Drug resistance negatively impacts the lives of millions of patients and costs our society billions of dollars by limiting the longevity of many of our most potent drugs. Drug resistance can be caused by a change in the balance of molecular recognition events that selectively weakens inhibitor binding, but maintains the biological function of the target.  To reduce the likelihood of drug resistance, a detailed understanding of the target’s function is necessary.  Both structure at <i>atomic resolution </i>and <i>evolutionarily constraints</i> on its variation is required. This rationale was derived from our lab’s experience with substrate recognition and drug resistance in the viral proteases of HIV, HCV and most recently applying to emerging target of SARS-CoV-2.  This resulted in our development of the strategy of the substrate envelope and the use of parallel MD and machine learning to strategically avoid drug resistance and develop robust inhibitors.

Avoiding Drug Resistance:  Lessons from viral proteases, from HIV to SARS-CoV-2

Fall 2022 abstracts, posters, and presentations will launch in mid-September.

ACS Fall 2022

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.