Prospective virtual screening for novel p53–MDM2 inhibitors using ultrafast shape recognition
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The p53 protein, known as the guardian of genome, is mutated or deleted in approximately 50 % of human tumors. In the rest of the cancers, p53 is expressed in its wild-type form, but its function is inhibited by direct binding with the murine double minute 2 (MDM2) protein. Therefore, inhibition of the p53–MDM2 interaction, leading to the activation of tumor suppressor p53 protein presents a fundamentally novel therapeutic strategy against several types of cancers. The present study utilized ultrafast shape recognition (USR), a virtual screening technique based on ligand–receptor 3D shape complementarity, to screen DrugBank database for novel p53–MDM2 inhibitors. Specifically, using 3D shape of one of the most potent crystal ligands of MDM2, MI-63, as the query molecule, six compounds were identified as potential p53–MDM2 inhibitors. These six USR hits were then subjected to molecular modeling investigations through flexible receptor docking followed by comparative binding energy analysis. These studies suggested a potential role of the USR-selected molecules as p53–MDM2 inhibitors. This was further supported by experimental tests showing that the treatment of human colon tumor cells with the top USR hit, telmisartan, led to a dose-dependent cell growth inhibition in a p53-dependent manner. It is noteworthy that telmisartan has a long history of safe human use as an approved anti-hypertension drug and thus may present an immediate clinical potential as a cancer therapeutic. Furthermore, it could also serve as a structurally-novel lead molecule for the development of more potent, small-molecule p53–MDM2 inhibitors against variety of cancers. Importantly, the present study demonstrates that the adopted USR-based virtual screening protocol is a useful tool for hit identification in the domain of small molecule p53–MDM2 inhibitors.
KeywordsUltrafast shape recognition Virtual screening DrugBank database p53 MDM2 Colon cancer cells
We thank Dr. Bert Vogelstein at the Johns Hopkins University for the HCT-116 cell lines, Dr. Shirley Fischer-Drowos from the Department of Chemistry for her kind assistance with WST-1 assay and John Stoddart from the Department of Computer Science for his assistance with virtual database screening. We also thank the National cancer Institute (NCI) for carrying out NCI60 screening of telmisartan. The present study is supported by the Widener University Provost Grant to Dr. Sachin P. Patil and the Medical Research Council’s Methodology Research Fellowship (Grant No. G0902106) to Dr. Pedro J. Ballester.
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