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Mutations in the p53 gene are common and occur in over 50% of all cancers, as it is involved in DNA damage repair, cell cycle regulation and apoptosis. Moreover, the p53 gene is mutated in 70% of colon cancers. Therefore, the development of drugs to combat this mutation requires urgent attention. With this in mind,  in silico  drug design approaches were applied on quinoline derivatives with anticancer activity. In 3D-QSAR study, steric, electrostatic, hydrophobic and H-bond acceptor fields (SEHA) play an important role in prediction and design of new colon cancer compounds. Indeed, the two best CoMSIA/SEHA models with ( Q2  = 0.737,  R2  = 0.914,= 0.720) and ( Q2  = 0.738,  R2  = 0.919,= 0.739) show good prediction of human colon carcinoma HCT 116 (p53 +/+ ) and (p53 −/− ) activities, respectively. Furthermore, the predictive ability and robustness of these models were tested by several validation methods. Molecular docking analyses reveal crucial interactions with the active sites of the p53 protein in both wild type and mutant. Based on these theoretical studies, we designed 10 new compounds with good anticancer activity potential, which were evaluated using ADMET properties. Molecular dynamics simulations were performed to confirm the detailed binding mode of the docking results. Finally, the MM-GBSA based on molecular dynamics simulation confirmed that the designed compounds were able to form stable hydrogen bonding interactions with the crucial residues, which are essential to overcome the p53 mutation in colon cancer. Communicated by Ramaswamy H. Sarma

Discovery of anti-colon cancer agents targeting wild-type and mutant p53 using computer-aided drug design