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  • 1
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    American Association for the Advancement of Science (AAAS)
    Publication Date: 2001-10-06
    Description: Genome sequencing projects are producing linear amino acid sequences, but full understanding of the biological role of these proteins will require knowledge of their structure and function. Although experimental structure determination methods are providing high-resolution structure information about a subset of the proteins, computational structure prediction methods will provide valuable information for the large fraction of sequences whose structures will not be determined experimentally. The first class of protein structure prediction methods, including threading and comparative modeling, rely on detectable similarity spanning most of the modeled sequence and at least one known structure. The second class of methods, de novo or ab initio methods, predict the structure from sequence alone, without relying on similarity at the fold level between the modeled sequence and any of the known structures. In this Viewpoint, we begin by describing the essential features of the methods, the accuracy of the models, and their application to the prediction and understanding of protein function, both for single proteins and on the scale of whole genomes. We then discuss the important role that protein structure prediction methods play in the growing worldwide effort in structural genomics.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Baker, D -- Sali, A -- GM 54762/GM/NIGMS NIH HHS/ -- New York, N.Y. -- Science. 2001 Oct 5;294(5540):93-6.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA. dabaker@u.washington.edu.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/11588250" target="_blank"〉PubMed〈/a〉
    Keywords: Amino Acid Sequence ; Animals ; Binding Sites ; *Computational Biology ; Computer Simulation ; Databases, Factual ; *Genomics ; Humans ; Internet ; *Models, Molecular ; *Protein Conformation ; Protein Folding ; Protein Structure, Tertiary ; Proteins/*chemistry/genetics/physiology ; Sequence Alignment ; Software ; Templates, Genetic
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 2
    Publication Date: 2015-12-18
    Description: Tandem repeat proteins, which are formed by repetition of modular units of protein sequence and structure, play important biological roles as macromolecular binding and scaffolding domains, enzymes, and building blocks for the assembly of fibrous materials. The modular nature of repeat proteins enables the rapid construction and diversification of extended binding surfaces by duplication and recombination of simple building blocks. The overall architecture of tandem repeat protein structures--which is dictated by the internal geometry and local packing of the repeat building blocks--is highly diverse, ranging from extended, super-helical folds that bind peptide, DNA, and RNA partners, to closed and compact conformations with internal cavities suitable for small molecule binding and catalysis. Here we report the development and validation of computational methods for de novo design of tandem repeat protein architectures driven purely by geometric criteria defining the inter-repeat geometry, without reference to the sequences and structures of existing repeat protein families. We have applied these methods to design a series of closed alpha-solenoid repeat structures (alpha-toroids) in which the inter-repeat packing geometry is constrained so as to juxtapose the amino (N) and carboxy (C) termini; several of these designed structures have been validated by X-ray crystallography. Unlike previous approaches to tandem repeat protein engineering, our design procedure does not rely on template sequence or structural information taken from natural repeat proteins and hence can produce structures unlike those seen in nature. As an example, we have successfully designed and validated closed alpha-solenoid repeats with a left-handed helical architecture that--to our knowledge--is not yet present in the protein structure database.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4727831/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4727831/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Doyle, Lindsey -- Hallinan, Jazmine -- Bolduc, Jill -- Parmeggiani, Fabio -- Baker, David -- Stoddard, Barry L -- Bradley, Philip -- R01 GM049857/GM/NIGMS NIH HHS/ -- R01 GM115545/GM/NIGMS NIH HHS/ -- R01GM49857/GM/NIGMS NIH HHS/ -- R21 GM106117/GM/NIGMS NIH HHS/ -- R21GM106117/GM/NIGMS NIH HHS/ -- Howard Hughes Medical Institute/ -- England -- Nature. 