34th Annual Student Research Conference
Computational Drug Discovery for a Protease Inhibitor as a Treatment for the Coronavirus Disease
Marissa D. Pina
Dr. Bill R. Miller, Faculty Mentor
COVID-19 is a global pandemic that has resulted in 2.65 million deaths worldwide. COVID-19 is caused by the novel coronavirus, SARS-CoV-2. The current study aims to find a suitable inhibitor for the main protease of SARS-CoV-2. To test for novel inhibitors, 5180 known protease inhibitors were screened using Autodock QuickVina02. The 38 inhibitors that resulted in the most favorable complexes were simulated using Amber18 Molecular Dynamics. The average binding free energies of the controls (N3, ebselen, and cinanserin) are -14.3, -17.0, and -16.2 kcal mol<sup>-1</sup>, respectively. The ligand with the best average binding free energy was optimized, and resulted in an average binding free energy of -43.9 kcal mol<sup>-1</sup>, which is a promising result since it is much lower than the average binding free energies of the controls. This work will help us find treatments capable of fighting the novel coronavirus.
Keywords: COVID-19, SARS-CoV-2, molecular dynamics, computational chemistry, inhibitor, drug discovery, main protease, coronavirus
Topic(s):Biochemistry and Molecular Biology
Presentation Type: Asynchronous Virtual Oral Presentation
Session: 3-1
Location: https://flipgrid.com/f86d186b
Time: 0:00