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Computational Systems Biology pp 223–234Cite as

Survey of Computational Approaches for Prediction of DNA-Binding Residues on Protein Surfaces

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 1754))

Abstract

The increasing number of protein structures with uncharacterized function necessitates the development of in silico prediction methods for functional annotations on proteins. In this chapter, different kinds of computational approaches are briefly introduced to predict DNA-binding residues on surface of DNA-binding proteins, and the merits and limitations of these methods are mainly discussed. This chapter focuses on the structure-based approaches and mainly discusses the framework of machine learning methods in application to DNA-binding prediction task.

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References

  1. Luscombe NM, Austin SE, Berman HM, Thornton JM (2000) An overview of the structures of protein-DNA complexes. Genome Biol 1(1):REVIEWS001

    Article  CAS  Google Scholar 

  2. Biswas S, Guharoy M, Chakrabarti P (2009) Dissection, residue conservation, and structural classification of protein-DNA interfaces. Protein Struct Funct Bioinformatics 74(3):643–654

    Article  CAS  Google Scholar 

  3. Ahmad S, Keskin O, Sarai A, Nussinov R (2008) Protein-DNA interactions: structural, thermodynamic and clustering patterns of conserved residues in DNA-binding proteins. Nucleic Acids Res 36(18):5922–5932

    Article  CAS  Google Scholar 

  4. Zhao H, Yang Y, Zhou Y (2010) Structure-based prediction of DNA-binding proteins by structural alignment and a volume-fraction corrected DFIRE-based energy function. Bioinformatics 26(15):1857–1863

    Article  CAS  Google Scholar 

  5. Gao M, Skolnick J (2008) DBD-Hunter: a knowledge-based method for the prediction of DNA-protein interactions. Nucleic Acids Res 36(12):3978–3992

    Article  CAS  Google Scholar 

  6. Jones S, Barker JA, Nobeli I, Thornton JM (2003) Using structural motif templates to identify proteins with DNA binding function. Nucleic Acids Res 31(11):2811–2823

    Article  CAS  Google Scholar 

  7. Gao M, Skolnick J (2009) A threading-based method for the prediction of DNA-binding proteins with application to the human genome. PLoS Comput Biol 5(11):e1000567

    Article  Google Scholar 

  8. Gherardini PF, Helmer-Citterich M (2008) Structure-based function prediction: approaches and applications. Brief Funct Genomic Proteomic 7(4):291–302

    Article  CAS  Google Scholar 

  9. Nimrod G, Szilagyi A, Leslie C, Ben-Tal N (2009) Identification of DNA-binding proteins using structural, electrostatic and evolutionary features. J Mol Biol 387(4):1040–1053

    Article  CAS  Google Scholar 

  10. Ahmad S, Sarai A (2004) Moment-based prediction of DNA-binding proteins. J Mol Biol 341(1):65–71

    Article  CAS  Google Scholar 

  11. Liu B, Wang S, Wang X (2015) DNA binding protein identification by combining pseudo amino acid composition and profile-based protein representation. Sci Rep 5:15479

    Article  CAS  Google Scholar 

  12. Miao Z, Westhof E (2015) A large-scale assessment of nucleic acids binding site prediction programs. PLoS Comput Biol 11(12):e1004639

    Article  Google Scholar 

  13. Gromiha MM, Fukui K (2011) Scoring function based approach for locating binding sites and understanding recognition mechanism of protein-DNA complexes. J Chem Inf Model 51(3):721–729

    Article  CAS  Google Scholar 

  14. Liu R, Hu J (2013) DNABind: a hybrid algorithm for structure-based prediction of DNA-binding residues by combining machine learning- and template-based approaches. Proteins 81(11):1885–1899

    Article  CAS  Google Scholar 

  15. Zen A, de Chiara C, Pastore A, Micheletti C (2009) Using dynamics-based comparisons to predict nucleic acid binding sites in proteins: an application to OB-fold domains. Bioinformatics 25(15):1876–1883

    Article  CAS  Google Scholar 

  16. Gao M, Skolnick J (2009) From nonspecific DNA-protein encounter complexes to the prediction of DNA-protein interactions. PLoS Comput Biol 5(3):e1000341

    Article  Google Scholar 

  17. Maetschke SR, Yuan Z (2009) Exploiting structural and topological information to improve prediction of RNA-protein binding sites. BMC Bioinformatics 10:341

    Article  Google Scholar 

  18. Xiong Y, Xia J, Zhang W, Liu J (2011) Exploiting a reduced set of weighted average features to improve prediction of DNA-binding residues from 3D structures. PLoS One 6(12):e28440

    Article  CAS  Google Scholar 

  19. Zhou J, Xu R, He Y, Lu Q, Wang H, Kong B (2016) PDNAsite: identification of DNA-binding site from protein sequence by incorporating spatial and sequence context. Sci Rep 6:27653

