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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: 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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  • 3
    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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  • 4
    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
    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: 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
    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: 2015-12-18
    Description: A central question in protein evolution is the extent to which naturally occurring proteins sample the space of folded structures accessible to the polypeptide chain. Repeat proteins composed of multiple tandem copies of a modular structure unit are widespread in nature and have critical roles in molecular recognition, signalling, and other essential biological processes. Naturally occurring repeat proteins have been re-engineered for molecular recognition and modular scaffolding applications. Here we use computational protein design to investigate the space of folded structures that can be generated by tandem repeating a simple helix-loop-helix-loop structural motif. Eighty-three designs with sequences unrelated to known repeat proteins were experimentally characterized. Of these, 53 are monomeric and stable at 95 degrees C, and 43 have solution X-ray scattering spectra consistent with the design models. Crystal structures of 15 designs spanning a broad range of curvatures are in close agreement with the design models with root mean square deviations ranging from 0.7 to 2.5 A. Our results show that existing repeat proteins occupy only a small fraction of the possible repeat protein sequence and structure space and that it is possible to design novel repeat proteins with precisely specified geometries, opening up a wide array of new possibilities for biomolecular engineering.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Brunette, T J -- Parmeggiani, Fabio -- Huang, Po-Ssu -- Bhabha, Gira -- Ekiert, Damian C -- Tsutakawa, Susan E -- Hura, Greg L -- Tainer, John A -- Baker, David -- GM105404/GM/NIGMS NIH HHS/ -- K99GM112982/GM/NIGMS NIH HHS/ -- R01 GM105404/GM/NIGMS NIH HHS/ -- Howard Hughes Medical Institute/ -- England -- Nature. 2015 Dec 24;528(7583):580-4. doi: 10.1038/nature16162. Epub 2015 Dec 16.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Biochemistry, University of Washington, Seattle, Washington 98195, USA. ; Institute for Protein Design, University of Washington, Seattle, Washington 98195, USA. ; Department of Cellular and Molecular Pharmacology, UCSF, San Francisco, California 94158, USA. ; Department of Microbiology and Immunology, UCSF, San Francisco, California 94158, USA. ; Molecular Biophysics &Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA. ; Department of Chemistry and Biochemistry, University of California, Santa Cruz, California 95064, USA. ; Department of Molecular and Cellular Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas 77030, USA. ; Howard Hughes Medical Institute, University of Washington, Seattle, Washington 98195, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/26675729" target="_blank"〉PubMed〈/a〉
    Keywords: *Amino Acid Motifs ; Amino Acid Sequence ; *Bioengineering ; *Computer Simulation ; Crystallography, X-Ray ; Models, Molecular ; *Protein Conformation ; Protein Folding ; Protein Stability ; Proteins/*chemistry ; Temperature
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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