Abstract
The search for newer cytotoxic agents has taken many paths in the recent years and in fact some of these efforts led to the discovery of some potent cytotoxic agents. Though the vast number of targets of tumor progression has been identified recently, kinases remained key targets in drug design. It is well established that inhibition of JNK1, a serine/threonine protein kinase delays tumor formation. Poly hydroxylated chromenone analog, quescetagetin, inhibits JNK1. As a part of design of coumarin based JNK1 inhibitors, docking studies and 4D QSAR studies were carried out. 3- pyrazolyl substituted coumarin derivatives were chosen for these studies. Docking studies revealed that 3-pyrazolyl substituted coumarins make key interactions with residues at active site of JNK1. In order to investigate the structural features required in these inhibitors, 4D QSAR studies using LQTAgrid module were carried out. The 4D QSAR model built with PLS regression on the matrix of variables specific for interaction energies at each grid point around the molecular dynamics generated conformations of individual compounds shows good predictive abilities. The squared correlation coefficient, R2 for the model is 0.785, R2 cross-validated (Q2) is 0.698, R2 predicted is 0.701. Most of the descriptors contributing to 4D QSAR model are Coulombic potential energy based descriptors which highlight the importance of specific atoms in coumarin derivatives in generating these electrostatic potential at specific grid points with the -NH3 probe. We rationalize that solvent accessible van der Waals surface area around such compounds is good measure of this Coulombic potential energy and can be exploited in designing more active compounds.
Keywords: Anticancer agents, coumarin, LQTAgrid QSAR, molecular dynamics, METLAB, partial least square regression, quantum mechanics.
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