Unveiling the antiviral inhibitory activity of ebselen and ebsulfur derivatives on SARS-CoV-2 using machine learning-based QSAR, LB-PaCS-MD, and experimental assay.

ABSTRACT: Ebsulfur and ebselen derivatives that were proven to be potent inhibitors against the main protease (M^Pro) of SARS-CoV-2 which is an essential enzyme for viral replication were chosen to study the quantitative structure-activity relationship (QSAR) analysis using a classical multiple linear regression (MLR) and a machine learning approach of random forest (RF) and artificial neural network (ANN) in order to find the relationship between molecular structural properties and biological inhibitory activities. With the statistical criteria, the R² values of MLR, RF, and ANN models for the training set were 0.83, 0.82, and 0.92, respectively. The RMSE values of the test were considered for model evaluation, and the results were 0.27, 0.18, and 0.09 for MLR, RF, and ANN mode

SUBMITTER: Sinsulpsiri S 

PROVIDER: S-EPMC11865625 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature