B.A. Harvard College (2012)
MD/PhD Stony Brook University (2020)
Robert Rizzo, PhD
Molecular & Cellular Pharmacology
In drug discovery, one method to improve the potency of an inhibitor is to combine different substructures of known ligands that bind to a target. In the realm of computational drug discovery, this same technique can be implemented by using a genetic algorithm (GA) to “swap” substructures of inhibitors. Genetic algorithms are a powerful tool because they can improve the quality of inhibitors generated by de novo design or can generate unique ligands after a virtual screen. Although many genetic algorithms exist, incorporation of the 3D structure from docked ligands is not commonplace. The goal of this research project is to generate a genetic algorithm for DOCK which uses the binding interactions and position of ligands in order to determine substructures that have a desirable interaction with the target to generate a unique compound.
Singleton C, Humbly M, Yi H, Rizzo R, Jacobs A. Identification of Ebola Virus Inhibitors Targeting GP2 using Principles of Molecular Mimicry. J Virol. 2019; 93 (15) e00676-19; DOI: 10.1128/JVI.00676-19.