2015 Dec 24;528(7583):585-8. doi: 10.1038/nature16191. Epub 2015 Dec 16.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Division of Basic Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue N., Seattle, Washington 98109, USA. ; Department of Biochemistry, University of Washington, Seattle, Washington 98195, USA. ; Institute for Protein Design, University of Washington, Seattle, Washington 98195, USA. ; Howard Hughes Medical Institute, University of Washington, Seattle, Washington 98195, USA. ; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue N., Seattle, Washington 98019, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/26675735" target="_blank"〉PubMed〈/a〉
    Keywords: *Amino Acid Motifs ; *Bioengineering ; *Computer Simulation ; Crystallography, X-Ray ; Databases, Protein ; Models, Molecular ; *Protein Structure, Secondary ; Proteins/*chemistry ; Reproducibility of Results
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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  • 3
    Publication Date: 2010-02-06
    Description: Conventional protein structure determination from nuclear magnetic resonance data relies heavily on side-chain proton-to-proton distances. The necessary side-chain resonance assignment, however, is labor intensive and prone to error. Here we show that structures can be accurately determined without nuclear magnetic resonance (NMR) information on the side chains for proteins up to 25 kilodaltons by incorporating backbone chemical shifts, residual dipolar couplings, and amide proton distances into the Rosetta protein structure modeling methodology. These data, which are too sparse for conventional methods, serve only to guide conformational search toward the lowest-energy conformations in the folding landscape; the details of the computed models are determined by the physical chemistry implicit in the Rosetta all-atom energy function. The new method is not hindered by the deuteration required to suppress nuclear relaxation processes for proteins greater than 15 kilodaltons and should enable routine NMR structure determination for larger proteins.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2909653/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2909653/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Raman, Srivatsan -- Lange, Oliver F -- Rossi, Paolo -- Tyka, Michael -- Wang, Xu -- Aramini, James -- Liu, Gaohua -- Ramelot, Theresa A -- Eletsky, Alexander -- Szyperski, Thomas -- Kennedy, Michael A -- Prestegard, James -- Montelione, Gaetano T -- Baker, David -- GM76222/GM/NIGMS NIH HHS/ -- P41 GM103390/GM/NIGMS NIH HHS/ -- R01 GM092802/GM/NIGMS NIH HHS/ -- R01 GM095693/GM/NIGMS NIH HHS/ -- RR005351/RR/NCRR NIH HHS/ -- U54 GM074958/GM/NIGMS NIH HHS/ -- U54 GM074958-05/GM/NIGMS NIH HHS/ -- Howard Hughes Medical Institute/ -- Wellcome Trust/United Kingdom -- New York, N.Y. -- Science. 2010 Feb 19;327(5968):1014-8. doi: 10.1126/science.1183649. Epub 2010 Feb 4.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/20133520" target="_blank"〉PubMed〈/a〉
    Keywords: Computer Simulation ; Models, Molecular ; Monte Carlo Method ; Nuclear Magnetic Resonance, Biomolecular/*methods ; *Protein Conformation ; Protein Folding ; Proteins/*chemistry ; Software ; Thermodynamics
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 4
    Publication Date: 2011-05-14
    Description: We describe a general computational method for designing proteins that bind a surface patch of interest on a target macromolecule. Favorable interactions between disembodied amino acid residues and the target surface are identified and used to anchor de novo designed interfaces. The method was used to design proteins that bind a conserved surface patch on the stem of the influenza hemagglutinin (HA) from the 1918 H1N1 pandemic virus. After affinity maturation, two of the designed proteins, HB36 and HB80, bind H1 and H5 HAs with low nanomolar affinity. Further, HB80 inhibits the HA fusogenic conformational changes induced at low pH. The crystal structure of HB36 in complex with 1918/H1 HA revealed that the actual binding interface is nearly identical to that in the computational design model. Such designed binding proteins may be useful for both diagnostics and therapeutics.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3164876/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3164876/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Fleishman, Sarel J -- Whitehead, Timothy A -- Ekiert, Damian C -- Dreyfus, Cyrille -- Corn, Jacob E -- Strauch, Eva-Maria -- Wilson, Ian A -- Baker, David -- AI057141/AI/NIAID NIH HHS/ -- AI058113/AI/NIAID NIH HHS/ -- GM080209/GM/NIGMS NIH HHS/ -- P01 AI058113/AI/NIAID NIH HHS/ -- P01 AI058113-07/AI/NIAID NIH HHS/ -- Y1-CO-1020/CO/NCI NIH HHS/ -- Y1-GM-1104/GM/NIGMS NIH HHS/ -- Howard Hughes Medical Institute/ -- New York, N.Y. -- Science. 2011 May 13;332(6031):816-21. doi: 10.1126/science.1202617.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/21566186" target="_blank"〉PubMed〈/a〉
