Computational-guided approach for identification of PI3K alpha inhibitor in the treatment of hepatocellular carcinoma by virtual screening and water map analysis

Abstract

Hepatocellular carcinoma (HCC) is one of the most deadly disorders, with a relative survival rate of 36% in the last 5 years. After an extensive literature survey and pathophysiology analysis, PI3Kα was found to be a promising biological target as PIK3CA gene upregulation was observed in HCC, resulting in the loss of apoptosis of cells, which leads to uncontrollable growth and proliferation. Due to superior selectivity and promising therapeutic activity, the PI3K-targeted molecule library was selected, and the ligand preparation was executed. The study mainly focused on e-pharmacophore development, virtual screening and receptor–ligand docking analysis. Then, MMGBSA and ADME prediction analysis was performed with the top 10 molecules; for further analysis of ligand–receptor binding affinity at the catalytic binding site, induced fit docking was performed with the top two molecules. The analysis of quantum chemical stability descriptors, i.e., frontier molecular orbital analysis, was performed followed by molecular dynamics simulation of 100 ns to better understand the ligand-receptor binding. In this study, water map analysis played a significant role in the hit optimization and analysis of the thermodynamic properties of the receptor–ligand complex. The two hit molecules K894-1435 and K894-1045 represented superior docking scores, enhanced stability, and inhibitory action targeting Valine 851 amino acid residue at the catalytic binding site. Hence, the study has significance for the quest for selective PI3Kα inhibitors through the process of hit-to-lead optimization.

Communicated by Ramaswamy H. Sarma

Keywords:

• hepatocellular carcinoma
• watermap
• ADME
• frontier molecular orbital
• thermodynamic

Acknowledgments

The author extend their sincere gratitude to the Manipal-Schrödinger Centre for Molecular Simulations, as well as the Manipal College of Pharmaceutical Sciences (MCOPS), Manipal Academy of higher Education (MAHE), Manipal for their invaluable support and providing of necessary resources throughout this study. The author acknowledges ACS Publications and ACS Digitallinc for publishing the conference paper related to the current study conducted and presented by the author [Halder, D & Das, S. (2023). Structure-based identification of PI3Kα inhibitors as potential leads against hepatocellular carcinoma by E-pharmacophore based virtual screening, molecular docking, ADME, DFT calculations, water thermodynamics and molecular dynamics (Link: https://acs.digitellinc.com/sessions/568256/view)].

The current manuscript is based on the aforementioned conference paper presented at ACS Spring 2023. The authors also thank ChemDraw and BioRender.com.

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Conflict of interests

The author declares no conflict of interest in this article.

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.