solute-solvent van der Waals interaction energy, and electrostatic free energy described by the Poisson–Boltzmann theory. We apply our model and methods to the solvation of single ions, two parallel plates, and protein complexes BphC and p53/MDM2 to demonstrate the capability and efficiency of our approach at different levels. With a diffuse dielectric boundary, our new approach can describe the dielectric asymmetry in the solute-solvent interfacial region. Our theory is developed based on rigorous mathematical studies and is also connected to the Lum–Chandler–Weeks theory (1999). We discuss these connections and possible extensions of our theory and methods.

Description: We have calculated the electric polarizability of two types of lipid bilayers, formed by 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) and 1-palmitoyl-2- oleoyl-sn-glycero-3-phosphocholine (POPC) lipids. We demonstrate that despite the very similar chemical structures, the bilayers exhibit dramatically different terahertz infrared (IR) properties. We demonstrate that the chemical structure of the lipids influences the morphology of the bilayers, which in turn impacts their IR responses: interestingly, both structures exhibit a non-uniform absorption. For the case of DPPC, the infrared absorption is mostly driven by the hydrophilic heads, whereas for the POPC lipids, the absorption occurs predominately at the hydrophobic tails.

Description: We compare the performance of two well-established computational algorithms for the calculation of free-energy landscapes of biomolecular systems, umbrella sampling and metadynamics. We look at benchmark systems composed of polyethylene and polypropylene oligomers interacting with lipid (phosphatidylcholine) membranes, aiming at the calculation of the oligomer water-membrane free energy of transfer. We model our test systems at two different levels of description, united-atom and coarse-grained. We provide optimized parameters for the two methods at both resolutions. We devote special attention to the analysis of statistical errors in the two different methods and propose a general procedure for the error estimation in metadynamics simulations. Metadynamics and umbrella sampling yield the same estimates for the water-membrane free energy profile, but metadynamics can be more efficient, providing lower statistical uncertainties within the same simulation time.

Description: Coarse-grained models are useful tools to investigate the structural and thermodynamic properties of biomolecules. They are obtained by merging several atoms into one interaction site. Such simplified models try to capture as much as possible information of the original biomolecular system in all-atom representation but the resulting parameters of these coarse-grained force fields still need further optimization. In this paper, a force field optimization method, which is based on maximum-likelihood fitting of the simulated to the experimental conformational ensembles and least-squares fitting of the simulated to the experimental heat-capacity curves, is applied to optimize the Nucleic Acid united-RESidue 2-point (NARES-2P) model for coarse-grained simulations of nucleic acids recently developed in our laboratory. The optimized NARES-2P force field reproduces the structural and thermodynamic data of small DNA molecules much better than the original force field.

Description: We propose an analytic approach for calculating the electrostatic energy of proteins or protein complexes in aqueous solution. This method, termed CVCEL (Circular Variance Continuum ELectrostatics), is fitted to Poisson calculations and is able to reproduce the corresponding energies for different choices of solute dielectric constant. CVCEL thus treats both solute charge interactions and charge self-energies, and it can also deal with salt solutions. Electrostatic damping notably depends on the degree of solvent exposure of the charges, quantified here in terms of circular variance, a measure that reflects the vectorial distribution of the neighbors around a given center. CVCEL energies can be calculated rapidly and have simple analytical derivatives. This approach avoids the need for calculating effective atomic volumes or Born radii. After describing how the method was developed, we present test results for coarse-grain proteins of different shapes and sizes, using different internal dielectric constants and different salt concentrations and also compare the results with those from simple distance-dependent models. We also show that the CVCEL approach can be used successfully to calculate the changes in electrostatic energy associated with changes in protein conformation or with protein-protein binding.