    Keywords: Algorithms ; Amino Acid Sequence ; Binding Sites ; Computational Biology ; *Computer Simulation ; Hemagglutinin Glycoproteins, Influenza Virus/chemistry/*metabolism ; Hydrogen Bonding ; Hydrogen-Ion Concentration ; Hydrophobic and Hydrophilic Interactions ; *Models, Molecular ; Molecular Sequence Data ; Mutation ; Peptide Library ; Protein Binding ; Protein Conformation ; *Protein Engineering ; Protein Interaction Domains and Motifs ; Protein Structure, Secondary ; Proteins/*chemistry/genetics/*metabolism ; Software
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 5
    Publication Date: 2003-11-25
    Description: A major challenge of computational protein design is the creation of novel proteins with arbitrarily chosen three-dimensional structures. Here, we used a general computational strategy that iterates between sequence design and structure prediction to design a 93-residue alpha/beta protein called Top7 with a novel sequence and topology. Top7 was found experimentally to be folded and extremely stable, and the x-ray crystal structure of Top7 is similar (root mean square deviation equals 1.2 angstroms) to the design model. The ability to design a new protein fold makes possible the exploration of the large regions of the protein universe not yet observed in nature.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Kuhlman, Brian -- Dantas, Gautam -- Ireton, Gregory C -- Varani, Gabriele -- Stoddard, Barry L -- Baker, David -- New York, N.Y. -- Science. 2003 Nov 21;302(5649):1364-8.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/14631033" target="_blank"〉PubMed〈/a〉
    Keywords: Algorithms ; Amino Acid Sequence ; Circular Dichroism ; Computational Biology ; Computer Graphics ; Computer Simulation ; Crystallization ; Crystallography, X-Ray ; Databases, Protein ; Models, Molecular ; Molecular Sequence Data ; Monte Carlo Method ; Nuclear Magnetic Resonance, Biomolecular ; *Protein Conformation ; Protein Denaturation ; *Protein Engineering ; *Protein Folding ; Protein Structure, Secondary ; Proteins/*chemistry ; *Software ; Solubility ; Temperature ; Thermodynamics
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 6
    Publication Date: 2005-09-17
    Description: The prediction of protein structure from amino acid sequence is a grand challenge of computational molecular biology. By using a combination of improved low- and high-resolution conformational sampling methods, improved atomically detailed potential functions that capture the jigsaw puzzle-like packing of protein cores, and high-performance computing, high-resolution structure prediction (〈1.5 angstroms) can be achieved for small protein domains (〈85 residues). The primary bottleneck to consistent high-resolution prediction appears to be conformational sampling.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Bradley, Philip -- Misura, Kira M S -- Baker, David -- New York, N.Y. -- Science. 2005 Sep 16;309(5742):1868-71.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉University of Washington, Department of Biochemistry, and Howard Hughes Medical Institute, Box 357350, Seattle, WA 98195, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/16166519" target="_blank"〉PubMed〈/a〉
    Keywords: Amino Acid Sequence ; Chemistry, Physical ; *Computational Biology ; Computer Simulation ; Hydrogen Bonding ; Models, Molecular ; Monte Carlo Method ; Physicochemical Phenomena ; *Protein Conformation ; Protein Folding ; Protein Structure, Secondary ; Protein Structure, Tertiary ; Proteins/*chemistry ; Sequence Alignment ; Thermodynamics
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    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 7
    Publication Date: 2005-10-29
