The aims of this proposal are to (1) improve comparative modeling so that atomic level accuracy models can be routinely generated starting from structures of homologous proteins, (2) transform the process of NMR structure determination by making possible the determination of atomic level accuracy models without side chain assignments, and (3) enable the determination of high resolution structures from 3-4.5 E resolution density maps. These methodological advances will be extended to enable structure determination of membrane proteins and large homo-oligomers based on datasets not sufficient to allow structure determination using conventional methods.

Public Health Relevance

The proposed work could transform the process of macromolecular structure determination, making it possible to determine accurate structures rapidly with less cost and effort, and to determine atomic level structures for proteins and complexes for which this is not currently possible. Such structures could provide insight into fundamental biological processes and the basis for disease causing mutations, and allow the structure based design of new therapeutics.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM092802-04
Application #
8450156
Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Preusch, Peter C
Project Start
2010-04-01
Project End
2014-03-31
Budget Start
2013-04-01
Budget End
2014-03-31
Support Year
4
Fiscal Year
2013
Total Cost
$262,869
Indirect Cost
$89,124
Name
University of Washington
Department
Biochemistry
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
Ovchinnikov, Sergey; Park, Hahnbeom; Kim, David E et al. (2018) Protein structure prediction using Rosetta in CASP12. Proteins 86 Suppl 1:113-121
Park, Hahnbeom; Ovchinnikov, Sergey; Kim, David E et al. (2018) Protein homology model refinement by large-scale energy optimization. Proc Natl Acad Sci U S A 115:3054-3059
Alford, Rebecca F; Leaver-Fay, Andrew; Jeliazkov, Jeliazko R et al. (2017) The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design. J Chem Theory Comput 13:3031-3048
Anishchenko, Ivan; Ovchinnikov, Sergey; Kamisetty, Hetunandan et al. (2017) Origins of coevolution between residues distant in protein 3D structures. Proc Natl Acad Sci U S A 114:9122-9127
Ovchinnikov, Sergey; Park, Hahnbeom; Varghese, Neha et al. (2017) Protein structure determination using metagenome sequence data. Science 355:294-298
Park, Hahnbeom; DiMaio, Frank; Baker, David (2016) CASP11 refinement experiments with ROSETTA. Proteins 84 Suppl 1:314-22
Ovchinnikov, Sergey; Kim, David E; Wang, Ray Yu-Ruei et al. (2016) Improved de novo structure prediction in CASP11 by incorporating coevolution information into Rosetta. Proteins 84 Suppl 1:67-75
Safarian, Schara; Rajendran, Chitra; Müller, Hannelore et al. (2016) Structure of a bd oxidase indicates similar mechanisms for membrane-integrated oxygen reductases. Science 352:583-6
Ovchinnikov, Sergey; Park, Hahnbeom; Kim, David E et al. (2016) Structure prediction using sparse simulated NOE restraints with Rosetta in CASP11. Proteins 84 Suppl 1:181-8
Park, Hahnbeom; Bradley, Philip; Greisen Jr, Per et al. (2016) Simultaneous Optimization of Biomolecular Energy Functions on Features from Small Molecules and Macromolecules. J Chem Theory Comput 12:6201-6212

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