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. Our long term goal is to address the """"""""docking problem,"""""""" that of predicting the structures and ligand identities of protein-ligand complexes. Methods to do so would have wide application in structure-function studies.
The specific aims are: 1. To develop algorithms that dock ligands in hierarchies of increasing geometrical and chemical complexity. Although the configuration space for ligand-protein complexes is enormous, it is also highly redundant and constrained by the excluded volume of the complex. Docking molecules as ensembles of states allow for methods that take advantage of these features. By representing molecules in hierarchies of increasing complexity, it may be possible to exclude most unfavorable conformations early in the calculation. Such a hierarchical algorithm should be applicable to related chemistries in the same way as to related conformations. These methods would explore many more states and chemistries than can now be considered in docking calculations. Improvements to solvation energy models will also be investigated. 2. To test the new algorithms in a well-behaved experimental system. The new algorithms will be tested for their ability to predict new ligands and geometries for two model systems: AmpC beta-lactamase and a cavity site in lysozyme. Both proteins are easy to work with and provide well defined sites for docking studies. At the simplest level, the experimental tests will evaluate """"""""hit-rates"""""""" for the algorithms and their accuracy through structure determination. More fundamentally, this will alllow for investigation of the thermodynamic driving forces in complex formation. Extensive prelimary results suggest that the new algorithms are feasible. See the following articles for instance: a. Flexible Ligand Docking Using Conformational Ensembles b. Docking Molecules by Families to Increase the Diversity of Hits in Database Screens c. Protein-Protein Docking with Multiple Ligand Residue Conformations and Multiple Residue Identities The model system seems to be well suited to testing the new algorithms. See the following articles for instance: a. Mapping the Active Site of AmpC beta-Lactamase for Hot Spots b. Structure-based Discovery of a Novel, Non-Covalent Inhibitor of AmpC beta-Lactamase c. A Model Binding Site for Testing Scoring Functions in Molecular Docking Interactive computer graphics available through the RBVI are key to visualizing and evaluating how well docking calculations have performed, and to the structure-based discovery of new ligands. They are also very useful for crystallographic modeling and structure determination, which is part of the experimental testing aspect of this project.

National Institute of Health (NIH)
National Center for Research Resources (NCRR)
Biotechnology Resource Grants (P41)
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Special Emphasis Panel (ZRG1-BST-D (40))
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University of California San Francisco
Schools of Pharmacy
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Kozak, John J; Gray, Harry B; Garza-López, Roberto A (2018) Relaxation of structural constraints during Amicyanin unfolding. J Inorg Biochem 179:135-145
Alamo, Lorenzo; Pinto, Antonio; Sulbarán, Guidenn et al. (2018) Lessons from a tarantula: new insights into myosin interacting-heads motif evolution and its implications on disease. Biophys Rev 10:1465-1477
Viswanath, Shruthi; Chemmama, Ilan E; Cimermancic, Peter et al. (2017) Assessing Exhaustiveness of Stochastic Sampling for Integrative Modeling of Macromolecular Structures. Biophys J 113:2344-2353
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
Portioli, Corinne; Bovi, Michele; Benati, Donatella et al. (2017) Novel functionalization strategies of polymeric nanoparticles as carriers for brain medications. J Biomed Mater Res A 105:847-858
Alamo, Lorenzo; Koubassova, Natalia; Pinto, Antonio et al. (2017) Lessons from a tarantula: new insights into muscle thick filament and myosin interacting-heads motif structure and function. Biophys Rev 9:461-480
Nguyen, Hai Dang; Yadav, Tribhuwan; Giri, Sumanprava et al. (2017) Functions of Replication Protein A as a Sensor of R Loops and a Regulator of RNaseH1. Mol Cell 65:832-847.e4
Sofiyev, Vladimir; Kaur, Hardeep; Snyder, Beth A et al. (2017) Enhanced potency of bivalent small molecule gp41 inhibitors. Bioorg Med Chem 25:408-420
Sato, Daisuke; Shannon, Thomas R; Bers, Donald M (2016) Sarcoplasmic Reticulum Structure and Functional Properties that Promote Long-Lasting Calcium Sparks. Biophys J 110:382-390
Towse, Clare-Louise; Rysavy, Steven J; Vulovic, Ivan M et al. (2016) New Dynamic Rotamer Libraries: Data-Driven Analysis of Side-Chain Conformational Propensities. Structure 24:187-199

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