In-Silico Perspectives on the Potential Therapeutic Aids of Hesperetin Derivatives for Lung Cancer

Abstract

Background: Lung carcinoma has become one of the most noteworthy and dangerous health problems discovered today. The disease is mainly caused by smoking and becomes among the leading causes of death spread by growing the cancerous cells into the lining of the lungs and nearby lobes. The FDA has given clearance to numerous drugs and chemotherapy agents; nevertheless, they can be exceedingly costly as well as frequently fall short of entirely addressing the ailment. In the medical management of lung cancer, new medicines or active leads with high efficacy and minimal toxicity are required in this era. Methods: The study has been conducted with the intent to uncover a prospective approach to treating lung cancer through structural modification of Hesperetin by creating its analogs to enhance its efficacy compared to its parent compound with the computational drug design. The analysis has been conducted with various approaches followed by PASS prediction, ADME, toxicity profile, molecular docking, data filtration, and anticancer activity. Results: All the compounds showed satisfactory criteria in each parameter that was assessed. The data mining was done carefully by pointing out the compounds that had the greatest value among all the compounds in each investigation, which resulted in a total of 3 compounds out of 50. Conclusions: Finally, the selected compounds were further analyzed for MD simulation studies. Afterward, PCA analysis was also conducted in order to get the lead compound with this additional investigation.