Topological models for prediction of anti-inflammatory activity of N-arylanthranilic acids

Relationship of anti-inflammatory activity of N-arylanthranilic acids with distance based Wiener's index, adjacency based Zagreb indices M1 and M2, and distance-cum-adjacency based eccentric connectivity index (ECI) was investigated. A dataset comprising of 112 N-arylanthranilic acids was selected. The values of all the four indices for each of the 112 compounds were calculated using an in-house computer program. The dataset was divided randomly into training and test sets. The data was analyzed and suitable models were developed after identification the active ranges in the training set. Subsequently, a biological activity was assigned to each of the compound involved in the test set using these models, which was then compared with the reported anti-inflammatory activity. High accuracy of prediction ranging from 83% to 90% was observed using models based upon topological indices.