    Article  CAS  Google Scholar 

  20. Yan J, Friedrich S, Kurgan L (2016) A comprehensive comparative review of sequence-based predictors of DNA- and RNA-binding residues. Brief Bioinform 17(1):88–105

    Article  CAS  Google Scholar 

  21. Peng Z, Kurgan L (2015) High-throughput prediction of RNA, DNA and protein binding regions mediated by intrinsic disorder. Nucleic Acids Res 43(18):e121

    Article  Google Scholar 

  22. Si J, Zhang Z, Lin B, Schroeder M, Huang B (2011) MetaDBSite: a meta approach to improve protein DNA-binding sites prediction. BMC Syst Biol 5(Suppl 1):S7

    Article  CAS  Google Scholar 

  23. Wang L, Huang C, Yang MQ, Yang JY (2010) BindN+ for accurate prediction of DNA and RNA-binding residues from protein sequence features. BMC Syst Biol 4(Suppl 1):S3

    Article  Google Scholar 

  24. Cai Y, He Z, Shi X, Kong X, Gu L, Xie L (2010) A novel sequence-based method of predicting protein DNA-binding residues, using a machine learning approach. Mol Cells 30(2):99–105

    Article  CAS  Google Scholar 

  25. JS W, Liu HD, Duan XY, Ding Y, HT W, Bai YF, Sun X (2009) Prediction of DNA-binding residues in proteins from amino acid sequences using a random forest model with a hybrid feature. Bioinformatics 25(1):30–35

    Article  Google Scholar 

  26. Wang L, Yang MQ, Yang JY (2009) Prediction of DNA-binding residues from protein sequence information using random forests. BMC Genomics 10(Suppl 1):S1

    Article  Google Scholar 

  27. Badis G, Berger MF, Philippakis AA, Talukder S, Gehrke AR, Jaeger SA, Chan ET, Metzler G, Vedenko A, Chen X, Kuznetsov H, Wang CF, Coburn D, Newburger DE, Morris Q, Hughes TR, Bulyk ML (2009) Diversity and complexity in DNA recognition by transcription factors. Science 324(5935):1720–1723

    Article  CAS  Google Scholar 

  28. Ofran Y, Mysore V, Rost B (2007) Prediction of DNA-binding residues from sequence. Bioinformatics 23(13):I347–I353

    Article  CAS  Google Scholar 

  29. Hwang S, Gou ZK, Kuznetsov IB (2007) DP-Bind: a Web server for sequence-based prediction of DNA-binding residues in DNA-binding proteins. Bioinformatics 23(5):634–636

    Article  CAS  Google Scholar 

  30. Ho SY, FC Y, Chang CY, Huang HL (2007) Design of accurate predictors for DNA-binding sites in proteins using hybrid SVM-PSSM method. Biosystems 90(1):234–241

    Article  CAS  Google Scholar 

  31. Wang LJ, Brown SJ (2006) BindN: a web-based tool for efficient prediction of DNA and RNA binding sites in amino acid sequences. Nucleic Acids Res 34:W243–W248

    Article  CAS  Google Scholar 

  32. Wang L, Brown SJ (2006) Prediction of DNA-binding residues from sequence features. J Bioinform Comput Biol 4(6):1141–1158

    Article  CAS  Google Scholar 

  33. Ahmad S, Gromiha MM, Sarai A (2004) Analysis and prediction of DNA-binding proteins and their binding residues based on composition, sequence and structural information. Bioinformatics 20(4):477–486

    Article  CAS  Google Scholar 

  34. Yan J, Kurgan L (2017) DRNApred, fast sequence-based method that accurately predicts and discriminates DNA- and RNA-binding residues. Nucleic Acids Res 45(10):e84

    PubMed  PubMed Central  Google Scholar 

  35. Ahmad S, Sarai A (2005) PSSM-based prediction of DNA binding sites in proteins. BMC Bioinformatics 6:33

    Article  Google Scholar 

  36. Zhu X, Ericksen SS, Mitchell JC (2013) DBSI: DNA-binding site identifier. Nucleic Acids Res 41(16):e160

    Article  Google Scholar 

  37. Tsuchiya Y, Kinoshita K, Nakamura H (2004) Structure-based prediction of DNA-binding sites on proteins using the empirical preference of electrostatic potential and the shape of molecular surfaces. Protein Struct Funct Bioinformatics 55(4):885–894

    Article  CAS  Google Scholar 

  38. Chen YC, CY W, Lim C (2007) Predicting DNA-binding amino acid residues from electrostatic stabilization upon mutation to Asp/Glu and evolutionary conservation. Proteins 67(3):671–680

    Article  CAS  Google Scholar 

  39. Bhardwaj N, Lu H (2007) Residue-level prediction of DNA-binding sites and its application on DNA-binding protein predictions. FEBS Lett 581(5):1058–1066

    Article  CAS  Google Scholar 

  40. Zhou W, Yan H (2010) A discriminatory function for prediction of protein-DNA interactions based on alpha shape modeling. Bioinformatics 26(20):2541–2548

