標題: Moiety-Linkage Map Reveals Selective Nonbisphosphonate Inhibitors of Human Geranylgeranyl Diphosphate Synthase
作者: Chen, Shih-Hsun
Lin, Sheng-Wei
Lin, Shen-Rong
Liang, Po-Huang
Yang, Jinn-Moon
生物科技學系
生物資訊及系統生物研究所
Department of Biological Science and Technology
Institude of Bioinformatics and Systems Biology
公開日期: 1-Sep-2013
摘要: Bisphosphonates are potent inhibitors of farnesyl pyrophosphate synthase (FPPS) and geranylgeranyl diphosphate synthase (GGPPS). Current bisphosphonate drugs (e.g., Fosamax and Zometa) are highly efficacious in the treatment of bone diseases such as osteoporosis, Paget's disease, and tumor-induced osteolysis, but they are often less potent in blood and soft-tissue due to their phosphate moieties. The discovery of nonbisphosphonate inhibitors of FPPS and/or GGPPS for the treatment of bone diseases and cancers is, therefore, a current goal. Here, we propose a moiety-linkage-based method, combining a site-moiety map with chemical structure rules. (CSRs), to discover nonbisphosphonate inhibitors from thousands of commercially available compounds and known crystal structures. Our moiety-linkage map reveals the binding mechanisms and inhibitory efficacies of 51 human GGPPS (hGGPPS) inhibitors. To the best of our knowledge, we are the first team to discover two novel selective nonbisphosphonate inhibitors, which bind to the inhibitory site of hGGPPS, using CSRs and site-moiety maps. These two compounds can be considered as a novel lead for the potent inhibitors of hGGPPS for the treatment of cancers and mevalonate-pathway diseases. Moreover, based on our moiety-linkage map, we identified two key residues of hGGPPS, K202, and K212, which play an important role for the inhibitory effect of zoledronate (IC50 = 3.4 mu M and 2.4 mu M, respectively). This result suggests that our method can discover specific hGGPPS inhibitors across multiple prenyltransferases. These results show that the compounds that highly fit our moiety-linkage map often inhibit hGGPPS activity and induce tumor cell apoptosis. We believe that our method is useful for discovering potential inhibitors and binding mechanisms for pharmaceutical targets.
URI: http://dx.doi.org/10.1021/ci400227r
http://hdl.handle.net/11536/23557
ISSN: 1549-9596
DOI: 10.1021/ci400227r
期刊: JOURNAL OF CHEMICAL INFORMATION AND MODELING
Volume: 53
Issue: 9
起始頁: 2299
結束頁: 2311
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