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  • 1
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    NMR structure determination for larger proteins using backbone-only data (2010)
    American Association for the Advancement of Science (AAAS)
    Details
    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
    Published by American Association for the Advancement of Science (AAAS)
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  • 2
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    Computational design of proteins targeting the conserved stem region of influenza hemagglutinin (2011)
    American Association for the Advancement of Science (AAAS)
    Details
    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
    Published by American Association for the Advancement of Science (AAAS)
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  • 3
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    Improved molecular replacement by density- and energy-guided protein structure optimization (2011)
    Nature Publishing Group (NPG)
    Details
    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
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Published by Nature Publishing Group (NPG)
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  • 4
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    Principles for designing ideal protein structures (2012)
    Nature Publishing Group (NPG)
    Details
    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
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Published by Nature Publishing Group (NPG)
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  • 5
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    Computational design of ligand-binding proteins with high affinity and selectivity (2013)
    Nature Publishing Group (NPG)
    Details
    Publication Date: 2013-09-06
    Description: The ability to design proteins with high affinity and selectivity for any given small molecule is a rigorous test of our understanding of the physiochemical principles that govern molecular recognition. Attempts to rationally design ligand-binding proteins have met with little success, however, and the computational design of protein-small-molecule interfaces remains an unsolved problem. Current approaches for designing ligand-binding proteins for medical and biotechnological uses rely on raising antibodies against a target antigen in immunized animals and/or performing laboratory-directed evolution of proteins with an existing low affinity for the desired ligand, neither of which allows complete control over the interactions involved in binding. Here we describe a general computational method for designing pre-organized and shape complementary small-molecule-binding sites, and use it to generate protein binders to the steroid digoxigenin (DIG). Of seventeen experimentally characterized designs, two bind DIG; the model of the higher affinity binder has the most energetically favourable and pre-organized interface in the design set. A comprehensive binding-fitness landscape of this design, generated by library selections and deep sequencing, was used to optimize its binding affinity to a picomolar level, and X-ray co-crystal structures of two variants show atomic-level agreement with the corresponding computational models. The optimized binder is selective for DIG over the related steroids digitoxigenin, progesterone and beta-oestradiol, and this steroid binding preference can be reprogrammed by manipulation of explicitly designed hydrogen-bonding interactions. The computational design method presented here should enable the development of a new generation of biosensors, therapeutics and diagnostics.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3898436/" 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/PMC3898436/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Tinberg, Christine E -- Khare, Sagar D -- Dou, Jiayi -- Doyle, Lindsey -- Nelson, Jorgen W -- Schena, Alberto -- Jankowski, Wojciech -- Kalodimos, Charalampos G -- Johnsson, Kai -- Stoddard, Barry L -- Baker, David -- P41 GM103533/GM/NIGMS NIH HHS/ -- R01 GM049857/GM/NIGMS NIH HHS/ -- T32 HG000035/HG/NHGRI NIH HHS/ -- T32 HG00035/HG/NHGRI NIH HHS/ -- England -- Nature. 2013 Sep 12;501(7466):212-6. doi: 10.1038/nature12443. Epub 2013 Sep 4.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Biochemistry, University of Washington, Seattle, Washington 98195, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/24005320" target="_blank"〉PubMed〈/a〉
    Keywords: Binding Sites ; Biotechnology ; *Computer Simulation ; Crystallography, X-Ray ; Digoxigenin/chemistry/*metabolism ; *Drug Design ; Estradiol/chemistry/metabolism ; Ligands ; Models, Molecular ; Progesterone/chemistry/metabolism ; Protein Binding ; Proteins/*chemistry/*metabolism ; Reproducibility of Results ; Substrate Specificity
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Published by Nature Publishing Group (NPG)
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