%0 Journal Article
%T Structure-based Multi-targeted Molecular Docking and Molecular Dynamic Simulation Analysis to Identify Potential Inhibitors against Ovarian Cancer
%A Bandar Hamad Aloufi
%J Journal of Biochemical Technology
%@ 0974-2328
%D 2022
%V 13
%N 2
%R 10.51847/b1KFmETha6
%P 29-39
%X Ovarian Cancer (OC) is among the most prevalent cancers in females. OC is one of the deadliest and worst prognosis diseases. Currently, there are no approved OC screening tests or early detection methods. Hence, new screening, prevention, and early detection strategies are still highly demanded. Plant compounds have recently become increasingly important in developing new, effective, and affordable anti-cancer drugs. To investigate the protein-ligand interaction, molecular docking was used with the Molecular Operating Environment (MOE) tool to find the best inhibitor for the target proteins. Compound spatial affinity for the active sites of the NY-ESO-1, RUNX3, and UBE2Q1 proteins was calculated using molecular docking. ADMET analysis was used to determine the drug-likeness of the selected compounds, while MD simulation and MMGBSA/MMPBSA experiments were used to further understand the binding behaviors. Pre-clinical tests can help confirm the validity of our in silico studies and determine whether the compound can be used as an anti-cancer drug to treat OC.
%U https://jbiochemtech.com/article/structure-based-multi-targeted-molecular-docking-and-molecular-dynamic-simulation-analysis-to-identi-r10cgwcpkz7sv60