ALBERT

Beschreibung: 〈p〉Publication date: Available online 28 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Biophysical Journal〈/p〉 〈p〉Author(s): Daniel Trotter, Stefan Wallin〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Experiments have compared the folding of proteins with different amino acid sequences but the same basic structure, or fold. Results indicate that folding is robust to sequence variations for proteins with some nonlocal folds, such as all-〈em〉β〈/em〉, while the folding of more local, all-〈em〉α〈/em〉 proteins typically exhibit a stronger sequence dependence. Here we use a coarse-grained model to systematically study how variations in sequence perturb the folding energy landscapes of three model sequences with 3〈em〉α〈/em〉, 4〈sup〉β+α〈/sup〉 and 〈em〉β〈/em〉-barrel folds, respectively. These three proteins exhibit folding features in line with experiments, including expected rank order in the cooperativity of the folding transition and stability-dependent shifts in the location of the free energy barrier to folding. Using a generalized-ensemble simulation approach, we determine the thermodynamics of around 2,000 sequence variants representing all possible hydrophobic/polar single- and double-point mutations. From an analysis of the subset of stability neutral mutations we find that folding is perturbed in a topology-dependent manner, with the 〈em〉β〈/em〉-barrel protein being the most robust. Our analysis shows, in particular, that the magnitude of mutational perturbations of the transition state is controlled in part by the size or “width” of the underlying conformational ensemble. This result suggests that the mutational robustness of the folding of the 〈em〉β〈/em〉-barrel protein is underpinned by its conformationally restricted transition state ensemble, revealing a link between sequence and topological effects in protein folding.〈/p〉〈/div〉

Beschreibung: 〈p〉Publication date: Available online 28 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Biophysical Journal〈/p〉 〈p〉Author(s): Reut Israeli, Sofiya Kolusheva, Uzi Hadad, Raz Jelinek〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Membrane interactions of amyloidogenic proteins constitute central determinants both in protein aggregation as well as amyloid cytotoxicity. Most reported studies of amyloid peptide-membrane interactions have employed model membrane systems, combined with application of spectroscopy methods or microscopy analysis of individual binding events. Here, we applied for the first time imaging flow cytometry for investigating interactions of representative amyloidogenic peptides – the 102-126 fragment of prion protein [PrP(106-126)], and the human Islet Amyloid Polypeptide (hIAPP) – with giant lipid vesicles. Imaging flow cytometry was also applied to examine the inhibition of PrP(106-126)-membrane interactions by epigallocatechin gallate (EGCG), a known modulator of amyloid peptide aggregation. We show that imaging flow cytometry provided comprehensive population-based statistical information upon morphology changes of the vesicles induced by PrP(106-126) and hIAPP. Specifically, the experiments reveal that both PrP(106-126) and hIAPP induced dramatic transformations of the vesicles, specifically disruption of the spherical shapes, reduction of vesicle circularity, lobe formation, and modulation of vesicle compactness. Interesting differences, however, were apparent between the impact of the two peptides upon the model membranes. The morphology analysis also showed that EGCG ameliorated vesicle disruption by PrP(106-126). Overall, this study demonstrates that imaging flow cytometry provides powerful means for disclosing population-based morphological membrane transformations induced by amyloidogenic peptides and their inhibition by aggregation modulators.〈/p〉〈/div〉

Beschreibung: 〈p〉Publication date: Available online 22 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Biophysical Journal〈/p〉 〈p〉Author(s): Wajih Anwer, Amanda Ratto Velasquez, Valeria Tsoukanova〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Excessive accumulation of acylcarnitines (ACs), often caused by metabolic disorders, has been associated with obesity, arrhythmias, cardiac ischemia, insulin resistance, etc. Mechanisms whereby elevated ACs might contribute to pathophysiological effects remain largely unexplored. We have aimed to gain insight into AC interactions with the mitochondrial inner membrane. To model its outer leaflet, Langmuir monolayers and cushioned supported bilayers were employed. Their interactions with ACs were monitored with epifluorescence microscopy, which revealed a local leaflet expansion upon exposure to elevated concentrations of a long-chain AC, plausibly caused by its insertion. To assess the AC insertion parameters, constant pressure insertion assays were performed. A value of 21 ± 3 Å〈sup〉2〈/sup〉 was obtained for the AC insertion area, which is roughly the same as the cross-sectional area of an acyl chain. By contrast, the carnitine moiety was found to require an area of 37 ± 3 Å〈sup〉2〈/sup〉. The AC insertion has thus been concluded to involve solely the AC acyl chain. This mode of insertion implies that the carnitine moiety with its nontitratable positive charge is left dangling at the membrane surface, which is likely to alter the surface electrostatics of the outer leaflet. The extrapolation of these findings has enabled us to hypothesize that, by altering the morphology and surface electrostatics of the outer leaflet, the insertion of ACs, in particular their long-chain counterparts, may trigger a nonspecific activation of signaling pathways in the inner mitochondrial membrane thereby modulating its function and potentially leading to pathophysiological responses.〈/p〉〈/div〉

