Discovery of Novel Noncovalent KRAS G12D Inhibitors through Structure-Based Virtual Screening and Molecular Dynamics Simulations

The development of effective inhibitors targeting the Kirsten rat sarcoma viral proto-oncogene (KRAS(G12D)) mutation, a prevalent oncogenic driver in cancer, represents a significant unmet need in precision medicine. In this study, an integrated computational approach combining structure-based virtual screening and molecular dynamics simulation was employed to identify novel noncovalent inhibitors targeting theKRAS(G12D) variant. Through virtual screening of over 1.7 million diverse compounds, potential lead compounds with high binding affinity and specificity were identified using molecular docking and scoring techniques. Subsequently, 200 ns molecular dynamics simulations provided critical insights into the dynamic behavior, stability, and conformational changes of the inhibitor-KRAS(G12D) complexes, facilitating the selection of lead compounds with robust binding profiles. Additionally, in silico absorption, distribution, metabolism, excretion (ADME) profiling, and toxicity predictions were applied to prioritize the lead compounds for further experimental validation. The discovered noncovalent KRAS(G12D) inhibitors exhibit promises as potential candidates for targeted therapy against KRAS(G12D)-driven cancers. This comprehensive computational framework not only expedites the discovery of novel KRAS(G12D) inhibitors but also provides valuable insights for the development of precision treatments tailored to this oncogenic mutation.