? The aim of this proposal is to modernize the Rosetta software package for protein structure modeling in order to facilitate its continued development in parallel in multiple research groups and to promote the widespread use of the software in the scientific community. Achieving this aim would have a very positive impact on computational structural biology quite broadly because in many critical areas, the Rosetta methodology appears to be at least as good, if not better, than other approaches. By facilitating further development and application of the software by a large group of researchers throughout the scientific community, the power and usefulness of the software should increase enormously. Rosetta currently contains modules for de novo protein structure prediction, protein design, protein-protein docking, proteinprotein and proteim DNA interface design, protein-protein and protein-DNA interaction specificity prediction, loop modeling, and high-resolution protein structure refinement. These diverse applications provide stringent tests for the underlying potential functions and optimization methods that are shared by all modules, stimulating continued improvements in both areas. When such improved core elements are incorporated into the integrated Rosetta structure-modeling platform, all the individual applications reap the benefits. Integration of the different modules in a single package has made substantial advances possible by allowing multiple modules to be combined to address complex modeling problem. For example, the combined use of the structure prediction, protein design, and model refinement modules allowed the design of a novel protein fold with atomic level accuracy. To facilitate further integration of the different modules to attack problems such as flexible backbone protein-protein docking, and to facilitate the continued development of new features and functionality, the Rosetta package will be ported to C++ and modernized to an object-oriented design. To promote widespread use of the software, a comprehensive Rosetta web server will be developed, the modernized source code will be made freely available to the scientific community with extensive documentation, and researchers throughout the community will be encouraged to join the growing Rosetta development team. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
7R01GM073151-03
Application #
7172634
Study Section
Special Emphasis Panel (ZRG1-BST-D (51))
Program Officer
Li, Jerry
Project Start
2005-03-01
Project End
2009-08-31
Budget Start
2007-03-01
Budget End
2009-08-31
Support Year
3
Fiscal Year
2007
Total Cost
$641,182
Indirect Cost
Name
University of North Carolina Chapel Hill
Department
Biochemistry
Type
Schools of Medicine
DUNS #
608195277
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599
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Tessmer, Maxx H; Anderson, David M; Pickrum, Adam M et al. (2018) Identification of a ubiquitin-binding interface using Rosetta and DEER. Proc Natl Acad Sci U S A 115:525-530
Kratochvil, Isabel; Hofmann, Tommy; Rother, Sandra et al. (2018) Mono(2-ethylhexyl) phthalate (MEHP) and mono(2-ethyl-5-oxohexyl) phthalate (MEOHP) but not di(2-ethylhexyl) phthalate (DEHP) bind productively to the peroxisome proliferator-activated receptor ?. Rapid Commun Mass Spectrom :
Leffler, Abba E; Kuryatov, Alexander; Zebroski, Henry A et al. (2017) Discovery of peptide ligands through docking and virtual screening at nicotinic acetylcholine receptor homology models. Proc Natl Acad Sci U S A 114:E8100-E8109
Li, Bian; Mendenhall, Jeffrey; Nguyen, Elizabeth Dong et al. (2017) Improving prediction of helix-helix packing in membrane proteins using predicted contact numbers as restraints. Proteins 85:1212-1221
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
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Weitzner, Brian D; Gray, Jeffrey J (2017) Accurate Structure Prediction of CDR H3 Loops Enabled by a Novel Structure-Based C-Terminal Constraint. J Immunol 198:505-515
Alford, Rebecca F; Leaver-Fay, Andrew; Gonzales, Lynda et al. (2017) A cyber-linked undergraduate research experience in computational biomolecular structure prediction and design. PLoS Comput Biol 13:e1005837

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