國家衛生研究院 NHRI:Item 3990099045/10888
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    题名: In silico-based identification of human alpha-enolase inhibitors to block cancer cell growth metabolically
    作者: Lung, J;Chen, KL;Hung, CH;Chen, CC;Hung, MS;Lin, YC;Wu, CY;Lee, KD;Shih, NY;Tsai, YH
    贡献者: National Institute of Cancer Research
    摘要: Unlimited growth of cancer cells requires an extensive nutrient supply. To meet this demand, cancer cells drastically upregulate glucose uptake and metabolism compared to normal cells. This difference has made the blocking of glycolysis a fascinating strategy to treat this malignant disease, alpha-enolase is not only one of the most upregulated glycolytic enzymes in cancer cells, but also associates with many cellular processes or conditions important to cancer cell survival, such as cell migration, invasion, and hypoxia. Targeting alpha-enolase could simultaneously disturb cancer cells in multiple ways and, therefore, is a good target for anticancer drug development. In the current study, more than 22 million chemical structures meeting the criteria of Lipinski's rule of five from the ZINC database were docked to alpha-enolase by virtual screening. Twenty-four chemical structures with docking scores better than that of the enolase substrate, 2-phosphoglyceratc, were further screened by the absorption, distribution, metabolism, excretion, and toxicity (ADMKT) properties prediction. Four of them were classified as non-mutagenic, non-carcinogenic, and capable of oral administration where they showed steady interactions to alpha-enolase that were comparable, even superior, to the currently available inhibitors in molecular dynamics (MD) simulation. These compounds may be considered promising leads for further development of the alpha-enolase inhibitors and could help fight cancer metabolically.
    日期: 2017-11-16
    關聯: Drug Design Development and Therapy. 2017 Nov 16;11:3281-3290.
    Link to: http://dx.doi.org/10.2147/dddt.s149214
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=1177-8881&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000415381300002
    Cited Times(Scopus): https://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85035193635
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