Description: Validity of local equilibrium has been questioned for non-equilibrium systems which are characterized by delayed response. In particular, for systems with non-zero thermodynamic inertia, the assumption of local equilibrium leads to negative values of the entropy production, which is in contradiction with the second law of thermodynamics. In this paper, we address this question by suggesting a variational formulation of irreversible evolution of a system with non-zero thermodynamic inertia. We introduce the Lagrangian, which depends on the properties of the normal and the so-called “mirror-image” systems. We show that the standard evolution equations, in particular, the Maxwell-Cattaneo-Vernotte equation, can be derived from the variational procedure without going beyond the assumption of local equilibrium. We also argue that the second law of thermodynamics in non-equilibrium should be understood as a consequence of the variational procedure and the property of local equilibrium. For systems with instantaneous response this leads to the standard requirement of the local instantaneous entropy production being always positive. However, if a system is characterized by delayed response, the formulation of the second law of thermodynamics should be altered. In particular, the quantity, which is always positive, is not the instantaneous entropy production, but the entropy production averaged over a proper time interval.

Description: We demonstrate that different sets of Lennard-Jones parameters proposed for the Na + ion, in conjunction with the empirical combining rules routinely used in simulation packages, can lead to essentially different equilibrium structures for a deprotonated poly-L-glutamic acid molecule (poly-L-glutamate) dissolved in a 0.3M aqueous NaCl solution. It is, however, difficult to discriminate a priori between these model potentials; when investigating the structure of the Na + -solvation shell in bulk NaCl solution, all parameter sets lead to radial distribution functions and solvation numbers in broad agreement with the available experimental data. We do not find any such dependency of the equilibrium structure on the parameters associated with the Cl − ion. This work does not aim at recommending a particular set of parameters for any particular purpose. Instead, it stresses the model dependence of simulation results for complex systems such as biomolecules in solution and thus the difficulties if simulations are to be used for unbiased predictions, or to discriminate between contradictory experiments. However, this opens the possibility of validating a model specifically in view of analyzing experimental data believed to be reliable.

Description: The amino-keto tautomer of supersonic jet-cooled cytosine undergoes intersystem crossing (ISC) from the v = 0 and low-lying vibronic levels of its S 1 ( 1 ππ ∗ ) state. We investigate these ISC rates experimentally and theoretically as a function of S 1 state vibrational excess energy E exc . The S 1 vibronic levels are pumped with a ∼5 ns UV laser, the S 1 and triplet state ion signals are separated by prompt or delayed ionization with a second UV laser pulse. After correcting the raw ISC yields for the relative S 1 and T 1 ionization cross sections, we obtain energy dependent ISC quantum yields Q ISC corr = 1 % –5%. These are combined with previously measured vibronic state-specific decay rates, giving ISC rates k ISC = 0.4–1.5 ⋅ 10 9 s −1 , the corresponding S 1 ⇝ S 0 internal conversion (IC) rates are 30–100 times larger. Theoretical ISC rates are computed using SCS-CC2 methods, which predict rapid ISC from the S 1 ; v = 0 state with k ISC = 3 ⋅ 10 9 s −1 to the T 1 ( 3 ππ ∗ ) triplet state. The surprisingly high rate of this El Sayed-forbidden transition is caused by a substantial admixture of 1 n O π ∗ character into the S 1 ( 1 ππ ∗ ) wave function at its non-planar minimum geometry. The combination of experiment and theory implies that (1) below E exc = 550 cm −1 in the S 1 state, S 1 ⇝ S 0 internal conversion dominates the nonradiative decay with k IC ≥ 2 ⋅ 10 10 s −1 , (2) the calculated S 1 ⇝ T 1 ( 1 ππ ∗ ⇝ 3 ππ ∗ ) ISC rate is in good agreement with experiment, (3) being El-Sayed forbidden, the S 1 ⇝ T 1 ISC is moderately fast ( k ISC = 3 ⋅ 10 9 s −1 ), and not ultrafast, as claimed by other calculations, and (4) at E exc ∼ 550 cm −1 the IC rate increases by ∼50 times, probably by accessing the lowest conical intersection (the C5-twist CI) and thereby effectively switching off the ISC decay channels.

