Quantum mechanical parameters-based study of aryl sulphonamides as 5-HT6 serotonin ligand using DFT methods

Abstract

In the present work, quantum mechanical descriptors have been used for the development of quantitative structure activity relationship (QSAR) models for the thirty-two derivatives of aryl sulphonamide and sulfone based 5-HT6 antagonists. Among several classes of serotonin 5-HT6 receptor ligands, aryl sulphonamides reported better affinity towards the receptor. Drugs acting as serotonin ligands are useful in the treatment of a variety of mental disorders. The descriptors that have been used in our study are total energy, log P, molecular weight, dipole moment, heat of formation, LUMO energy, HOMO energy and electrophilicity index. The geometry optimization and evaluation of descriptors of all the compounds has been done with the help of CAChe Pro software using DFT-B88-LYP method with double-zeta valence polarized (DZVP) basis set. The best QSAR model for this set of derivatives has been obtained by combination of descriptors molecular weight, dipole moment and heat of formation. The descriptor molecular weight gives a mono-parametric QSAR model with remarkable predictive ability with positive contribution. The descriptor molecular weight is present in all best bi-parametric and tri-parametric QSAR models. Statistical parameters such as correlation coefficient, cross validation coefficient, standard error etc. were used to validate the predictability of QSAR models.