Machine Learning Models Identify Inhibitors of SARS-CoV-2.

ABSTRACT: With the rapidly evolving SARS-CoV-2 variants of concern, there is an urgent need for the discovery of further treatments for the coronavirus disease (COVID-19). Drug repurposing is one of the most rapid strategies for addressing this need, and numerous compounds have already been selected for in vitro testing by several groups. These have led to a growing database of molecules with in vitro activity against the virus. Machine learning models can assist drug discovery through prediction of the best compounds based on previously published data. Herein, we have implemented several machine learning methods to develop predictive models from recent SARS-CoV-2 in vitro inhibition data and used them to prioritize additional FDA-approved compounds for in vitro testing s

SUBMITTER: Gawriljuk VO 

PROVIDER: S-EPMC8574161 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature