Bio-activity of aminosulfonyl ureas in the light of nucleic acid bases and DNA base pair interaction.

The quantum chemical descriptors based on density functional theory (DFT) are applied to predict the biological activity (log IC) of one class of acyl-CoA: cholesterol O-acyltransferase (ACAT) inhibitors, viz. aminosulfonyl ureas. ACAT are very effective agents for reduction of triglyceride and cholesterol levels in human body. Successful two parameter quantitative structure-activity relationship (QSAR) models are developed with a combination of relevant global and local DFT based descriptors for prediction of biological activity of aminosulfonyl ureas. The global descriptors, electron affinity of the ACAT inhibitors (EA) and/or charge transfer (ΔN) between inhibitors and model biosystems (NA bases and DNA base pairs) along with the local group atomic charge on sulfonyl moiety (∑Q) of the inhibitors reveals more than 90% efficacy of the selected descriptors for predicting the experimental log (IC) values.