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Background: Despite significant progress in the development of anticancer medications, obstacles such as drug resistance, poor efficacy, and excessive toxicity have significantly impacted the daily lives of cancer patients. Consequently, the search for highly selective, effective, and non-toxic molecules remains a major challenge for cancer researchers. Objective: To utilize a computer program for evaluating new benzothiophene derivatives to investigate how they influence the estrogen-related receptor-gamma (ERRγ) active sites as anticancer agents. Methods: The molecular docking method used the Cambridge Crystallographic Data Centre's (CCDC) Genetic Optimization for Ligand Docking (GOLD) tool. We used the Desmond modules of the Schrodinger 2023 to perform MDS on the derivative with the highest docking score. The Swiss ADME server then assessed our drugs' pharmacokinetic profile, which included how well they crossed the blood-brain barrier (BBB), bound to P-gp, and were bioavailable. Results: The compounds were docked with the ERRγ crystal structure (2GPV) to assess their binding affinity to active sites. One of them earned a high score (102.62), and six compounds had a higher binding energy than the gold standard medication, tamoxifen. The molecular dynamic simulation analysis found that compound 1 closely matched the ERRγ based on RMSD and RMSF data. After examining the ADME study of practically active substances, they follow Lipinski's laws and other pharmacokinetic features. Conclusions: These chemicals have the potential to act as precursors in the development of new anticancer medicines.
Abdulqader et al. (Sun,) studied this question.