Beschreibung: 〈p〉Publication date: Available online 22 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Biophysical Journal〈/p〉 〈p〉Author(s): Chris Neale, Angel E. García〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Mutant Ras proteins are important drivers of human cancers, yet no approved drugs act directly on this difficult target. Over the last decade, the idea has emerged that oncogenic signaling can be diminished by molecules that drive Ras into orientations in which effector binding interfaces are occluded by the cell membrane. To support this approach to drug discovery, we characterize the orientational preferences of membrane-bound K-Ras4B in 1.45 milliseconds aggregate time of atomistic molecular dynamics simulations. Individual simulations probe active or inactive states of Ras on membranes with or without anionic lipids. We find that the membrane orientation of Ras is relatively insensitive to its bound guanine nucleotide and activation state but depends strongly on interactions with anionic phosphatidylserine lipids. These lipids slow Ras’ translational and orientational diffusion and promote a discrete population in which small changes in orientation control Ras’ competence to bind multiple regulator and effector proteins. Our results suggest that compound-directed conversion of constitutively active mutant Ras into functionally inactive forms may be accessible via subtle perturbations of Ras’ orientational preferences at the membrane surface.〈/p〉〈/div〉

Beschreibung: 〈p〉Publication date: Available online 23 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Biophysical Journal〈/p〉 〈p〉Author(s): Jun Wang, Chitra Karki, Yi Xiao, Lin Li〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Ribosomes are essential machines for protein synthesis in cells. Their structures are very complex but conserved in different species. Since most parts of a ribosome are composed of negatively charged RNAs, its electrostatics should play a fundamental role in the realization of its functions. However, a complete picture of the electrostatics of ribosomes is still absent at present. Here, assisted by the latest version of DelPhi (Version: 8.4), we illustrate a picture of the electrostatics of a prokaryotic ribosome as well as its molecular chaperones. The revealed electrostatics features are well consistent with available experimental data as well as the functions of the ribosome and its molecular chaperones and provides a basis for further studying the mechanism underlying these functions.〈/p〉〈/div〉

Beschreibung: 〈p〉Publication date: Available online 23 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Biophysical Journal〈/p〉 〈p〉Author(s): T.B. Brouwer, N. Hermans, J. van Noort〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Many single-molecule biophysical techniques rely on nanometric tracking of microbeads to obtain quantitative information about the mechanical properties of biomolecules such as chromatin fibers. Their three-dimensional position can be resolved by holographic analysis of the diffraction pattern in wide-field imaging. Fitting this diffraction pattern to Lorentz Mie scattering theory yields the bead position with nanometer accuracy in three dimensions but is computationally expensive. Real-time multiplexed bead tracking therefore requires a more efficient tracking method, such as comparison with previously measured diffraction patterns, known as look-up tables (LUT). Here, we introduce an alternative 3D phasor algorithm, that provides robust bead tracking with nanometric localization accuracy in a 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"〉〈mi〉z〈/mi〉〈/math〉〈em〉-〈/em〉range of over 10 μm under non-optimal imaging conditions. The algorithm is based on a 2D cross-correlation using Fast Fourier Transforms with computer-generated reference images, yielding a processing rate of up to 10,000 regions of interest per second. We implemented the technique in magnetic tweezers and tracked the 3D position of over 100 beads in real-time on a generic CPU. The accuracy of 3D Phasor tracking was extensively tested and compared to a LUT approach using Lorentz Mie simulations, avoiding experimental uncertainties. Its easy implementation, efficiency, and robustness can improve multiplexed biophysical bead tracking applications, especially where high throughput is required and image artefacts are difficult to avoid.〈/p〉〈/div〉

