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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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Abstract

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.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 31200993), the Fundamental Research Funds for the Central Universities (No. ZYGX2012J111), the Young Teacher Doctoral Discipline Fund of Ministry of Education of China (No. 20120185120025) and the scientific research funds of UESTC.

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Authors and Affiliations

  1. Center of Bioinformatics (COBI), School of Life Science and Technology, University of Electronic Science and Technology of China (UESTC), Chengdu, 610054, China

    Peng Zhou, Congcong Wang, Chao Yang & Jian Huang

  2. School of Life Science and Engineering, Southwest Jiaotong University, Chengdu, 610031, China

    Feifei Tian

  3. Department of Biological and Chemical Engineering, Chongqing University of Education, Chongqing, 400067, China

    Yanrong Ren

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  1. Peng Zhou
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  2. Congcong Wang
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Correspondence to Peng Zhou or Jian Huang.

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Zhou, P., Wang, C., Tian, F. et al. Biomacromolecular quantitative structure–activity relationship (BioQSAR): a proof-of-concept study on the modeling, prediction and interpretation of protein–protein binding affinity. J Comput Aided Mol Des 27, 67–78 (2013). https://doi.org/10.1007/s10822-012-9625-3

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