Back

Multidose evaluation of 6,710 drug repurposing library identifies potent SARS-CoV-2 infection inhibitors In Vitro and In Vivo.

Patten, J.; Keiser, P. T.; Gysi, D. M.; Menichetti, G.; Mori, H.; Donahue, C. J.; Gan, X.; do Valle, I. F.; Geoghegan-Barek, K.; Anantpadma, M.; Berrigan, J. L.; Jalloh, S. C.; Ayazika, K. T.; Wagner, F.; Zitnik, M.; Ayehunie, S.; Anderson, D.; Loscalzo, J.; Gummuluru, S.; Namchuk, M. N.; Barabasi, A.-L.; Davey, R. A.

2021-04-20 microbiology
10.1101/2021.04.20.440626 bioRxiv
Show abstract

Identification of host factors contributing to replication of viruses and resulting disease progression remains a promising approach for development of new therapeutics. Here, we evaluated 6710 clinical and preclinical compounds targeting 2183 host proteins by immunocytofluorescence-based screening to identify SARS-CoV-2 infection inhibitors. Computationally integrating relationships between small molecule structure, dose-response antiviral activity, host target and cell interactome networking produced cellular networks important for infection. This analysis revealed 389 small molecules, >12 scaffold classes and 813 host targets with micromolar to low nanomolar activities. From these classes, representatives were extensively evaluated for mechanism of action in stable and primary human cell models, and additionally against Beta and Delta SARS-CoV-2 variants and MERS-CoV. One promising candidate, obatoclax, significantly reduced SARS-CoV-2 viral lung load in mice. Ultimately, this work establishes a rigorous approach for future pharmacological and computational identification of novel host factor dependencies and treatments for viral diseases.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.