Quantitative structure-activity relationships analysis, homology modeling, docking and molecular dynamics studies of triterpenoid saponins as Kirsten rat sarcoma inhibitors

Oncogenic Kirsten RAt Sarcoma (KRAS) mutations are attractive targets in non-small-cell lung cancer (NSCLC). Thus, the objective of this work is to discover promising inhibitors that target this protein using in silico methods that have become increasingly cost-effective in research and development of drugs. In this study, 24 triterpenoid saponins were selected for designing the potent inhibitors using different methods: quantitative structure activity relationships (QSAR) analysis, homology modeling, as well as molecular docking, molecular dynamics (MD) simulation and in silico Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) screening. The selected model was presented high-squared cross-validation coefficient Q(2) = 0.85, and external validation R(2)pred = 0.75. In addition, the best comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models presented high values of Q(2) = 0.77 and 0.784 and values of R(2)pred = 0.87 and 0.83, respectively. After that, homology modeling was carried out for modeling the selected target and then validated by both Ramachandran plot and Qualitative Model Energy ANalysis (QMEAN) score of 0.83, indicating the best accuracy of the modeled protein with the experimental results. Furthermore, molecular docking study was conducted to better understanding the binding mechanism of homologous protein with triterpenoid saponins. In addition, MD simulations confirmed the stability of the selected complex systems during 10,000 femtosecondes (fs). According to these studies, three molecules were picked out as potential inhibitors. Indeed, the oral bioavailability and the toxicity of the predicted triterpenoid saponins have been found respecting the ADMET properties. Communicated by Ramaswamy H Sarma

Automated summary

Using computational methods and bioinformatics techniques, potential inhibitors targeting the KRAS mutated protein were screened using various analytical and simulation methods, and the accuracy and stability of the simulation results were validated.