Description: Protein-protein interactions (PPIs) are involved in many cellular processes. Experimentally obtained protein quaternary structures provide the location of protein-protein interfaces, the surface region of a given protein that interacts with another. These regions are termed half-interfaces (HIs). Canonical HIs cover roughly one third of a protein’s surface and were found to have more hydrophobic residues than the non-interface surface region. In addition, the classical view of protein HIs was that there are a few (if not one) HIs per protein that are structurally and chemically unique. However, on average, a given protein interacts with at least a dozen others. This raises the question of whether they use the same or other HIs. By copying HIs from monomers with the same folds in solved quaternary structures, we introduce the concept of geometric HIs (HIs whose geometry has a significant match to other known interfaces) and show that on average they cover three quarters of a protein’s surface. We then demonstrate that in some cases, these geometric HI could result in real physical interactions (which may or may not be biologically relevant). The composition of the new HIs is on average more charged compared to most known ones, suggesting that the current protein interface database is biased towards more hydrophobic, possibly more obligate, complexes. Finally, our results provide evidence for interface fuzziness and PPI promiscuity. Thus, the classical view of unique, well defined HIs needs to be revisited as HIs are another example of coarse-graining that is used by nature.

Description: A measure of enzyme efficiency is proposed for an open reaction network that, in suitable form, applies to closed systems as well. The idea originates from the description of classical enzyme kinetics in terms of cycles. We derive analytical expressions for the efficiency measure by treating the network not only deterministically but also stochastically. The latter accounts for any significant amount of noise that can be present in biological systems and hence reveals its impact on efficiency. Numerical verification of the results is also performed. It is found that the deterministic equation overestimates the efficiency, the more so for very small system sizes. Roles of various kinetics parameters and system sizes on the efficiency are thoroughly explored and compared with the standard definition k 2 / K M . Study of substrate fluctuation also indicates an interesting efficiency-accuracy balance.

Description: The forced translocation of homopolymers through αβα sandwich-like compound channels was investigated by Monte Carlo simulation. The interaction between polymer and part α is strongly attractive, whereas that between polymer and part β is purely repulsive. Simulation results show that the translocation is influenced obviously by the length of part β ( L β ) and the starting position of part β ( L α1 ). For small L β , the translocation is mainly governed by the escaping process, and polymer is trapped near the exit of the channel. However, the translocation time can be tuned by varying L α1 and the fastest translocation can be achieved at relatively large L α1 . Whereas for large L β and small L α1 , the translocation is mainly controlled by the filling process. It is difficult for polymer to enter the channel, and polymer is trapped at the first αβ interface. Finally, the dynamics for the filling process and the escaping process are discussed from the view of free-energy landscape, respectively.

Description: We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy “ensemble refinement of SAXS” (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the “Bayesian inference of ensembles” method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.

Description: Many stochastic models of biochemical reaction networks contain some chemical species for which the number of molecules that are present in the system can only be finite (for instance due to conservation laws), but also other species that can be present in arbitrarily large amounts. The prime example of such networks are models of gene expression, which typically contain a small and finite number of possible states for the promoter but an infinite number of possible states for the amount of mRNA and protein. One of the main approaches to analyze such models is through the use of equations for the time evolution of moments of the chemical species. Recently, a new approach based on conditional moments of the species with infinite state space given all the different possible states of the finite species has been proposed. It was argued that this approach allows one to capture more details about the full underlying probability distribution with a smaller number of equations. Here, I show that the result that less moments provide more information can only stem from an unnecessarily complicated description of the system in the classical formulation. The foundation of this argument will be the derivation of moment equations that describe the complete probability distribution over the finite state space but only low-order moments over the infinite state space. I will show that the number of equations that is needed is always less than what was previously claimed and always less than the number of conditional moment equations up to the same order. To support these arguments, a symbolic algorithm is provided that can be used to derive minimal systems of unconditional moment equations for models with partially finite state space.

Description: Sterols play an essential role in modulating bilayer structure and dynamics. Coarse-grained molecular dynamics parameters for cholesterol and related molecules are available for the Martini force field and have been successfully used in multiple lipid bilayer studies. In this work, we focus on the use of virtual sites as a means of increasing the stability of cholesterol and cholesterol-like structures. We improve and extend the Martini parameterization of sterols in four different ways: 1—the cholesterol parameters were adapted to make use of virtual interaction sites, which markedly improves numerical stability; 2—cholesterol parameters were also modified to address reported shortcomings in reproducing correct lipid phase behavior in mixed membranes; 3—parameters for ergosterol were created and adapted from cholesterols; and 4—parameters for the hopanoid class of bacterial polycyclic molecules were created, namely, for hopane, diploptene, bacteriohopanetetrol, and for their polycyclic base structure.

