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

被引:90
作者
Zhou, Peng [1 ]
Wang, Congcong [1 ]
Tian, Feifei [2 ]
Ren, Yanrong [3 ]
Yang, Chao [1 ]
Huang, Jian [1 ]
机构
[1] Univ Elect Sci & Technol China, Sch Life Sci & Technol, Ctr Bioinformat COBI, Chengdu 610054, Peoples R China
[2] SW Jiaotong Univ, Sch Life Sci & Engn, Chengdu 610031, Peoples R China
[3] Chongqing Univ Educ, Dept Biol & Chem Engn, Chongqing 400067, Peoples R China
基金
中国国家自然科学基金;
关键词
Biomacromolecular quantitative structure-activity relationship; Protein-protein interaction; Regression modeling; Affinity prediction; GAUSSIAN PROCESS; HYDROGEN-BONDS; FORCE-FIELD; MEAN FORCE; HOT-SPOTS; QSAR; PEPTIDE; FLEXIBILITY; STABILITY; PROFILE;
D O I
10.1007/s10822-012-9625-3
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
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.
引用
收藏
页码:67 / 78
页数:12
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