QSAR studies on the antiviral compounds of natural origin

Abstract

Two data sets of natural antiviral agents including 107 anti-HIV1 and 18 anti-polio molecules were collected and subjected to quantitative structure-activity relationship (QSAR) analyses. A wide variety of molecular descriptors belonging to various structural properties were calculated for each molecule. Multiple linear regression (MLR) based on stepwise variable selection was employed to find the most convenient quantitative models. For each antiviral data set different QSAR models were established in two steps. Firstly, for each type of molecular descriptors separate QSAR analysis was performed, and then a new QSAR model was calculated using the selected descriptors in the first phase. For both types of antiviral data sets significant QSAR models were obtained. The atom-centered fragment descriptors represented the highest impact on the anti-HIV1 activity whereas for anti-polio agents, radial distribution function and three-dimensional MoRSE descriptors showed the most significant influences. Cross-validation and a separate prediction set were used to evaluate the stability and prediction ability of the models. It was found the discovered QSAR models for anti-HIV1 and anti-polio agents could reproduce about 80% and 90% of variances in the antiviral activity data with root mean square error of prediction of 0.421 and 0.171, respectively.