Description: Predicting conformational changes of proteins is needed in order to fully comprehend functional mechanisms. With the large number of available structures in sets of related proteins, it is now possible to directly visualize the clusters of conformations and their conformational transitions through the use of principal component analysis. The most striking observation about the distributions of the structures along the principal components is their highly non-uniform distributions. In this work, we use principal component analysis of experimental structures of 50 diverse proteins to extract the most important directions of their motions, sample structures along these directions, and estimate their free energy landscapes by combining knowledge-based potentials and entropy computed from elastic network models. When these resulting motions are visualized upon their coarse-grained free energy landscapes, the basis for conformational pathways becomes readily apparent. Using three well-studied proteins, T4 lysozyme, serum albumin, and sarco-endoplasmic reticular Ca 2+ adenosine triphosphatase (SERCA), as examples, we show that such free energy landscapes of conformational changes provide meaningful insights into the functional dynamics and suggest transition pathways between different conformational states. As a further example, we also show that Monte Carlo simulations on the coarse-grained landscape of HIV-1 protease can directly yield pathways for force-driven conformational changes.

Description: The long range attractive force between two hydrophobic surfaces immersed in water is observed to decrease exponentially with their separation—this distance-dependence of effective force is known as the hydrophobic force law (HFL). We explore the microscopic origin of HFL by studying distance-dependent attraction between two parallel rods immersed in 2D Mercedes Benz model of water. This model is found to exhibit a well-defined HFL. Although the phenomenon is conventionally explained by density-dependent theories, we identify orientation, rather than density, as the relevant order parameter. The range of density variation is noticeably shorter than that of orientational heterogeneity. The latter is comparable to the observed distances of hydrophobic force. At large separation, attraction between the rods arises primarily from a destructive interference among the inwardly propagating oppositely oriented heterogeneity generated in water by the two rods. As the rods are brought closer, the interference increases leading to a decrease in heterogeneity and concomitant decrease in free energy of the system, giving rise to the effective attraction. We notice formation of hexagonal ice-like structures at the onset of attractive region which suggests that metastable free energy minimum may play a role in the origin of HFL.

Description: We performed monomolecular observations on linear and circular giant DNAs (208 kbp) in an aqueous solution by the use of fluorescence microscopy. The results showed that the degree of conformational fluctuation in circular DNA was ca. 40% less than that in linear DNA, although the long-axis length of circular DNA was only 10% smaller than that of linear DNA. Additionally, the relaxation time of a circular chain was shorter than that of a linear chain by at least one order of magnitude. The essential features of this marked difference between linear and circular DNAs were reproduced by numerical simulations on a ribbon-like macromolecule as a coarse-grained model of a long semiflexible, double-helical DNA molecule. In addition, we calculated the radius of gyration of an interacting chain in a circular form on the basis of the mean field model, which provides a better understanding of the present experimental trend than a traditional theoretical equation.

Description: In earlier works, we showed that the entropic effect originating from the translational displacement of water molecules plays the pivotal role in protein folding and denaturation. The two different solvent models, hard-sphere solvent and model water, were employed in theoretical methods wherein the entropic effect was treated as an essential factor. However, there were similarities and differences in the results obtained from the two solvent models. In the present work, to unveil the physical origins of the similarities and differences, we simultaneously consider structural transition, cold denaturation, and pressure denaturation for the same protein by employing the two solvent models and considering three different thermodynamic states for each solvent model. The solvent-entropy change upon protein folding/unfolding is decomposed into the protein-solvent pair (PA) and many-body (MB) correlation components using the integral equation theories. Each component is further decomposed into the excluded-volume (EV) and solvent-accessible surface (SAS) terms by applying the morphometric approach. The four physically insightful constituents, (PA, EV), (PA, SAS), (MB, EV), and (MB, SAS), are thus obtained. Moreover, (MB, SAS) is discussed by dividing it into two factors. This all-inclusive investigation leads to the following results: (1) the protein-water many-body correlation always plays critical roles in a variety of folding/unfolding processes; (2) the hard-sphere solvent model fails when it does not correctly reproduce the protein-water many-body correlation; (3) the hard-sphere solvent model becomes problematic when the dependence of the many-body correlation on the solvent number density and temperature is essential: it is not quite suited to studies on cold and pressure denaturating of a protein; (4) when the temperature and solvent number density are limited to the ambient values, the hard-sphere solvent model is usually successful; and (5) even at the ambient values, however, the many-body correlation plays significant roles in the β -sheet formation and argument of relative stabilities of very similar structures of a protein. These results are argued in detail with respect to the four physically insightful constituents and the two factors mentioned above. The relevance to the absence or presence of hydrogen-bonding properties in the solvent is also discussed in detail.

