The research program centers on the development and use of computational methods to make quantitative predictions on the structure, energetics, and reactivity of proteins. Progress in this field is essential for the deeper understanding of biochemical structure and function, and for the improvement of predictive skills of importance, for example, in the design of therapeutic drugs. The theoretical approach features computer simulations at the atomic level with explicit inclusion of the solvent. The principal techniques are Monte Carlo (MC) statistical mechanics and molecular dynamics (MD) with emphasis on computing changes in free energy for transformations in solution. The proposed research includes the development of force field and modeling software with applications concerning protein-ligand binding inhibitor design, protein stability, and pathways of protein denaturation. Effort will be directed specifically at (1) completion of the all-atom OPLS force field, followed by pursuit of the next generation of force field incorporating explicit polarization, (2) refinement of the MCPRO program for MC simulations of proteins as an alternative to MD, especially for free energy calculations, (3) extensive studies of protein-ligand complexes, e.g., for thrombin and Src homology domains, aimed both at in- depth understanding of variations in binding affinities and at participating in the design of enzyme inhibitors with therapeutic potential for coronary diseases, immune system regulation, and hyperproliferative disorders including cancer and allergies, (4) investigation of factors controlling protein stability such as the propensities for the different amino acids to occur on central or edge strands of beta sheets, (5) gaining insights into protein folding/ unfolding through further MD simulations of protein denaturation including for barnase at different temperatures and in the presence or absence of urea, and (6) elucidation of the origin of the effects of 2,2,2- trifluoroethanol (TFE) on helicity.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
2R01GM032136-13
Application #
2176458
Study Section
Molecular and Cellular Biophysics Study Section (BBCA)
Project Start
1990-07-01
Project End
1999-06-30
Budget Start
1995-07-01
Budget End
1996-06-30
Support Year
13
Fiscal Year
1995
Total Cost
Indirect Cost
Name
Yale University
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
082359691
City
New Haven
State
CT
Country
United States
Zip Code
06520
Trivedi-Parmar, Vinay; Jorgensen, William L (2018) Advances and Insights for Small Molecule Inhibition of Macrophage Migration Inhibitory Factor. J Med Chem 61:8104-8119
Trivedi-Parmar, Vinay; Robertson, Michael J; Cisneros, José A et al. (2018) Optimization of Pyrazoles as Phenol Surrogates to Yield Potent Inhibitors of Macrophage Migration Inhibitory Factor. ChemMedChem 13:1092-1097
Cabeza de Vaca, Israel; Qian, Yue; Vilseck, Jonah Z et al. (2018) Enhanced Monte Carlo Methods for Modeling Proteins Including Computation of Absolute Free Energies of Binding. J Chem Theory Comput 14:3279-3288
Dodda, Leela S; Tirado-Rives, Julian; Jorgensen, William L (2018) Unbinding Dynamics of Non-Nucleoside Inhibitors from HIV-1 Reverse Transcriptase. J Phys Chem B :
Dawson, Thomas K; Dziedzic, Pawel; Robertson, Michael J et al. (2017) Adding a Hydrogen Bond May Not Help: Naphthyridinone vs Quinoline Inhibitors of Macrophage Migration Inhibitory Factor. ACS Med Chem Lett 8:1287-1291
Chan, Albert H; Lee, Won-Gil; Spasov, Krasimir A et al. (2017) Covalent inhibitors for eradication of drug-resistant HIV-1 reverse transcriptase: From design to protein crystallography. Proc Natl Acad Sci U S A 114:9725-9730
Dodda, Leela S; Vilseck, Jonah Z; Tirado-Rives, Julian et al. (2017) 1.14*CM1A-LBCC: Localized Bond-Charge Corrected CM1A Charges for Condensed-Phase Simulations. J Phys Chem B 121:3864-3870
Robertson, Michael J; Tirado-Rives, Julian; Jorgensen, William L (2017) Improved Treatment of Nucleosides and Nucleotides in the OPLS-AA Force Field. Chem Phys Lett 683:276-280
Yan, Xin Cindy; Robertson, Michael J; Tirado-Rives, Julian et al. (2017) Improved Description of Sulfur Charge Anisotropy in OPLS Force Fields: Model Development and Parameterization. J Phys Chem B 121:6626-6636
Dodda, Leela S; Cabeza de Vaca, Israel; Tirado-Rives, Julian et al. (2017) LigParGen web server: an automatic OPLS-AA parameter generator for organic ligands. Nucleic Acids Res 45:W331-W336

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