QSAR of Lipid-Coated Virus Inhibition by Fatty Acids and Monoglycerides Using Electropological Descriptors

Abstract

E-State QSAR models were developed for the inhibition of a lipid-coated virus with a set of 19 fatty acids (FA) and their monoglycerides (MG). The FA and MG were also divided into two subsets to improve correlations, the saturated (n = 12) and the unsaturated set (n = 7). QSAR of the sets yielded better correlation statistics; the saturated FA and MG gave r2 = 0.87, s = 0.26 while the QSAR of the unsaturated FA and MG gave r2 = 0.9999, s = 0.0041. The combined set model however yielded only r2 = 0.81, s = 0.32. Statistically satisfactory four and five variable models for the saturated and the unsaturated respectively and three variable model for the combined set FA and MG were developed. Structure interpretation is given for each variable emphasizing their effects on the resulting viral inhibition (pIC values). A leave-one-out method (LOO) was applied to investigate the predictive quality of each of the QSAR equation. This predictive quality of the multiple regression equation will be useful in the prediction of new potential antiviral compounds against lipid-coated virus. This paper hopes that the study could also be applied to SARS-CoV-2 virus, which is also a lipid-coated virus.