Description: We study noisy heterogeneous diffusion processes with a position dependent diffusivity of the form D ( x ) ∼ D 0 | x | α 0 in the presence of annealed and quenched disorder of the environment, corresponding to an effective variation of the exponent α in time and space. In the case of annealed disorder, for which effectively α 0 = α 0 ( t ), we show how the long time scaling of the ensemble mean squared displacement (MSD) and the amplitude variation of individual realizations of the time averaged MSD are affected by the disorder strength. For the case of quenched disorder, the long time behavior becomes effectively Brownian after a number of jumps between the domains of a stratified medium. In the latter situation, the averages are taken over both an ensemble of particles and different realizations of the disorder. As physical observables, we analyze in detail the ensemble and time averaged MSDs, the ergodicity breaking parameter, and higher order moments of the time averages.

Description: A recent experiment using fluorescence microscopy showed that double-stranded DNA fragments shorter than 100 base pairs loop with the probabilities higher by the factor of 10 2 –10 6 than predicted by the worm-like chain (WLC) model [R. Vafabakhsh and T. Ha, Science 337 , 1101(2012)]. Furthermore, the looping probabilities were found to be nearly independent of the loop size. The results signify a breakdown of the WLC model for DNA mechanics which works well on long length scales and calls for fundamental understanding for stressed DNA on shorter length scales. We develop an analytical, statistical mechanical model to investigate what emerges to the short DNA under a tight bending. A bending above a critical level initiates nucleation of a thermally induced bubble, which could be trapped for a long time, in contrast to the bubbles in both free and uniformly bent DNAs, which are either transient or unstable. The trapped bubble is none other than the previously hypothesized kink, which releases the bending energy more easily as the contour length decreases. It leads to tremendous enhancement of the cyclization probabilities, in a reasonable agreement with experiment.

Description: We report on measurements of integral cross sections (ICSs) for electron impact excitation of a series of composite vibrational modes and electronic-states in phenol, where the energy range of those experiments was 15–250 eV. There are currently no other results against which we can directly compare those measured data. We also report results from our independent atom model with screened additivity rule correction computations, namely, for the inelastic ICS (all discrete electronic states and neutral dissociation) and the total ionisation ICS. In addition, for the relevant dipole-allowed excited electronic states, we also report f -scaled Born-level and energy-corrected and f -scaled Born-level (BE f -scaled) ICS. Where possible, our measured and calculated ICSs are compared against one another with the general level of accord between them being satisfactory to within the measurement uncertainties.

Description: A fully atomistic modelling of many biophysical and biochemical processes at biologically relevant length- and time scales is beyond our reach with current computational resources, and one approach to overcome this difficulty is the use of multiscale simulation techniques. In such simulations, when system properties necessitate a boundary between resolutions that falls within the solvent region, one can use an approach such as the Adaptive Resolution Scheme (AdResS), in which solvent particles change their resolution on the fly during the simulation. Here, we apply the existing AdResS methodology to biomolecular systems, simulating a fully atomistic protein with an atomistic hydration shell, solvated in a coarse-grained particle reservoir and heat bath. Using as a test case an aqueous solution of the regulatory protein ubiquitin, we first confirm the validity of the AdResS approach for such systems, via an examination of protein and solvent structural and dynamical properties. We then demonstrate how, in addition to providing a computational speedup, such a multiscale AdResS approach can yield otherwise inaccessible physical insights into biomolecular function. We use our methodology to show that protein structure and dynamics can still be correctly modelled using only a few shells of atomistic water molecules. We also discuss aspects of the AdResS methodology peculiar to biomolecular simulations.

