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Biomacromolecular quantitative structure-activity relationship (BioQSAR): a proof-of-concept study on the modeling, prediction and interpretation of protein-protein binding affinity.

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WOS被引频次:34
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成果类型:
期刊论文
作者:
Peng Zhou;Congcong Wang;Feifei Tian;Yanrong Ren;Chao Yang;Jian Huang
通讯作者:
Zhou, Peng
作者机构:
[Jian Huang; Chao Yang; Congcong Wang; Peng Zhou] Univ Elect Sci & Technol China, Sch Life Sci & Technol, Ctr Bioinformat COBI, Chengdu 610054, Peoples R China.
[Feifei Tian] SW Jiaotong Univ, Sch Life Sci & Engn, Chengdu 610031, Peoples R China.
[Yanrong Ren] Chongqing Univ Educ, Dept Biol & Chem Engn, Chongqing 400067, Peoples R China.
通讯机构:
[Zhou, Peng] Univ Elect Sci & Technol China, Sch Life Sci & Technol, Ctr Bioinformat COBI, Chengdu 610054, Peoples R China.
语种:
英文
关键词:
Biomacromolecular quantitative structure-activity relationship;Protein-protein interaction;Regression modeling;Affinity prediction
期刊:
Journal of computer-aided molecular design
ISSN:
0920-654X
年:
2013
卷:
27
期:
1
页码:
67-78
文献类别:
WOS:Article
所属学科:
ESI学科类别:化学;WOS学科类别:Biochemistry & Molecular Biology;Biophysics;Computer Science, Interdisciplinary Applications
入藏号:
基金类别:
National Natural Science Foundation of China [31200993]; Fundamental Research Funds for the Central Universities [ZYGX2012J111]; Ministry of Education of China [20120185120025]; UESTC
机构署名:
本校为其他机构
院系归属:
生命科学与工程学院
摘要:
Quantitative structure-activity relationship (QSAR), a regression modeling methodology that establishes statistical correlation between structure feature and apparent behavior for a series of congeneric molecules quantitatively, has been widely used to evaluate the activity, toxicity and property of various small-molecule compounds such as drugs, toxicants and surfactants. However, it is surprising to see that such useful technique has only very limited applications to biomacromolecules, albeit the solved 3D atom-resolution structures of proteins, nucleic acids and their complexes have accumulated rapidly in past decades. Here, we present a proof-of-concept paradigm for the modeling, prediction and interpretation of the binding affinity of 144 sequence-nonredundant, structure-available and affinity-known protein complexes (Kastritis et al. Protein Sci 20:482-491, 2011) using a biomacromolecular QSAR (BioQSAR) scheme. We demonstrate that the modeling performance and predictive power of BioQSAR are comparable to or even better than that of traditional knowledge-based strategies, mechanism-type methods and empirical scoring algorithms, while BioQSAR possesses certain additional features compared to the traditional methods, such as adaptability, interpretability, deep-validation and high-efficiency. The BioQSAR scheme could be readily modified to infer the biological behavior and functions of other biomacromolecules, if their X-ray crystal structures, NMR conformation assemblies or computationally modeled structures are available.
参考文献:
Hansch C, Fujita T (1964) ρ-σ-π analysis. A method for correlation of biological activity and chemical structure. J Am Chem Soc 86:1616–1626
Katritzky AR, Lobanov VS, Karelson M (1995) QSPR: the correlation and quantitative prediction of chemical and physical properties from structure. Chem Soc Rev 24:279–287
Siraki AG, Chevaldina T, Moridani MY, O’Brien PJ (2004) Quantitative structure–toxicity relationships by accelerated cytotoxicity mechanism screening. Curr Opin Drug Discov Devel 7:118–125
Mozrzymas A, Rózycka-Roszak B (2010) Prediction of critical micelle concentration of nonionic surfactants by a quantitative structure–property relationship. Comb Chem High Throughput Screen 13:39–44
Fourches D, Pu D, Tassa C, Weissleder R, Shaw SY, Mumper RJ, Tropsha A (2010) Quantitative nanostructure–activity relationship modeling. ACS Nano 4:5703–5712

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