Literature DB >> 22992059

Discovery of novel tubulin inhibitors via structure-based hierarchical virtual screening.

Ran Cao1, Minyu Liu, Min Yin, Quanhai Liu, Yanli Wang, Niu Huang.   

Abstract

To discover novel tubulin inhibitors, we performed structure-based virtual screening against the colchicine binding pocket. In combination with a hierarchical docking and scoring procedure, the structural information of an additional subpocket in colchicine site was applied to filter out the undesired docking hits. This strategy automatically resulted in 63 candidates meeting the structural and energetic criteria from a screening library containing approximately 100,000 diverse druglike compounds. Among them, nine molecules were chosen for experimental validation, which all share the similar binding pose and contain an enriched scaffold bearing thiophene core. Encouragingly, five compounds are active in tubulin polymerization assay. The most potent inhibitor, 2-(2-fluorobenzamido)-3-carboxamide-4,5-dimethylthiophene, is structurally distinct to any known colchicine site binders and has higher ligand efficiency than colchicine. On the basis of its predicted binding pose, we systematically probed its binding characteristics by testing series of structural modifications. The obtained structure-activity relationship results are consistent with our binding model, and the inhibition activities of two analogues are improved by 2-fold. We expect that the novel structure discovered in the present study may serve as a starting point for developing tubulin inhibitors with improved efficacy and fewer side effects. We also expect that our hierarchical strategy may be generally applicable in structure-based virtual screening campaigns.

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Year:  2012        PMID: 22992059     DOI: 10.1021/ci300302c

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  6 in total

1.  Free energy calculation provides insight into the action mechanism of selective PARP-1 inhibitor.

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Journal:  J Mol Model       Date:  2016-03-12       Impact factor: 1.810

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Journal:  Methods Mol Biol       Date:  2021

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Journal:  Naunyn Schmiedebergs Arch Pharmacol       Date:  2021-02-23       Impact factor: 3.000

4.  Identification of novel potential antibiotics against Staphylococcus using structure-based drug screening targeting dihydrofolate reductase.

Authors:  Maiko Kobayashi; Tomohiro Kinjo; Yuji Koseki; Christina R Bourne; William W Barrow; Shunsuke Aoki
Journal:  J Chem Inf Model       Date:  2014-04-02       Impact factor: 4.956

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Review 6.  Hierarchical virtual screening approaches in small molecule drug discovery.

Authors:  Ashutosh Kumar; Kam Y J Zhang
Journal:  Methods       Date:  2014-07-27       Impact factor: 3.608

  6 in total

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