Rosetta is molecular modeling software that has been developed for the prediction and design of macromolecular structure. Rosetta has performed well in community wide assessments of protein structure prediction and docking, and it has been used to engineer proteins for a variety of applications including: scaffold design for vaccine development, biosensor design for live cell imaging, and protein interface design to create inhibitors of human pathogens. Rosetta is developed and maintained by research groups at over 20 universities, and over the 9 years since its first release, 9750 academic laboratories have obtained free licenses to use the software. This proposal is a competing renewal and is in response to a program announcement (PAR-11-028) for the continued development and maintenance of software. Activities from the previous funding periods have been instrumental in the productive growth of Rosetta, these include the creation of a C++ object-oriented version of Rosetta (from Fortran) that allows scientists to more easily combine alternate sampling protocols and energy functions, the development of an automated testing system for checking the integrity of the code base, deployment of web servers for more standard Rosetta simulations, and user support through an online forum system. With this proposal our goal is to further increase the usefulness of Rosetta to expert and non-expert users as well as promote the rapid development of new algorithms by maintaining a robust code base and a rigorous set of technical and scientific benchmarks.
Our specific aims i nclude the further development and extension of scripting tools for generating custom protocols, increasing the speed of Rosetta simulations through parallel computing, deployment of new automated tests to validate code accuracy and enforce coding standards, and user support through a unified web server for Rosetta applications.

Public Health Relevance

The function of a protein, RNA or DNA molecule is largely determined by its 3-dimensional structure. We aim to develop a state-of-the-art computer program for predicting and designing the structures of biological macromolecules. The program will be freely available to academic laboratories and its predictions will help investigators understand and fight human diseases such as cancer and AIDS.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM073151-09
Application #
8729395
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Friedman, Fred K
Project Start
2005-03-01
Project End
2017-04-30
Budget Start
2014-05-01
Budget End
2015-04-30
Support Year
9
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of North Carolina Chapel Hill
Department
Biochemistry
Type
Schools of Medicine
DUNS #
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599
Fu, Darwin Yu; Meiler, Jens (2018) RosettaLigandEnsemble: A Small-Molecule Ensemble-Driven Docking Approach. ACS Omega 3:3655-3664
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
Weitzner, Brian D; Jeliazkov, Jeliazko R; Lyskov, Sergey et al. (2017) Modeling and docking of antibody structures with Rosetta. Nat Protoc 12:401-416
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

Showing the most recent 10 out of 34 publications