Computational design of quinoxaline molecules as VEGFR-2 inhibitors: QSAR modelling, pharmacokinetics, molecular docking, and dynamics simulation studies

Abstract

Cancer is a deadly condition characterized by accelerated cell proliferation. According to the World Health Organization, global cancer cases are projected to reach 22 million by 2030. Therefore, the relentless search for safer and more effective anticancer drugs remains an imperative direction in the research and progression of drugs targeting cancer. This work utilized a ligand-based approach to designing more effective quinoxaline derivatives for the VEGFR-2 enzyme, an important protein in the pathogenesis of breast cancer. To accomplish this task, a statistically validated QSAR model was built using quinoxaline derivatives. The developed model was used for the virtual screening of the quinoxaline derivatives, from which compound 8 with a high inhibitory capacity (pIC50 = 5.357) was selected as the design template from which five hypothetical molecules with better VEGFR-2 inhibitory capacities ranging from pIC50 = 5.43 to 6.16 were designed. Docking studies were performed with the designed molecules as ligands and the VEGFR-2 active site residues, and they were found to have docking scores ranging from −171.384 to −182.241 kcal/mol, which outperformed the template ligand with a score of −170.579 kcal/mol. MD simulation predicted a stable docked complex and that the ligands did not leave the VEGFR-2 active site over the course of 200ns simulation. The designed quinoxaline molecules exhibit drug-like and desired ADMET parameters, as revealed by the outcomes of drug-likeness and pharmacological profiling. Hence, this research could be significant in unearthing novel breast cancer-targeting molecules.