Computational investigation of bisquinoline derivatives as potential c-met kinase inhibitors: 3D-QSAR, molecular docking, dynamics simulations, and ADME-Tox studies

Abstract

c-Met kinase is a key player in cancer progression, driving tumor growth and metastasis, making it an important target for cancer treatment. This study utilizes 3D-QSAR, molecular docking, and molecular dynamics simulations to evaluate bisquinoline derivatives as c-Met kinase inhibitors. CoMFA (Comparative Molecular Field Analysis) and CoMSIA (Comparative Molecular Similarity Indices Analysis) were employed to build 3D-QSAR models, with the CoMFA model demonstrating strong predictive performance (Q2 = 0.61; R2 = 0.94; R2pred = 0.67). CoMFA contour maps identified critical regions for anticancer activity. Based on these insights, four bisquinoline inhibitors T1, T2, T3, and T4 were proposed. ADME-Tox predictions indicated favorable pharmacokinetic and toxicological profiles for these candidates. Molecular docking demonstrated stable interactions of the proposed bisquinoline scaffold with the receptor c-Met active site (PDB ID: 4MXC), highlighting key interactions with residues such as Tyr-1230, Phe-1223, and Asp-1222. Molecular dynamics simulations revealed that T2 maintained the most stable interactions with the c-Met kinase over a 500 ns simulation, indicating strong binding affinity and potential effectiveness. While T1 also showed stability, T2 consistently outperformed the other candidates. These results reinforce the potential of these bisquinoline derivatives as c-Met kinase inhibitors, particularly highlighting T2 as a promising lead compound.