Beschreibung: 〈p〉Publication date: Available online 22 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Biophysical Journal〈/p〉 〈p〉Author(s): Francisco Sahli-Costabal, Kinya Seo, Euan Ashley, Ellen Kuhl〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉All medications have adverse effects. Among the most serious of these are cardiac arrhythmias. Current paradigms for drug safety evaluation are costly, lengthy, conservative, and impede efficient drug development. Here we combine multiscale experiment and simulation, high-performance computing, and machine learning to create a risk estimator to stratify new and existing drugs according to their pro-arrhythmic potential. We capitalize on recent developments in machine learning and integrate information across ten orders of magnitude in space and time to provide a holistic picture of the effects of drugs, either individually or in combination with other drugs. We show, both experimentally and computationally, that drug-induced arrhythmias are dominated by the interplay between two currents with opposing effects: the rapid delayed rectifier potassium current and the L-type calcium current. Using Gaussian process classification, we create a classifier that stratifies drugs into safe and arrhythmic domains for any combinations of these two currents. We demonstrate that our classifier correctly identifies the risk categories of 22 common drugs, exclusively on the basis of their concentrations at 50% current block. Our new risk assessment tool explains under which conditions blocking the L-type calcium current can delay or even entirely suppress arrhythmogenic events. Using machine learning in drug safety evaluation can provide a more accurate and comprehensive mechanistic assessment of the pro-arrhythmic potential of new drugs. Our study paves the way towards establishing science-based criteria to accelerate drug development, design safer drugs, and reduce heart rhythm disorders.〈/p〉〈/div〉

Beschreibung: 〈p〉Publication date: Available online 22 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Biophysical Journal〈/p〉 〈p〉Author(s): Alemayehu A. Gorfe, Stephen G. Sligar〈/p〉

Beschreibung: 〈p〉Publication date: Available online 22 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Biophysical Journal〈/p〉 〈p〉Author(s): Christopher T. Lee, Justin G. Laughlin, John B. Moody, Rommie E. Amaro, J. Andrew McCammon, Michael J. Holst, Padmini Rangamani〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Advances in imaging methods such as electron microscopy, tomography, and other modalities are enabling high-resolution reconstructions of cellular and organelle geometries. Such advances pave the way for using these geometries for biophysical and mathematical modeling once these data can be represented as a geometric mesh, which, when carefully conditioned, enables the discretization and solution of partial differential equations. In this study, we outline the steps for a naïve user to approach 〈code〉GAMer 2〈/code〉, a mesh generation code written in C++ designed to convert structural datasets to realistic geometric meshes, while preserving the underlying shapes. We present two example cases, 1) mesh generation at the subcellular scale as informed by electron tomography, and 2) meshing a protein with structure from x-ray crystallography. We further demonstrate that the meshes generated by 〈code〉GAMer〈/code〉 are suitable for use with numerical methods. Together, this collection of libraries and tools simplifies the process of constructing realistic geometric meshes from structural biology data.〈/p〉〈/div〉

Beschreibung: 〈p〉Publication date: Available online 28 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Biophysical Journal〈/p〉 〈p〉Author(s): Brian P. Josey, Frank Heinrich, Vitalii Silin, Mathias Lösche〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Aimed to reproduce the results of electrophysiological studies of synaptic signal transduction, conventional models of neurotransmission are based on the specific binding of neurotransmitters to ligand-gated receptor ion channels. However, the complex kinetic behavior observed in synaptic transmission cannot be reproduced in a standard kinetic model without the ad hoc postulation of additional conformational channel states. On the other hand, if one invokes unspecific neurotransmitter adsorption to the bilayer—a process not considered in the established models—the electrophysiological data can be rationalized with only the standard set of three conformational receptor states that also depend on this indirect coupling of neurotransmitters via their membrane interaction. Experimental verification has been difficult because binding affinities of neurotransmitters to the lipid bilayer are low. We quantify this interaction with surface plasmon resonance to measure equilibrium dissociation constants in neurotransmitter membrane association. Neutron reflection measurements on artificial membranes, so-called sparsely-tethered bilayer lipid membranes (stBLMs), reveal the structural aspects of neurotransmitters association with zwitterionic and anionic bilayers. We thus establish that serotonin interacts non-specifically with the membrane at physiologically relevant concentrations whilst GABA (γ-aminobutyric acid) does not. Surface plasmon resonance shows that serotonin adsorbs with millimolar affinity and neutron reflectometry shows that it penetrates the membrane deeply whereas GABA is excluded from the bilayer.〈/p〉〈/div〉