AI-assisted generation and in-depth in-silico evaluation of potential inhibitor targeting aurora kinase A (AURKA): An anticancer discovery exploiting synthetic lethality approach

Abstract

Genetic alterations are lead causative agents behind the complex pathologies of cancers which render all treatments unarmed. Such alterations in oncogenes can be treated by direct inhibition by specific drugs while alteration in tumor suppressor genes mediating loss of function is challenging to treat. Identification of synthetic lethal partners to specific tumor suppressor genes and mediating their inhibition can be a potential approach to deal with loss of function mutations. Aurora kinase A (AURKA) has been established as an effective synthetic lethal partner of several tumor suppressor genes and is overexpressed in cancerous conditions, mediating adverse pathologies. The present AI-assisted study deals with the generation of novel inhibitor compounds against AURKA and the exhaustive evaluation of the best compound using molecular docking, molecular dynamic simulation, MM/PBSA, and QM/MMGBSA-based analysis. Out of the 200 novel compounds generated using features of ATP binding pocket of AURKA and previously reported inhibitor, compound 1 (4-{5-fluoro-6-[(1Z)-3-hydrazinyl-3-oxo-2-phenylprop-1-en-1-yl]pyridin-2-yl}benzoic acid) was identified as the most potent candidate with high negative binding energy of -10.4 kcal/mol in molecular docking analysis. The molecular dynamic simulation analysis resulted in major conformational changes in the conserved DFG motif and loop 277-291 of AURKA in the apo-AURKA compared to AURKA-compound 1 complex thus maintaining open ATP binding cavity in apo-form and inhibiting the entry of ATP to its binding site in complex form. The free energy landscape displayed a persistence of folded states of the enzyme in complex form. The MM/PBSA revealed effective Gibb's free energy of binding of -11 kcal/mol for compound 1 inhibiting AURKA. The QM/MMGBSA analysis resulted in a significantly high negative binding energy of -13.98 kcal/mol proving significant inhibition potential of compound 1 against AURKA. Therefore, further in-vitro investigation can provide a novel effective, and safe treatment against a wide range of cancers by targeting a well-established cancer target AURKA.

Keywords: Artificial intelligence; Aurora kinase A (AURKA); Cancer; MM/PBSA; Molecular dynamic simulation; QM/MMGBSA.