Identification of common genes in obesity and cancer through network interaction and targeting those genes by virtual screening approach

Abstract

Obesity may have an effect on cancer outcomes, resulting in global inequalities in cancer survival and death. Microarray data analysis was done to identify differentially expressed genes (DEGs) in obese and cancer patients. Total 1977 differentially expressed genes among obesity and gastric cancer, breast cancer, pancreatic cancer, and colorectal cancer were used to build a gene interaction network, which was then analyzed by using Cytoscape software. It has been identified that JUN, CXCL12, and LEP genes show a higher degree and stress, and play an important role in obesity and cancer progression. Further, CXCL12 and LEP were taken for virtual screening study with coumarin and its derivatives to develop a drug against obesity and cancer. The interactions of CXCL12 and LEP with coumarins were studied by molecular docking and it shows good interaction as well as docking score as compared to the standard one. The ADME properties were predicted to check the drug-likeness activity of coumarins and the most of the drug-likeness activities are in admire range. The Binding free energy of the docked complex was calculated by performing MM-GBSA. The molecular docking, ADME properties prediction, and MM-GBSA was performed on Maestro 12.6. The top docked score compounds were further subjected to molecular dynamic simulation to check the stability by using GROMACS. The MM-PBSA study was performed to calculate the binding energy components as well as the energy contributions of specific amino acids. The resultant compounds could be a potent anti-obesity and anti-cancer drug.

Communicated by Ramaswamy H. Sarma

Keywords:

• Obesity
• cancer
• microarray data analysis
• protein–protein interaction
• MD Simulation

Acknowledgments

The authors are grateful to the Indian Institute of Information Technology Allahabad for providing research work facilities. The authors gratefully acknowledge the financial support of the UP-CST for providing the JRF fellowship.

Disclosure statement

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

Additional information

Funding

The authors are grateful to the Indian Institute of Information Technology Allahabad for providing research work facilities. The authors gratefully acknowledge the financial support of the UP-CST for providing the JRF fellowship.