The broad objective of this proposal is to establish a computational platform to predict and understand protein functions at multi-scales, from molecule to cell, through integrating data from structural genomics, functional genomics and chemical genomics, and using tools derived from bioinformatics, chemical informatics and biophysics. There is a serious need to meet this objective in an era of proteomics where proteins are easily isolated, yet not so easily functionally classified with any degree of confidence. As the first step we propose here to: (1) design and implement scalable, accurate, reliable and robust algorithms and associated software for predicting, comparing, searching, and classifying protein functional sites and proteinligand interactions;(2) design and implement an ontology-driven protein functional site and protein-ligand interaction database that integrates comprehensive structure, function, and mutation information and supports quantitative modeling of protein structure and functions at the genome scale;(3) Establish first an intuitive graphical user interfaces (GUI) for scientists to visualize, analyze and mine functional site information for comparative proteomics and second establish an application programming interface (API) for programmers to develop new algorithms and applications using the foundation proposed here. The results of this effort will be disseminated through the Protein Data Bank which is used by over 10,000 scientists every day.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM078596-03
Application #
7642315
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Remington, Karin A
Project Start
2007-07-01
Project End
2011-06-30
Budget Start
2009-07-01
Budget End
2010-06-30
Support Year
3
Fiscal Year
2009
Total Cost
$523,859
Indirect Cost
Name
University of California San Diego
Department
Type
Schools of Pharmacy
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
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Wang, Jian; Anania, Veronica G; Knott, Jeff et al. (2014) A turn-key approach for large-scale identification of complex posttranslational modifications. J Proteome Res 13:1190-9
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Wang, Jian; Bourne, Philip E; Bandeira, Nuno (2011) Peptide identification by database search of mixture tandem mass spectra. Mol Cell Proteomics 10:M111.010017
Xie, Lei; Xie, Li; Bourne, Philip E (2011) Structure-based systems biology for analyzing off-target binding. Curr Opin Struct Biol 21:189-99
Kinnings, Sarah L; Liu, Nina; Tonge, Peter J et al. (2011) A machine learning-based method to improve docking scoring functions and its application to drug repurposing. J Chem Inf Model 51:408-19
Gramada, Apostol; Bourne, Philip E (2011) Coarse-graining the electrostatic potential via distributed multipole expansions. Comput Phys Commun 182:1455-1462
Kinnings, Sarah L; Liu, Nina; Tonge, Peter J et al. (2011) Correction to ""Machine learning-based method to improve docking scoring functions and its application to drug repurposing"". J Chem Inf Model 51:1195-7
Xie, Li; Evangelidis, Thomas; Xie, Lei et al. (2011) Drug discovery using chemical systems biology: weak inhibition of multiple kinases may contribute to the anti-cancer effect of nelfinavir. PLoS Comput Biol 7:e1002037

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