OpenTox Virtual Conference 2021 Session 2
Viribus unitis – utility and modeling of drug combinations
Eugene N. Muratova,* and Alexey Zakharovb
a Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, 27599, USA.
b National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, Maryland 20850, United States
The opportunities that may be provided by synergistic antiviral action of drugs for battling SARS-CoV2 are currently underestimated. Modern AI technologies realized as text, data, and knowledge mining and analytics tools provide the researchers with unprecedented opportunities for “smart” design of drug combinations with synergistic antiviral activities. The goal of this talk is to emphasize combination therapy as a potential treatment against COVID-19 and to utilize the combination of modern machine learning and AI technologies with our expertise to select the most promising drug combinations with further experimental validation. We hypothesized that combining drugs with independent mechanisms of action could result in synergy against SARS-CoV-2, thus generating better antiviral efficacy. Using in silico approaches, we prioritized 73 combinations of 32 drugs with potential activity against SARS-CoV-2 and then tested them in vitro. Sixteen synergistic and eight antagonistic combinations were identified; among 16 synergistic cases, combinations of the FDA-approved drug nitazoxanide with remdesivir, amodiaquine, or umifenovir were most notable, all exhibiting significant synergy against SARS-CoV-2 in a cell model. However, the combination of remdesivir and lysosomotropic drugs, such as hydroxychloroquine, demonstrated strong antagonism. Overall, these results highlight the utility of drug repurposing and preclinical testing of drug combinations for discovering potential therapies to treat COVID-19.
CV: Eugene N. Muratov is a Research Associate Professor and Associate Director of the Laboratory for Molecular Modeling at the UNC Eshelman School of Pharmacy, UNC-Chapel Hill. He received MS in technology of organic substances from Odessa National Polytechnic University in 2000 and PhD in organic chemistry in 2004 from the A.V. Bogatsky Physical-Chemical Institute. In 2014-2020 he was a Visiting Professor at the Federal Universities of Goias and Paraiba, Brazil. His research interests are in the areas of cheminformatics (especially QSAR), computer-assisted drug design, antiviral research, computational toxicology, and medicinal chemistry. He has co-authored ~150 peer-reviewed publications and edited two books.
