Prediction of African Swine Fever Virus Inhibitors by Molecular Docking-Driven Machine Learning Models.

ABSTRACT: African swine fever virus (ASFV) causes a highly contagious and severe hemorrhagic viral disease with high mortality in domestic pigs of all ages. Although the virus is harmless to humans, the ongoing ASFV epidemic could have severe economic consequences for global food security. Recent studies have found a few antiviral agents that can inhibit ASFV infections. However, currently, there are no vaccines or antiviral drugs. Hence, there is an urgent need to identify new drugs to treat ASFV. Based on the structural information data on the targets of ASFV, we used molecular docking and machine learning models to identify novel antiviral agents. We confirmed that compounds with high affinity present in the region of interest belonged to subsets in the chemical space using principal component an

SUBMITTER: Choi J 

PROVIDER: S-EPMC8231271 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature