Literature DB >> 24554192

Prospective virtual screening for novel p53-MDM2 inhibitors using ultrafast shape recognition.

Sachin P Patil1, Pedro J Ballester, Cassidy R Kerezsi.   

Abstract

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.

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Year:  2014        PMID: 24554192     DOI: 10.1007/s10822-014-9732-4

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  32 in total

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Journal:  Science       Date:  1996-11-08       Impact factor: 47.728

Review 5.  The structure-based design of Mdm2/Mdmx-p53 inhibitors gets serious.

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6.  Identification of FDA-approved drugs that computationally bind to MDM2.

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Journal:  Chem Biol Drug Des       Date:  2012-07-23       Impact factor: 2.817

7.  Structures of low molecular weight inhibitors bound to MDMX and MDM2 reveal new approaches for p53-MDMX/MDM2 antagonist drug discovery.

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10.  Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification.

Authors:  Pedro J Ballester; Martina Mangold; Nigel I Howard; Richard L Marchese Robinson; Chris Abell; Jochen Blumberger; John B O Mitchell
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  9 in total

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Journal:  J Comput Aided Mol Des       Date:  2018-08-06       Impact factor: 3.686

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

Authors:  Sachin P Patil; Michael F Pacitti; Kevin S Gilroy; John C Ruggiero; Jonathan D Griffin; Joseph J Butera; Joseph M Notarfrancesco; Shawn Tran; John W Stoddart
Journal:  J Comput Aided Mol Des       Date:  2014-11-07       Impact factor: 3.686

3.  Structure- and ligand-based virtual screening identifies new scaffolds for inhibitors of the oncoprotein MDM2.

Authors:  Douglas R Houston; Li-Hsuan Yen; Simon Pettit; Malcolm D Walkinshaw
Journal:  PLoS One       Date:  2015-04-17       Impact factor: 3.240

4.  UFSRAT: Ultra-fast Shape Recognition with Atom Types--the discovery of novel bioactive small molecular scaffolds for FKBP12 and 11βHSD1.

Authors:  Steven Shave; Elizabeth A Blackburn; Jillian Adie; Douglas R Houston; Manfred Auer; Scott P Webster; Paul Taylor; Malcolm D Walkinshaw
Journal:  PLoS One       Date:  2015-02-06       Impact factor: 3.240

5.  Biochemical evaluation of virtual screening methods reveals a cell-active inhibitor of the cancer-promoting phosphatases of regenerating liver.

Authors:  Birgit Hoeger; Maren Diether; Pedro J Ballester; Maja Köhn
Journal:  Eur J Med Chem       Date:  2014-08-20       Impact factor: 6.514

6.  USR-VS: a web server for large-scale prospective virtual screening using ultrafast shape recognition techniques.

Authors:  Hongjian Li; Kwong-S Leung; Man-H Wong; Pedro J Ballester
Journal:  Nucleic Acids Res       Date:  2016-04-22       Impact factor: 16.971

7.  Predicting the Reliability of Drug-target Interaction Predictions with Maximum Coverage of Target Space.

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Journal:  Sci Rep       Date:  2017-06-19       Impact factor: 4.379

Review 8.  Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery.

Authors:  Ashutosh Kumar; Kam Y J Zhang
Journal:  Front Chem       Date:  2018-07-25       Impact factor: 5.221

9.  A topology-based network tree for the prediction of protein-protein binding affinity changes following mutation.

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  9 in total

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