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Optimizing Scoring Function of Protein-Nucleic Acid Interactions with Both Affinity and Specificity

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  • Zhiqiang Yan
  • Jin Wang

Abstract

Protein-nucleic acid (protein-DNA and protein-RNA) recognition is fundamental to the regulation of gene expression. Determination of the structures of the protein-nucleic acid recognition and insight into their interactions at molecular level are vital to understanding the regulation function. Recently, quantitative computational approach has been becoming an alternative of experimental technique for predicting the structures and interactions of biomolecular recognition. However, the progress of protein-nucleic acid structure prediction, especially protein-RNA, is far behind that of the protein-ligand and protein-protein structure predictions due to the lack of reliable and accurate scoring function for quantifying the protein-nucleic acid interactions. In this work, we developed an accurate scoring function (named as SPA-PN, SPecificity and Affinity of the Protein-Nucleic acid interactions) for protein-nucleic acid interactions by incorporating both the specificity and affinity into the optimization strategy. Specificity and affinity are two requirements of highly efficient and specific biomolecular recognition. Previous quantitative descriptions of the biomolecular interactions considered the affinity, but often ignored the specificity owing to the challenge of specificity quantification. We applied our concept of intrinsic specificity to connect the conventional specificity, which circumvents the challenge of specificity quantification. In addition to the affinity optimization, we incorporated the quantified intrinsic specificity into the optimization strategy of SPA-PN. The testing results and comparisons with other scoring functions validated that SPA-PN performs well on both the prediction of binding affinity and identification of native conformation. In terms of its performance, SPA-PN can be widely used to predict the protein-nucleic acid structures and quantify their interactions.

Suggested Citation

  • Zhiqiang Yan & Jin Wang, 2013. "Optimizing Scoring Function of Protein-Nucleic Acid Interactions with Both Affinity and Specificity," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-8, September.
  • Handle: RePEc:plo:pone00:0074443
    DOI: 10.1371/journal.pone.0074443
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    References listed on IDEAS

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    1. Justin Ashworth & James J. Havranek & Carlos M. Duarte & Django Sussman & Raymond J. Monnat & Barry L. Stoddard & David Baker, 2006. "Computational redesign of endonuclease DNA binding and cleavage specificity," Nature, Nature, vol. 441(7093), pages 656-659, June.
    2. Fyodor D. Urnov & Jeffrey C. Miller & Ya-Li Lee & Christian M. Beausejour & Jeremy M. Rock & Sheldon Augustus & Andrew C. Jamieson & Matthew H. Porteus & Philip D. Gregory & Michael C. Holmes, 2005. "Highly efficient endogenous human gene correction using designed zinc-finger nucleases," Nature, Nature, vol. 435(7042), pages 646-651, June.
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    Cited by:

    1. Jin, Jun & Xu, Fei & Liu, Zhilong & Shuai, Jianwei & Li, Xiang, 2024. "Quantifying the underlying landscape, entropy production and biological path of the cell fate decision between apoptosis and pyroptosis," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    2. Xiliang Zheng & Jin Wang, 2015. "The Universal Statistical Distributions of the Affinity, Equilibrium Constants, Kinetics and Specificity in Biomolecular Recognition," PLOS Computational Biology, Public Library of Science, vol. 11(4), pages 1-24, April.

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