In silico analysis of Diosmetin as an effective chemopreventive agent against prostate cancer: molecular docking, validation, dynamic simulation and pharmacokinetic prediction-based studies

Abstract

Prostate cancer is the second most dangerous cancer type worldwide. While various treatment options are present i.e. agonists and antagonists, their utilization leads to adverse effects and due to this resistance developing, ultimately the outcome is remission. So, to overcome this issue, we have undertaken an in-silico investigation to identify promising and unique flavonoid candidates for combating prostate cancer. Using GOLD software, the study assessed the effectiveness of 560 natural secondary polyphenols against CDKN2. Protein Data Bank was used to retrieve the 3D crystal structure of CDKN2 (PDB Id: 4EK3) and we retrieved the structure of selected secondary polyphenols from the PubChem database. The compound Diosmetin shows the highest GOLD score with the selected Protein i.e. CDKN2 which is 58.72. To better understand the 2-dimensional and 3-dimensional interactions, the interacting amino acid residues were visualised using Discovery Studio 3.5 and Maestro 13.5. Using Schrodinger-Glide, the Diosmetin and CDKN2 were re-docked, and decoy ligands were docked to CDKN2, which was used to further ascertain the study. The ligands with the highest Gold score were forecasted for pharmacokinetics characteristics, and the results were tabulated and analysed. Utilising the Gromacs software and Desmond packages, 100 ns of Diosmetin molecular dynamics simulations were run to evaluate the structural persistence and variations of protein-ligand complexes. Additionally, our investigation revealed that Diosmetin had a better binding affinity with CDKN2 measuring 58.72, and it also showed remarkable stability across a 100-ns simulation. Thus, following in-vitro and in-vivo clinical studies, diosmetin might lead to the Prostate regimen. Communicated by Ramaswamy H. Sarma