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Computational and Structure-Based Methods for the Prediction of Resistance-Associated Mutations

November 13, 2019, 1:00 pm - 2:00 pm
Location Richardson Hall - 104
Posted InCollege of Science and Mathematics

Dr. Kathleen Frey, Fairleigh Dickinson University School of Pharmacy & Health Sciences; Department of Pharmaceutical Sciences, presents this seminar.

Event will be preceded by pizza and socializing, and followed by a career discussion.

Abstract

Drug resistance is a major limitation of therapeutic agents used for the treatment of infectious diseases and cancer. For enzyme targets, mutations in drug binding sites often lead to amino acid changes that disrupt key drug-target interactions. In the clinical setting, these resistance-associated mutations (RAMs) are responsible for treatment failure. In order to aid drug design efforts, it would be efficient and cost effective to develop computational and structure-based methods to pre-evaluate resistance mutations for enzyme drug targets during preclinical design. Our main research objective is to use computational and structure-based methods to pre-evaluate RAMs for enzyme drug targets. As proof of concept, we evaluated 2 enzyme targets for this study: HIV reverse transcriptase (RT), an antiretroviral target, and Glutathione S-transferase Pi (GSTP), an anticancer target. Our computational and structure-based methods include molecular docking, residue scanning, comparative structure analysis, and molecular dynamics (MD) simulations. Computational predictions were further validated with experimental enzyme inhibition assays. Major results indicate that this approach can predict and elucidate the effects of clinically relevant RAMs. We believe that this approach may be useful in predicting RAMs for inhibitors in development.