collaborative research to uncover molecular modifications for COVID-19 medications

The study “Data Driven Computational Design and Experimental Validation of Drugs for Accelerated Mitigation of Pandemic-like Scenarios,” which was published by a multidisciplinary collaboration at Virginia Tech, focuses on using computer algorithms to generate modifications to molecules in compounds for current and prospective medications that can improve their ability to bind to the main protease in SARS-CoV-2, the virus that causes COVID-19.

In a study published by a multidisciplinary collaboration at Virginia Tech, “Data Driven Computational Design and Experimental Validation of Drugs for Accelerated Mitigation of Pandemic-like Scenarios,” the authors focus on using computer algorithms to generate modifications to molecules in compounds for both current and future medications that can improve their ability to bind to the main protease in SARS-CoV-2, the virus that causes COVID-19.

Significant cross-departmental cooperation, including four Virginia Tech faculty members, four associate professors, Andrew Lowell, and James Weger-Lucarelli, among others, made the study possible. In a veterinary college laboratory, the functionalized molecules were tested against live SARS-CoV-2, and the results demonstrated that the new drug was more effective against the virus than the parent compound. Non-biological applications of the algorithm method include the functionalization and design of various materials such polymers, glycomaterials, and metal organic frameworks.