Abstract

Cancer remains the leading cause of mortality and morbidity in the world, with 19.3 million new diagnoses and 10.1 million deaths in 2020. Cancer is caused due to mutations in proto-oncogenes and tumor-suppressor genes. Genetic analyses found that Ras (Rat sarcoma) is one of the most deregulated oncogenes in human cancers. The Ras oncogene family members including NRas (Neuroblastoma ras viral oncogene homolog), HRas (Harvey rat sarcoma) and KRas are involved in different types of human cancers. The mutant KRas is considered as the most frequent oncogene implicated in the development of lung, pancreatic and colon cancers. However, there is no efficient clinical drug even though it has been identified as an oncogene for 30 years. Therefore there is an emerging need to develop potent, new anticancer drugs. In this study, computer-aided drug designing approaches as well as experimental methods were employed to find new and potential anti-cancer drugs. The pharmacophore model was developed from an already known FDA approved anti-cancer drug Bortezomib using the software MOE. The validated pharmacophore model was then used to screen the in-house and commercially available databases. The pharmacophore-based virtual screening resulted in 26 and 86 hits from in-house and commercial databases respectively. Finally, 6/13 (in-house database) and 24/64 hits (commercial databases) were selected with different scaffolds having good interactions with the significant active residues of KRasG12D protein that were predicted as potent lead compounds. Finally, the results of pharmacophore-based virtual screening were further validated by molecular dynamics simulation analysis. The 6 hits of the in-house database were further evaluated experimentally. The experimental results showed that these compounds have good anti-cancer activity which validate the protocol of our in silico studies. KRasG12D protein is a very important anti-cancer target and potent inhibitors for this target are still not available, so small lead compound inhibitors were identified to inhibit the activity of this protein by blocking the GTP-binding pocket. Communicated by Ramaswamy H. Sarma

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