The UCSF Resource for Biocomputing, Visualization, and Informatics (RBVI) will continue its long history of developing software and advanced web-based resources for the integrated visualization and analysis of molecular structure at scales ranging from atomic to supramolecular. We will create tools for handling and integrating diverse types of biomolecular data, including atomic-resolution coordinates, density maps, sequences, annotations, and networks. Our primary efforts are in the visualization and analysis of structures of molecules and molecular assemblies, enzyme sequence-structure-function relationships, and network representations of protein similarity, binding interactions, and biological pathways. We will provide technologies to enable identifying the molecular bases of disease and phenotypic variation, annotating proteins of unknown function, identifying targets for drug development, designing drugs, and engineering proteins with new functions. Through our Driving Biomedical Projects, we will enable scientists to understand, analyze, and illustrate to others the important principles of molecular recognition and interactions. All of the tools that we develop will be made available in binary and source code form via our web site. Researchers will be trained in the use of these tools and will be able to collaborate with RBVI staff. Dissemination of our technological developments and collaborative research results will be accomplished via scientific publications, lectures, software distribution, video animations, and though our web site: www.rbvi.ucsf.edu/.
The research tools we develop will directly address the challenges associated with applying computing and information technology to biomedicine, building out from today's fundemental knowledge in structural biology and computational biology, to provide insight into cellular function and tools for translational medicine.
|Gao, Yong; McKay, Paul F; Mann, Jamie F S (2018) Advances in HIV-1 Vaccine Development. Viruses 10:|
|Orbán-Németh, Zsuzsanna; Beveridge, Rebecca; Hollenstein, David M et al. (2018) Structural prediction of protein models using distance restraints derived from cross-linking mass spectrometry data. Nat Protoc 13:478-494|
|Maruyama, Yutaka; Mitsutake, Ayori (2018) Analysis of Structural Stability of Chignolin. J Phys Chem B 122:3801-3814|
|Kontur, Wayne S; Bingman, Craig A; Olmsted, Charles N et al. (2018) Novosphingobium aromaticivorans uses a Nu-class glutathione S-transferase as a glutathione lyase in breaking the ?-aryl ether bond of lignin. J Biol Chem 293:4955-4968|
|Tokmina-Roszyk, Michal; Fields, Gregg B (2018) Dissecting MMP P10' and P11' subsite sequence preferences, utilizing a positional scanning, combinatorial triple-helical peptide library. J Biol Chem 293:16661-16676|
|Rosenberg, Masha M; Redfield, Alfred G; Roberts, Mary F et al. (2018) Dynamic Characteristics of Guanosine-5'-monophosphate Reductase Complexes Revealed by High-Resolution 31P Field-Cycling NMR Relaxometry. Biochemistry 57:3146-3154|
|Ren, Jinhong; Mistry, Tina L; Su, Pin-Chih et al. (2018) Determination of absolute configuration and binding efficacy of benzimidazole-based FabI inhibitors through the support of electronic circular dichroism and MM-GBSA techniques. Bioorg Med Chem Lett 28:2074-2079|
|Calhoun, Sara; Korczynska, Magdalena; Wichelecki, Daniel J et al. (2018) Prediction of enzymatic pathways by integrative pathway mapping. Elife 7:|
|Goddard, Thomas D; Brilliant, Alan A; Skillman, Thomas L et al. (2018) Molecular Visualization on the Holodeck. J Mol Biol 430:3982-3996|
|Skiba, Meredith A; Sikkema, Andrew P; Moss, Nathan A et al. (2018) Biosynthesis of t-Butyl in Apratoxin A: Functional Analysis and Architecture of a PKS Loading Module. ACS Chem Biol 13:1640-1650|
Showing the most recent 10 out of 272 publications