    Description: The prediction of the structures and interactions of biological macromolecules at the atomic level and the design of new structures and interactions are critical tests of our understanding of the interatomic interactions that underlie molecular biology. Equally important, the capability to accurately predict and design macromolecular structures and interactions would streamline the interpretation of genome sequence information and allow the creation of macromolecules with new and useful functions. This review summarizes recent progress in modeling that suggests that we are entering an era in which high-resolution prediction and design will make increasingly important contributions to biology and medicine.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Schueler-Furman, Ora -- Wang, Chu -- Bradley, Phil -- Misura, Kira -- Baker, David -- New York, N.Y. -- Science. 2005 Oct 28;310(5748):638-42.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/16254179" target="_blank"〉PubMed〈/a〉
    Keywords: Computer Simulation ; Computing Methodologies ; *Models, Molecular ; *Protein Conformation
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    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 8
    Publication Date: 2011-08-23
    Description: Proteins are inherently plastic molecules, whose function often critically depends on excursions between different molecular conformations (conformers). However, a rigorous understanding of the relation between a protein's structure, dynamics and function remains elusive. This is because many of the conformers on its energy landscape are only transiently formed and marginally populated (less than a few per cent of the total number of molecules), so that they cannot be individually characterized by most biophysical tools. Here we study a lysozyme mutant from phage T4 that binds hydrophobic molecules and populates an excited state transiently (about 1 ms) to about 3% at 25 degrees C (ref. 5). We show that such binding occurs only via the ground state, and present the atomic-level model of the 'invisible', excited state obtained using a combined strategy of relaxation-dispersion NMR (ref. 6) and CS-Rosetta model building that rationalizes this observation. The model was tested using structure-based design calculations identifying point mutants predicted to stabilize the excited state relative to the ground state. In this way a pair of mutations were introduced, inverting the relative populations of the ground and excited states and altering function. Our results suggest a mechanism for the evolution of a protein's function by changing the delicate balance between the states on its energy landscape. More generally, they show that our approach can generate and validate models of excited protein states.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3706084/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3706084/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Bouvignies, Guillaume -- Vallurupalli, Pramodh -- Hansen, D Flemming -- Correia, Bruno E -- Lange, Oliver -- Bah, Alaji -- Vernon, Robert M -- Dahlquist, Frederick W -- Baker, David -- Kay, Lewis E -- R01 GM092802/GM/NIGMS NIH HHS/ -- Canadian Institutes of Health Research/Canada -- Howard Hughes Medical Institute/ -- England -- Nature. 2011 Aug 21;477(7362):111-4. doi: 10.1038/nature10349.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Molecular Genetics, The University of Toronto, Toronto, Ontario M5S 1A8, Canada.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/21857680" target="_blank"〉PubMed〈/a〉
    Keywords: Bacteriophage T4/*enzymology/*genetics ; Evolution, Molecular ; Hydrophobic and Hydrophilic Interactions ; Ligands ; *Models, Molecular ; Muramidase/*chemistry/*genetics ; *Mutation ; Protein Binding ; Temperature
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  • 9
    Publication Date: 2011-05-03
    Description: Molecular replacement procedures, which search for placements of a starting model within the crystallographic unit cell that best account for the measured diffraction amplitudes, followed by automatic chain tracing methods, have allowed the rapid solution of large numbers of protein crystal structures. Despite extensive work, molecular replacement or the subsequent rebuilding usually fail with more divergent starting models based on remote homologues with less than 30% sequence identity. Here we show that this limitation can be substantially reduced by combining algorithms for protein structure modelling with those developed for crystallographic structure determination. An approach integrating Rosetta structure modelling with Autobuild chain tracing yielded high-resolution structures for 8 of 13 X-ray diffraction data sets that could not be solved in the laboratories of expert crystallographers and that remained unsolved after application of an extensive array of alternative approaches. We estimate that the new method should allow rapid structure determination without experimental phase information for over half the cases where current methods fail, given diffraction data sets of better than 3.2 A resolution, four or fewer copies in the asymmetric unit, and the availability of structures of homologous proteins with 〉20% sequence identity.