中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Specificity quantification of biomolecular recognition and its implication for drug discovery

文献类型:期刊论文

作者Yan ZQ ; Wang J
刊名scientific reports
出版日期2012
卷号2页码:文献号: 309
关键词STATISTICAL-MECHANICS MOLECULAR RECOGNITION ENERGY LANDSCAPE MEAN FORCE PROTEIN PREDICTION DOCKING POTENTIALS DESIGN PRINCIPLES
ISSN号2045-2322
通讯作者wang j
中文摘要highly efficient and specific biomolecular recognition requires both affinity and specificity. previous quantitative descriptions of biomolecular recognition were mostly driven by improving the affinity prediction, but lack of quantification of specificity. we developed a novel method spa (specificity and affinity) based on our funneled energy landscape theory. the strategy is to simultaneously optimize the quantified specificity of the "native" protein-ligand complex discriminating against "non-native" binding modes and the affinity prediction. the benchmark testing of spa shows the best performance against 16 other popular scoring functions in industry and academia on both prediction of binding affinity and "native" binding pose. for the target cox-2 of nonsteroidal anti-inflammatory drugs, spa successfully discriminates the drugs from the diversity set, and the selective drugs from non-selective drugs. the remarkable performance demonstrates that spa has significant potential applications in identifying lead compounds for drug discovery.
收录类别SCI收录期刊论文
语种英语
WOS记录号WOS:000301441400001
公开日期2013-10-09
源URL[http://ir.ciac.jl.cn/handle/322003/48844]  
专题长春应用化学研究所_长春应用化学研究所知识产出_期刊论文
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GB/T 7714
Yan ZQ,Wang J. Specificity quantification of biomolecular recognition and its implication for drug discovery[J]. scientific reports,2012,2:文献号: 309.
APA Yan ZQ,&Wang J.(2012).Specificity quantification of biomolecular recognition and its implication for drug discovery.scientific reports,2,文献号: 309.
MLA Yan ZQ,et al."Specificity quantification of biomolecular recognition and its implication for drug discovery".scientific reports 2(2012):文献号: 309.

入库方式: OAI收割

来源:长春应用化学研究所

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