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  • 1
    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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  • 2
    Publication Date: 2011-11-07
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
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  • 3
    Publication Date: 2011-11-23
    Description: Foldit is a multiplayer online game in which players collaborate and compete to create accurate protein structure models. For specific hard problems, Foldit player solutions can in some cases outperform state-of-the-art computational methods. However, very little is known about how collaborative gameplay produces these results and whether Foldit player strategies can be formalized and structured so that they can be used by computers. To determine whether high performing player strategies could be collectively codified, we augmented the Foldit gameplay mechanics with tools for players to encode their folding strategies as “recipes” and to share their recipes with other players, who are able to further modify and redistribute them. Here we describe the rapid social evolution of player-developed folding algorithms that took place in the year following the introduction of these tools. Players developed over 5,400 different recipes, both by creating new algorithms and by modifying and recombining successful recipes developed by other players. The most successful recipes rapidly spread through the Foldit player population, and two of the recipes became particularly dominant. Examination of the algorithms encoded in these two recipes revealed a striking similarity to an unpublished algorithm developed by scientists over the same period. Benchmark calculations show that the new algorithm independently discovered by scientists and by Foldit players outperforms previously published methods. Thus, online scientific game frameworks have the potential not only to solve hard scientific problems, but also to discover and formalize effective new strategies and algorithms.
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
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