Description: Foldamers constructed from oligomers of β -peptides form stable secondary helix structures already for small chain lengths, which makes them ideal candidates for the investigation of the (un)folding of polypeptides. Here, the results of molecular simulations of the mechanical unfolding of a β -heptapeptide in methanol solvent revealing the detailed unfolding pathway are reported. The unfolding process is shown to proceed via a stable intermediate even for such a small system. This result is arrived at performing non-equilibrium force ramp simulations employing different pulling velocities and also using standard calculations of the potential of mean force, i.e., the free energy as a function of the helix elongation. It is thus demonstrated that even with the rather large pulling velocities employed in the force ramp simulations relevant information about the equilibrium kinetics can be obtained. The smallness of the system allows a detailed analysis of the unfolding pathway, which is characterized by an opening of the terminal loops followed by the unfolding of the center. This sequence is in accord with the configurational preferences of the system that also are responsible for the stability of the 3 14 -helix. From an analysis of the distributions of rupture forces and the force spectra, the kinetic rates for both transitions were determined and common models were used to extract geometric quantities describing the free energy landscape of the system.

Description: The excited-state relaxation of retinal protonated Schiff bases (PSBs) is an important test case for biological applications of time-dependent (TD) density-functional theory (DFT). While well-known shortcomings of approximate TD-DFT might seem discouraging for application to PSB relaxation, progress continues to be made in the development of new functionals and of criteria allowing problematic excitations to be identified within the framework of TD-DFT itself. Furthermore, experimental and theoretical ab initio advances have recently lead to a revised understanding of retinal PSB photochemistry, calling for a reappraisal of the performance of TD-DFT in describing this prototypical photoactive system. Here, we re-investigate the performance of functionals in (TD-)DFT calculations in light of these new benchmark results, which we extend to larger PSB models. We focus on the ability of the functionals to describe primarily the early skeletal relaxation of the chromophore and investigate how far along the out-of-plane pathways these functionals are able to describe the subsequent rotation around formal single and double bonds. Conventional global hybrid and range-separated hybrid functionals are investigated as the presence of Hartree-Fock exchange reduces problems with charge-transfer excitations as determined by the Peach-Benfield-Helgaker-Tozer Λ criterion and by comparison with multi-reference perturbation theory results. While we confirm that most functionals cannot render the complex photobehavior of the retinal PSB, do we also observe that LC-BLYP gives the best description of the initial part of the photoreaction.

Description: The analysis of trajectories recorded in experiments often requires calculating time averages instead of ensemble averages. According to the Boltzmann hypothesis, they are equivalent only under the assumption of ergodicity. In this paper, we implement tools that allow to study ergodic properties. This analysis is conducted in two classes of anomalous diffusion processes: fractional Brownian motion and subordinated Ornstein-Uhlenbeck process. We show that only first of them is ergodic. We demonstrate this by applying rigorous statistical methods: mean square displacement, confidence intervals, and dynamical functional test. Our methodology is universal and can be implemented for analysis of many experimental data not only if a large sample is available but also when there are only few trajectories recorded.

Description: In a cell, the folding of a protein molecule into tertiary structure can begin while it is synthesized by the ribosome. The rate at which individual amino acids are incorporated into the elongating nascent chain has been shown to affect the likelihood that proteins will populate their folded state, indicating that co-translational protein folding is a far from equilibrium process. Developing a theoretical framework to accurately describe this process is, therefore, crucial for advancing our understanding of how proteins acquire their functional conformation in living cells. Current state-of-the-art computational approaches, such as molecular dynamics simulations, are very demanding in terms of the required computer resources, making the simulation of co-translational protein folding difficult. Here, we overcome this limitation by introducing an efficient approach that predicts the effects that variable codon translation rates have on co-translational folding pathways. Our approach is based on Markov chains. By using as an input a relatively small number of molecular dynamics simulations, it allows for the computation of the probability that a nascent protein is in any state as a function of the translation rate of individual codons along a mRNA’s open reading frame. Due to its computational efficiency and favorable scalability with the complexity of the folding mechanism, this approach could enable proteome-wide computational studies of the influence of translation dynamics on co-translational folding.