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3365536/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3365536/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉DiMaio, Frank -- Terwilliger, Thomas C -- Read, Randy J -- Wlodawer, Alexander -- Oberdorfer, Gustav -- Wagner, Ulrike -- Valkov, Eugene -- Alon, Assaf -- Fass, Deborah -- Axelrod, Herbert L -- Das, Debanu -- Vorobiev, Sergey M -- Iwai, Hideo -- Pokkuluri, P Raj -- Baker, David -- 082961/Wellcome Trust/United Kingdom -- 5R01GM092802/GM/NIGMS NIH HHS/ -- GM074898/GM/NIGMS NIH HHS/ -- P01 GM063210/GM/NIGMS NIH HHS/ -- P41RR002250/RR/NCRR NIH HHS/ -- R01 GM092802/GM/NIGMS NIH HHS/ -- U54 GM074898/GM/NIGMS NIH HHS/ -- U54 GM074958/GM/NIGMS NIH HHS/ -- U54 GM094586/GM/NIGMS NIH HHS/ -- U54GM074958/GM/NIGMS NIH HHS/ -- Howard Hughes Medical Institute/ -- Intramural NIH HHS/ -- Wellcome Trust/United Kingdom -- England -- Nature. 2011 May 26;473(7348):540-3. doi: 10.1038/nature09964. Epub 2011 May 1.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉University of Washington, Department of Biochemistry and HHMI, Seattle, Washington 98195, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/21532589" target="_blank"〉PubMed〈/a〉
    Keywords: Computational Biology/*methods ; Crystallography, X-Ray ; Databases, Protein ; Electrons ; *Models, Molecular ; Proteins/*chemistry ; Sequence Alignment ; Sequence Homology, Amino Acid ; *Structural Homology, Protein
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    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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  • 10
    Publication Date: 2012-11-09
    Description: Unlike random heteropolymers, natural proteins fold into unique ordered structures. Understanding how these are encoded in amino-acid sequences is complicated by energetically unfavourable non-ideal features--for example kinked alpha-helices, bulged beta-strands, strained loops and buried polar groups--that arise in proteins from evolutionary selection for biological function or from neutral drift. Here we describe an approach to designing ideal protein structures stabilized by completely consistent local and non-local interactions. The approach is based on a set of rules relating secondary structure patterns to protein tertiary motifs, which make possible the design of funnel-shaped protein folding energy landscapes leading into the target folded state. Guided by these rules, we designed sequences predicted to fold into ideal protein structures consisting of alpha-helices, beta-strands and minimal loops. Designs for five different topologies were found to be monomeric and very stable and to adopt structures in solution nearly identical to the computational models. These results illuminate how the folding funnels of natural proteins arise and provide the foundation for engineering a new generation of functional proteins free from natural evolution.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3705962/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3705962/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Koga, Nobuyasu -- Tatsumi-Koga, Rie -- Liu, Gaohua -- Xiao, Rong -- Acton, Thomas B -- Montelione, Gaetano T -- Baker, David -- U54 GM094597/GM/NIGMS NIH HHS/ -- Howard Hughes Medical Institute/ -- England -- Nature. 2012 Nov 8;491(7423):222-7. doi: 10.1038/nature11600.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉University of Washington, Department of Biochemistry and Howard Hughes Medical Institute, Seattle, Washington 98195, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/23135467" target="_blank"〉PubMed〈/a〉
    Keywords: *Computer Simulation ; *Models, Molecular ; *Protein Folding ; *Protein Stability ; Protein Structure, Secondary ; Protein Structure, Tertiary ; Proteins/*chemistry ; Thermodynamics
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    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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