Network-base approaches to identify therapeutic biomarkers in hepatocellular carcinoma and search for drug hunting utilizing molecular dynamics simulations

Abstract

The presence of conditions like Alpha-1 antitrypsin deficiency, hemochromatosis, non-alcoholic fatty liver diseases and metabolic syndrome can elevate the susceptibility to hepatic cellular carcinoma (HCC). Utilizing network-based gene expression profiling via network analyst tools, presents a novel approach for drug target discovery. The significance level (p-score) obtained through Cytoscape in the intended center gene survival assessment confirms the identification of all target center genes, which play a fundamental role in disease formation and progression in HCC. A total of 1064 deferential expression genes were found. These include MCM2 with the highest degree, followed by 4917 MCM6 and MCM4 with a 3944-degree score. We investigated the regulatory kinases involved in establishing the protein-protein interactions network using X2K web tool. The docking approach yields a favorable binding affinity of −8.7 kcal/mol against the target MCM2 using Auto-Dock Vina. Interestingly after simulating the complex system via AMBER16 package, results showed that the root mean square deviation values remained within 4.74 Å for a protein and remains stable throughout the time intervals. Additionally, the ligand’s fit to the protein exhibited fluctuations at some intervals but remains stable. Finally, Gibbs free energy was found to be at its lowest at 1 kcal/mol which presents the real time interactive binding of the atomic residues among inhibitor and protein. The displacement of the ligand was measured showing stable movement and displacement along the active site. These findings increased our understanding for potential biomarkers in hepatocellular carcinoma and an experimental approach will further enhance our outcomes in future.

Communicated by Ramaswamy H. Sarma

Keywords:

• Principal component 1
• hub gene 2
• cytoscape 3
• differentially expressed genes 4
• hydrogen bonds 5

Acknowledgments

The authors are thankful to the researchers supporting project number [RSP2024R335], King Saud University, Riyadh, Saudi Arabia.

Authors’ contribution

Conceptualization of the idea is presented by H.A. and F.A.; methodology section done by H.A. and F.A.; software usage done by S.A. and F.A.; validation of the data performed by Q.A., F.S. and A.F.A.; formal analysis done by S.C.; investigation done by F.S. and B.R.; resources, S.S.A.; data curation, S.S.A and A.Z.; writing—original draft preparation, H.A., T.H.A. and F.A.; writing—review and editing, F.A.; visualization, S.C.; supervision, M.S. and Y.W. All authors have read and agreed to the published version of the manuscript.

Data availability statement

The text and its supporting information files contains all pertinent data.

Disclosure statement

The authors declare no conflict of interest.

Additional information

Funding

The authors are thankful to the researchers supporting project number [RSP2024R335], King Saud University, Riyadh, Saudi Arabia.