Description: Fibril formation resulting from protein misfolding and aggregation is a hallmark of several neurodegenerative diseases such as Alzheimer’s and Parkinson’s diseases. Despite the fact that the fibril formation process is very slow and thus poses a significant challenge for theoretical and experimental studies, a number of alternative pictures of molecular mechanisms of amyloid fibril formation have been recently proposed. What seems to be common for the majority of the proposed models is that fibril elongation involves the formation of pre-nucleus seeds prior to the creation of a critical nucleus. Once the size of the pre-nucleus seed reaches the critical nucleus size, its thermal fluctuations are expected to be small and the resulting nucleus provides a template for sequential (one-by-one) accommodation of added monomers. The effect of template fluctuations on fibril formation rates has not been explored either experimentally or theoretically so far. In this paper, we make the first attempt at solving this problem by two sets of simulations. To mimic small template fluctuations, in one set, monomers of the preformed template are kept fixed, while in the other set they are allowed to fluctuate. The kinetics of addition of a new peptide onto the template is explored using all-atom simulations with explicit water and the GROMOS96 43a1 force field and simple lattice models. Our result demonstrates that preformed template fluctuations can modulate protein aggregation rates and pathways. The association of a nascent monomer with the template obeys the kinetics partitioning mechanism where the intermediate state occurs in a fraction of routes to the protofibril. It was shown that template immobility greatly increases the time of incorporating a new peptide into the preformed template compared to the fluctuating template case. This observation has also been confirmed by simulation using lattice models and may be invoked to understand the role of template fluctuations in slowing down fibril elongation in vivo .

Description: In Monte-Carlo simulations of protein folding, pathways and folding times depend on the appropriate choice of the Monte-Carlo move or process path. We developed a generalized set of process paths for a hybrid kinetic Monte Carlo—Molecular dynamics algorithm, which makes use of a novel constant time-update and allows formation of α -helical and β -stranded secondary structures. We apply our new algorithm to the folding of 3 different proteins: TrpCage, GB1, and TrpZip4. All three systems are seen to fold within the range of the experimental folding times. For the β -hairpins, we observe that loop formation is the rate-determining process followed by collapse and formation of the native core. Cluster analysis of both peptides reveals that GB1 folds with equal likelihood along a zipper or a hydrophobic collapse mechanism, while TrpZip4 follows primarily a zipper pathway. The difference observed in the folding behavior of the two proteins can be attributed to the different arrangements of their hydrophobic core, strongly packed, and dry in case of TrpZip4, and partially hydrated in the case of GB1.

Description: Advances in DNA nanotechnology have stimulated the search for simple motifs that can be used to control the properties of DNA nanostructures. One such motif, which has been used extensively in structures such as polyhedral cages, two-dimensional arrays, and ribbons, is a bulged duplex, that is, two helical segments that connect at a bulge loop. We use a coarse-grained model of DNA to characterize such bulged duplexes. We find that this motif can adopt structures belonging to two main classes: one where the stacking of the helices at the center of the system is preserved, the geometry is roughly straight, and the bulge is on one side of the duplex and the other where the stacking at the center is broken, thus allowing this junction to act as a hinge and increasing flexibility. Small loops favor states where stacking at the center of the duplex is preserved, with loop bases either flipped out or incorporated into the duplex. Duplexes with longer loops show more of a tendency to unstack at the bulge and adopt an open structure. The unstacking probability, however, is highest for loops of intermediate lengths, when the rigidity of single-stranded DNA is significant and the loop resists compression. The properties of this basic structural motif clearly correlate with the structural behavior of certain nano-scale objects, where the enhanced flexibility associated with larger bulges has been used to tune the self-assembly product as well as the detailed geometry of the resulting nanostructures. We further demonstrate the role of bulges in determining the structure of a “Z-tile,” a basic building block for nanostructures.

