Predicting Acyl-Coenzyme A: Cholesterol O-Acyltransferase Inhibitory Activity: Computational Approach Using Topological Descriptors

Abstract

Relationship between the topological indices and acyl-coenzyme A:cholesterol O-acyltransferase (ACAT) inhibitory activity of (aminosulfonyl)ureas has been investigated. Three topological indices, Wiener's index—a distance-based topological descriptor, molecular connectivity index—an adjacency-based topological index, and eccentric connectivity index—an adjacency-cum-distance–based topological descriptor, were used for the present investigations. A data set comprising 41 analogues of substituted (aminosulfonyl) ureas was selected for the present studies. The values of wiener's index, eccentric connectivity index, and molecular connectivity index for each of the 41 compounds comprising the data set were computed using an in-house computer program. Resultant data were analyzed and suitable models were developed after identification of active ranges. Subsequently, a biological activity was assigned to each compound using these models, which was then compared with the reported in vitro ACAT inhibitory activity. Accuracy of prediction using these models was found to vary from a minimum of ∼83% to a maximum of ∼91%.