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学科主题: 药学
题名:
Multiple-Docking and Affinity Fingerprint Methods for Protein Classification and Inhibitors Selection
作者: Li, Bo3; Liu, Zhenming1,2; Zhang, Liangren1; Zhang, Lihe1
刊名: JOURNAL OF CHEMICAL INFORMATION AND MODELING
发表日期: 2009-07-01
DOI: 10.1021/ci900044j
卷: 49, 期:7, 页:1725-1733
收录类别: SCI
文章类型: Article
WOS标题词: Science & Technology
类目[WOS]: Chemistry, Medicinal ; Chemistry, Multidisciplinary ; Computer Science, Information Systems ; Computer Science, Interdisciplinary Applications
研究领域[WOS]: Pharmacology & Pharmacy ; Chemistry ; Computer Science
关键词[WOS]: SECRETORY PHOSPHOLIPASE A(2) ; RHEUMATOID-ARTHRITIS ; INDOLE INHIBITORS ; DRUG DISCOVERY ; INDOLE-3-ACETAMIDES ; COMBINATION ; DISEASE ; SEARCH
英文摘要:

The function-based protein classification holds tremendous promise for molecular recognition and the structure-based design process. We describe here a new strategy combined with multiple-docking tools and "affinity fingerprint" analysis technology to detect functional relationships among proteins based on the substrate binding features and protein - ligand interaction matrix and apply it successfully for the family of phospholipase A2 to investigate protein-ligand binding, function-based protein classification, and inhibitor selection, evaluation. Binding data and matrix were generated by multiple versus multiple-docking among 12 PLA2s and 84 PLA2 inhibitors. Three kinds of statistic techniques, principal component analysis, multidimensional scaling, and cluster algorithms, were chosen. to distinguish the groups with similar binding characteristics. The 12 PLA2s were automatically categorized into reasonable subfamilies on the basis of the protein-ligand binding matrix, and the classifying problem of cPLA2 (PDB ID: 1CJY) with relatively low homology was successfully dealt with. This approach was also used to identify and group the selective inhibitors against human nonpancreatic sPLA2. A sound pharmacophore has been defined from these selective inhibitors. It shows that the method is quite robust against individual data deviation, especially false positive, which makes it possible to be used in virtual screening with large enzyme families to generate selective inhibitors of targets on the basis of limited structural/function information.

语种: 英语
WOS记录号: WOS:000268138900012
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.bjmu.edu.cn/handle/400002259/60521
Appears in Collections:北京大学药学院_期刊论文

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作者单位: 1.Peking Univ, State Key Lab Nat & Biomimet Drugs, Sch Pharmaceut Sci, Beijing 100191, Peoples R China
2.Peking Univ, Ctr Hlth, Sch Pharmaceut Sci, Beijing 100191, Peoples R China
3.Peking Univ, State Key Lab Struct Chem Unstable & Stable Speci, Coll Chem & Mol Engn, Beijing 100871, Peoples R China

Recommended Citation:
Li, Bo,Liu, Zhenming,Zhang, Liangren,et al. Multiple-Docking and Affinity Fingerprint Methods for Protein Classification and Inhibitors Selection[J]. JOURNAL OF CHEMICAL INFORMATION AND MODELING,2009,49(7):1725-1733.
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