Description: Estimating the relative stabilities of different conformational states of a (bio-)molecule using molecular dynamics simulations involves two challenging problems: the conceptual problem of how to define the states of interest and the technical problem of how to properly sample these states, along with achieving a sufficient number of interconversion transitions. In this study, the two issues are addressed in the context of a decaalanine peptide in water, by considering the 3 10 -, α -, and π -helical states. The simulations rely on the ball-and-stick local-elevation umbrella-sampling (B&S-LEUS) method. In this scheme, the states are defined as hyperspheres (balls) in a (possibly high dimensional) collective-coordinate space and connected by hypercylinders (sticks) to ensure transitions. A new object, the pipe, is also introduced here to handle curvilinear pathways. Optimal sampling within the so-defined space is ensured by confinement and (one-dimensional) memory-based biasing potentials associated with the three different kinds of objects. The simulation results are then analysed in terms of free energies using reweighting, possibly relying on two distinct sets of collective coordinates for the state definition and analysis. The four possible choices considered for these sets are Cartesian coordinates, hydrogen-bond distances, backbone dihedral angles, or pairwise sums of successive backbone dihedral angles. The results concerning decaalanine underline that the concept of conformational state may be extremely ambiguous, and that its tentative absolute definition as a free-energy basin remains subordinated to the choice of a specific analysis space. For example, within the force-field employed and depending on the analysis coordinates selected, the 3 10 -helical state may refer to weakly overlapping collections of conformations, differing by as much as 25 kJ mol −1 in terms of free energy. As another example, the π -helical state appears to correspond to a free-energy basin for three choices of analysis coordinates, but to be unstable with the fourth one. The problem of conformational-state definition may become even more intricate when comparison with experiment is involved, where the state definition relies on spectroscopic or functional observables.

Description: We introduce an extended version of oxDNA, a coarse-grained model of deoxyribonucleic acid (DNA) designed to capture the thermodynamic, structural, and mechanical properties of single- and double-stranded DNA. By including explicit major and minor grooves and by slightly modifying the coaxial stacking and backbone-backbone interactions, we improve the ability of the model to treat large (kilobase-pair) structures, such as DNA origami, which are sensitive to these geometric features. Further, we extend the model, which was previously parameterised to just one salt concentration ([Na + ] = 0.5M), so that it can be used for a range of salt concentrations including those corresponding to physiological conditions. Finally, we use new experimental data to parameterise the oxDNA potential so that consecutive adenine bases stack with a different strength to consecutive thymine bases, a feature which allows a more accurate treatment of systems where the flexibility of single-stranded regions is important. We illustrate the new possibilities opened up by the updated model, oxDNA2, by presenting results from simulations of the structure of large DNA objects and by using the model to investigate some salt-dependent properties of DNA.

Description: Using rare event simulation techniques, we calculated DNA denaturation rate constants for a range of sequences and temperatures for the Peyrard-Bishop-Dauxois (PBD) model with two different parameter sets. We studied a larger variety of sequences compared to previous studies that only consider DNA homopolymers and DNA sequences containing an equal amount of weak AT- and strong GC-base pairs. Our results show that, contrary to previous findings, an even distribution of the strong GC-base pairs does not always result in the fastest possible denaturation. In addition, we applied an adaptation of the PBD model to study hairpin denaturation for which experimental data are available. This is the first quantitative study in which dynamical results from the mesoscopic PBD model have been compared with experiments. Our results show that present parameterized models, although giving good results regarding thermodynamic properties, overestimate denaturation rates by orders of magnitude. We believe that our dynamical approach is, therefore, an important tool for verifying DNA models and for developing next generation models that have higher predictive power than present ones.

Description: The coupling between protein conformation, molecular volume, and solution phase behaviour is studied theoretically for a two-state, coarse-grained protein model in which protein molecules can reversibly switch between a native and a non-native excited state. In the model, native and non-native conformers are represented by perfect spheres with different hard-core diameters. We presume the larger, non-native species to attract each other through some unspecified potential. We find that at low concentrations the native state is stabilised energetically and that at high concentrations the native state is again stabilised but this time by self-crowding, i.e., a lack of free volume. These two regimes are separated by two first-order transitions from a region where the non-native conformational state is prevalent, stabilised by attractive interactions between the proteins. The calculated phase diagram is very sensitive to even quite small differences in particle volumes and has unusual features, including the loss of a critical point if the size difference is sufficiently large.