This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. The Resource for Biocomputing, Visualization and Informatics (RBVI) develops innovative methods and algorithms for computational and visualization-based data analysis, implements these as professional-quality, easy-to-use software tools, and applies the tools toward solving a wide range of problems relating to molecular sequence, structure, and function. UCSF Chimera (www.cgl.ucsf.edu/chimera) is the molecular modeling package under active development by the RBVI. Chimera is a tool for visualization and analysis of biomolecular structures and interactions. In addition to atomic coordinates, it can be used to explore other data types such as electron density maps, electrostatic potential maps, and sequence alignments, and it can be used to create high-quality images and movies for publication and presentation. For exploring broader biological contexts, RBVI also develops and distributes plugins to the open-source network visualization tool Cytoscape. Protein sequence or structure similarity networks, metabolic pathways, and networks of small molecule metabolites or drugs are a few examples of systems of interest. The plugins provide capabilities for manipulating and analyzing the networks and linking them to 3D visualization with Chimera. The Structure-Function Linkage Database (sfld.rbvi.ucsf.edu) connects evolutionarily related sequences and structures (superfamilies of enzymes) to their chemical reactions, and correlates conserved active site residues with specific partial reactions common to the members of a superfamily. It provides highly curated information on mechanistically diverse superfamilies, which catalyze many different overall reactions and have historically been subject to many annotation problems. This public resource can be used to guide functional annotation and protein engineering applications. The Sequence Analysis and Consulting Service (SACS, www.sacs.ucsf.edu) provides expertise in bioinformatics, molecular visualization and analysis, and network visualization and analysis. It also provides local access to up-to-date versions of sequence analysis software and sequence databases. As development continues, it is imperative that the RBVI team remains connected to the broader structural and molecular biology research and teaching community through outreach and training. These activities promote awareness of what the Resource has to offer, resulting in more effective use and driving further developments.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR001081-34
Application #
8363626
Study Section
Special Emphasis Panel (ZRG1-BST-D (40))
Project Start
2011-07-01
Project End
2012-06-30
Budget Start
2011-07-01
Budget End
2012-06-30
Support Year
34
Fiscal Year
2011
Total Cost
$109,362
Indirect Cost
Name
University of California San Francisco
Department
Pharmacology
Type
Schools of Pharmacy
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94143
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Chu, Shidong; Zhou, Guangyan; Gochin, Miriam (2017) Evaluation of ligand-based NMR screening methods to characterize small molecule binding to HIV-1 glycoprotein-41. Org Biomol Chem 15:5210-5219
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Nekouzadeh, Ali; Rudy, Yoram (2016) Conformational changes of an ion-channel during gating and emerging electrophysiologic properties: Application of a computational approach to cardiac Kv7.1. Prog Biophys Mol Biol 120:18-27
Forman, Stuart A; Miller, Keith W (2016) Mapping General Anesthetic Sites in Heteromeric ?-Aminobutyric Acid Type A Receptors Reveals a Potential For Targeting Receptor Subtypes. Anesth Analg 123:1263-1273
Sathyanarayana, Bangalore K; Li, Peng; Lin, Jian-Xin et al. (2016) Molecular Models of STAT5A Tetramers Complexed to DNA Predict Relative Genome-Wide Frequencies of the Spacing between the Two Dimer Binding Motifs of the Tetramer Binding Sites. PLoS One 11:e0160339

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