Development of Structure Activity Correlation Model on Aroylindole Derivatives as Anticancer Agents

Abstract

Background: Aroylindole derivatives, the structural analogs of Combretastatin A-4 has been found to possess potent growth inhibitory activity on several cancer cell lines due to its excellent antitumor and antivascular activities. The aim of present research work is to identify lead and establish structure activity correlation of trimethoxyaroylindole derivatives, using integrated ligand and structure based computational approaches. Materials and Methods: A correlation between structure and biological activity was established using computational approaches i.e., structure activity correlation by pharmacophore and atom based 3D QSAR, molecular docking and energetic based pharmacophore mapping studies of trimethoxyaroylindole derivatives. Results and Discussion: The 3D-QSAR on trimethoxyaroylindole derivatives generated and showed best statistical result for CPHs AAARR.182 was validated by Q2 (0.6929), R2 (0.82). The Comp. 1 of the training set was employed as template for hydrogen bond donor, hydrophobic and hydrogen bond acceptor field prediction features and visualization of the 3D-QSAR model provides details of relationship between structure and biological activity of trimethoxyaroylindole derivatives. Pharmacophore model was developed by Phase and e-pharmacophore on comp. 1, the trimethoxy group with ring A, keto group, N-H group with ring B and ring C are pharmacophoric group important for the lead generation and coincide with various chemical features that may facilitate non-covalent binding between the ligand and its target receptor. Molecular docking studies showed critical interactions between Cys241, Val318 and meta, para-methoxy group at ring A while and Thr179 and NH of indole (distance 3.5 Å). The para position of trimethoxyphenyl ring bind to SH group of CYS 241 receptor molecule via hydrogen bond. Conclusion: The lead identification and establish structure activity correlation of trimethoxyaroylindole derivatives, were performed using integrated ligand and structure based computational approaches i.e., atom based 3D QSAR and pharmacophore study, molecular docking, energetic based pharmacophore mapping studies showed promising results. The outcomes of present studies could be utilized for the design of novel aroylindole derivatives including its lead optimization as potential anticancer agent.