A major current focus of modern structural biology is the determination of the structures of macromolecular assemblies and machines. Such systems are often not amenable to high-resolution x-ray crystallographic techniques. This proposal aims to develop powerful new methods which integrate NMR data, information from homologous structures, cryo electron microscopy data, low resolution x-ray crystallographic data, evolutionary covariance data, and other sources of information to generate models with atomic level accuracy for macromolecular assemblies and machines. With collaborators, the new methodology will be used to solve cutting-edge structural biology problems which cannot be solved by currently available methods. The new methodology will be incorporated into the freely available Rosetta software suite for use throughout the scientific community.

Public Health Relevance

Proteins are the workhorses of living things. The structures of proteins are critical to carrying out their functions. This research will contribute to determining the structures of protein assemblies critical to life and human disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
2R01GM092802-05
Application #
8694374
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Preusch, Peter
Project Start
2010-04-01
Project End
2018-05-31
Budget Start
2014-07-01
Budget End
2015-05-31
Support Year
5
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of Washington
Department
Biochemistry
Type
Schools of Medicine
DUNS #
City
Seattle
State
WA
Country
United States
Zip Code
98195
Nordenfelt, Pontus; Moore, Travis I; Mehta, Shalin B et al. (2017) Direction of actin flow dictates integrin LFA-1 orientation during leukocyte migration. Nat Commun 8:2047
Ovchinnikov, Sergey; Park, Hahnbeom; Varghese, Neha et al. (2017) Protein structure determination using metagenome sequence data. Science 355:294-298
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
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
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
DaRosa, Paul A; Ovchinnikov, Sergey; Xu, Wenqing et al. (2016) Structural insights into SAM domain-mediated tankyrase oligomerization. Protein Sci 25:1744-52
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
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
Park, Hahnbeom; DiMaio, Frank; Baker, David (2015) The origin of consistent protein structure refinement from structural averaging. Structure 23:1123-8

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