Literature DB >> 31889491

Identification of Novel Cyclin A2 Binding Site and Nanomolar Inhibitors of Cyclin A2-CDK2 Complex.

Stephanie S Kim1, Michele J Alves2, Patrick Gygli2, Jose Otero2, Steffen Lindert1.   

Abstract

BACKGROUND: Given the diverse roles of cyclin A2 both in cell cycle regulation and in DNA damage response, identifying small molecule regulators of cyclin A2 activity carries significant potential to regulate diverse cellular processes in both ageing/neurodegeneration and in cancer.
OBJECTIVE: Based on cyclin A2's recently discovered role in DNA repair, we hypothesized that small molecule inhibitors that were predicted to bind to both cyclin A2 and CDK2 will be useful as a radiosensitizer of cancer cells. In this study, we used structure-based drug discovery to find inhibitors that target both cyclin A2 and CDK2.
METHODS: Molecular dynamics simulations were used to generate diverse binding pocket conformations for application of the relaxed complex scheme. We then used structure-based virtual screening to find potential dual cyclin A2 and CDK2 inhibitors. Based on a consensus score of docked poses from Glide and AutoDock Vina, we identified about 40 promising hit compounds, where all PAINS scaffolds were removed from consideration. A biochemical luminescence assay of cyclin A2-CDK2 function was used for experimental verification.
RESULTS: Four lead inhibitors of cyclin A2-CDK2 complex have been identified using a relaxed complex scheme virtual screen have been verified in a biochemical luminescence assay of cyclin A2- CDK2 function. Two of the four lead inhibitors had inhibitory concentrations in the nanomolar range.
CONCLUSION: The four cyclin A2-CDK2 complex inhibitors are the first reported inhibitors that were specifically designed not to target the cyclin A2-CDK2 protein-protein interface. Overall, our results highlight the potential of combined advanced computational tools and biochemical verification to discover novel binding scaffolds. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

Entities:  

Keywords:  Cyclin A2; PAINS; computational drug discovery; polypharmacology; structure-based drug discovery; virtual screening

Mesh:

Substances:

Year:  2021        PMID: 31889491      PMCID: PMC7326642          DOI: 10.2174/1573409916666191231113055

Source DB:  PubMed          Journal:  Curr Comput Aided Drug Des        ISSN: 1573-4099            Impact factor:   1.606


  60 in total

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