    Article  CAS  Google Scholar 

  41. Zhou P, Tian F, Ren Y, Shang Z (2010) Systematic classification and analysis of themes in protein-DNA recognition. J Chem Inf Model 50(8):1476–1488

    Article  CAS  Google Scholar 

  42. Sonavane S, Chakrabarti P (2009) Cavities in protein-DNA and protein-RNA interfaces. Nucleic Acids Res 37(14):4613–4620

    Article  CAS  Google Scholar 

  43. Xiong Y, Liu J, Wei DQ (2011) An accurate feature-based method for identifying DNA-binding residues on protein surfaces. Proteins 79(2):509–517

    Article  CAS  Google Scholar 

  44. Tjong H, Zhou HX (2007) DISPLAR: an accurate method for predicting DNA-binding sites on protein surfaces. Nucleic Acids Res 35(5):1465–1477

    Article  CAS  Google Scholar 

  45. Jones S, Shanahan HP, Berman HM, Thornton JM (2003) Using electrostatic potentials to predict DNA-binding sites on DNA-binding proteins. Nucleic Acids Res 31(24):7189–7198

    Article  CAS  Google Scholar 

  46. Dai H, Xu Q, Xiong Y, Liu WL, Wei DQ (2016) Improved prediction of michaelis constants in CYP450-mediated reactions by resilient back propagation algorithm. Curr Drug Metab 17(7):673–680

    Article  CAS  Google Scholar 

  47. Yao Y, Zhang T, Xiong Y, Li L, Huo J, Wei DQ (2011) Mutation probability of cytochrome P450 based on a genetic algorithm and support vector machine. Biotechnol J 6(11):1367–1376

    Article  CAS  Google Scholar 

  48. Xiong Y, Liu J, Zhang W, Zeng T (2012) Prediction of heme binding residues from protein sequences with integrative sequence profiles. Proteome Sci 10(Suppl 1):S20

    Article  Google Scholar 

  49. Li L, Xiong Y, Zhang ZY, Guo Q, Xu Q, Liow HH, Zhang YH, Wei DQ (2015) Improved feature-based prediction of SNPs in human cytochrome P450 enzymes. Interdiscip Sci Comput Life Sci 7(1):65–77

    Article  CAS  Google Scholar 

  50. Zhang W, Xiong Y, Zhao M, Zou H, Ye X, Liu J (2011) Prediction of conformational B-cell epitopes from 3D structures by random forests with a distance-based feature. BMC Bioinformatics 12:341

    Article  CAS  Google Scholar 

  51. Xu Q, Xiong Y, Dai H, Kumari KM, Xu Q, HY O, Wei DQ (2017) PDC-SGB: prediction of effective drug combinations using a stochastic gradient boosting algorithm. J Theor Biol 417:1–7

    Article  CAS  Google Scholar 

  52. Sun Y, Xiong Y, Xu Q, Wei D (2014) A hadoop-based method to predict potential effective drug combination. Biomed Res Int 2014:196858

    PubMed  PubMed Central  Google Scholar 

  53. Tsuchiya Y, Kinoshita K, Nakamura H (2005) PreDs: a server for predicting dsDNA-binding site on protein molecular surfaces. Bioinformatics 21(8):1721–1723

    Article  CAS  Google Scholar 

  54. Ozbek P, Soner S, Erman B, Haliloglu T (2010) DNABINDPROT: fluctuation-based predictor of DNA-binding residues within a network of interacting residues. Nucleic Acids Res 38(Web Server issue):W417–W423

    Article  CAS  Google Scholar 

  55. Sukumar S, Zhu X, Ericksen SS, Mitchell JC (2016) DBSI server: DNA binding site identifier. Bioinformatics 32(18):2853–2855

    Article  CAS  Google Scholar 

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Acknowledgments

This work was supported by the grants from National Natural Science Foundation of China for Young Scholars (Grant No. 31601074 and 21403002), the funding from National Key Research Program (Contract No. 2016YFA0501703), and the Open Fund of Shanghai Key Laboratory of Intelligent Information Processing (Contract No. IIPL-2016-005).

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Authors and Affiliations

  1. School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China

    Yi Xiong, Xiaolei Zhu, Hao Dai & Dong-Qing Wei

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  1. Yi Xiong
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  2. Xiaolei Zhu
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  3. Hao Dai
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  4. Dong-Qing Wei
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Correspondence to Yi Xiong .

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Editors and Affiliations

  1. Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China

    Tao Huang

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Xiong, Y., Zhu, X., Dai, H., Wei, DQ. (2018). Survey of Computational Approaches for Prediction of DNA-Binding Residues on Protein Surfaces. In: Huang, T. (eds) Computational Systems Biology. Methods in Molecular Biology, vol 1754. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7717-8_13

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  • DOI: https://doi.org/10.1007/978-1-4939-7717-8_13

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7716-1

  • Online ISBN: 978-1-4939-7717-8

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