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Identification of antipsychotic drug fluspirilene as a potential p53-MDM2 inhibitor: a combined computational and experimental study

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Abstract

The inhibition of tumor suppressor p53 protein due to its direct interaction with oncogenic murine double minute 2 (MDM2) protein, plays a central role in almost 50 % of all human tumor cells. Therefore, pharmacological inhibition of the p53-binding pocket on MDM2, leading to p53 activation, presents an important therapeutic target against these cancers expressing wild-type p53. In this context, the present study utilized an integrated virtual and experimental screening approach to screen a database of approved drugs for potential p53-MDM2 interaction inhibitors. Specifically, using an ensemble rigid-receptor docking approach with four MDM2 protein crystal structures, six drug molecules were identified as possible p53-MDM2 inhibitors. These drug molecules were then subjected to further molecular modeling investigation through flexible-receptor docking followed by Prime/MM-GBSA binding energy analysis. These studies identified fluspirilene, an approved antipsychotic drug, as a top hit with MDM2 binding mode and energy similar to that of a native MDM2 crystal ligand. The molecular dynamics simulations suggested stable binding of fluspirilene to the p53-binding pocket on MDM2 protein. The experimental testing of fluspirilene showed significant growth inhibition of human colon tumor cells in a p53-dependent manner. Fluspirilene also inhibited growth of several other human tumor cell lines in the NCI60 cell line panel. Taken together, these computational and experimental data suggest a potentially novel role of fluspirilene in inhibiting the p53-MDM2 interaction. It is noteworthy here that fluspirilene has a long history of safe human use, thus presenting immediate clinical potential as a cancer therapeutic. Furthermore, fluspirilene could also serve as a structurally-novel lead molecule for the development of more potent, small-molecule p53-MDM2 inhibitors against several types of cancer. Importantly, the combined computational and experimental screening protocol presented in this study may also prove useful for screening other commercially-available compound databases for identification of novel, small molecule p53-MDM2 inhibitors.

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Acknowledgments

We thank Dr. Bert Vogelstein at the Johns Hopkins University for the HCT-116 cell lines and Dr. Jeffrey Rufinus from Department of Computer Science for use of computer cluster for molecular dynamics simulations. We also thank the National Cancer Institute (NCI) for carrying out NCI60 screening of fluspirilene. The present study is supported by the Widener University Provost Grant to Dr. Sachin P. Patil.

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Authors and Affiliations

  1. NanoBio Laboratory, Department of Chemical Engineering, Widener University, Chester, PA, 19013, USA

    Sachin P. Patil, Michael F. Pacitti, Kevin S. Gilroy, John C. Ruggiero & Joseph J. Butera

  2. Department of Biomedical Engineering, Widener University, Chester, PA, 19013, USA

    Jonathan D. Griffin

  3. Department of Computer Science, Widener University, Chester, PA, 19013, USA

    Joseph M. Notarfrancesco, Shawn Tran & John W. Stoddart

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  1. Sachin P. Patil
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  2. Michael F. Pacitti
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Correspondence to Sachin P. Patil.

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Patil, S.P., Pacitti, M.F., Gilroy, K.S. et al. Identification of antipsychotic drug fluspirilene as a potential p53-MDM2 inhibitor: a combined computational and experimental study. J Comput Aided Mol Des 29, 155–163 (2015). https://doi.org/10.1007/s10822-014-9811-6

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  • DOI: https://doi.org/10.1007/s10822-014-9811-6

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