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Classification of Protein Kinases Influenced by Conservation of Substrate Binding Residues

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Data Mining Techniques for the Life Sciences

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1415))

Abstract

With the advent of genome sequencing projects in the recent past, several kinases have come to light as regulating different signaling pathways. These kinases are generally classified into different subfamilies based on their sequence similarity with members of known subfamilies of kinases. A functional association is then defined to the kinase based on the subfamily to which it has been characterized. However, one of the key factors that give identity to a kinase in a subfamily is its ability to phosphorylate a given set of substrates. Substrate specificity of a kinase is largely determined by the residues at the substrate binding site. Though in general the sequence similarity based measure for classification more or less gives the preliminary idea on subfamily, understanding the molecular basis of kinase substrate recognition could further refine the classification scheme for kinases and render a better understanding of their functional role. In this analysis we emphasize on the possibility of using putative substrate binding information in the classification of a given kinase into a particular subfamily.

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References

  1. Manning G, Whyte DB, Martinez R et al (2002) The protein kinase complement of the human genome. Science 298:1912–1934. doi:10.1126/science.1075762

    Article  CAS  PubMed  Google Scholar 

  2. Martin J, Anamika K, Srinivasan N (2010) Classification of protein kinases on the basis of both kinase and non-kinase regions. PLoS ONE 5, e12460. doi:10.1371/journal.pone.0012460

    Article  PubMed  PubMed Central  Google Scholar 

  3. Krupa A, Srinivasan N (2002) The repertoire of protein kinases encoded in the draft version of the human genome: atypical variations and uncommon domain combinations. Genome Biol 3:research0066.1–research0066.14

    Google Scholar 

  4. Taylor SS, Radzio-Andzelm E (1994) Three protein kinase structures define a common motif. Structure 2:345–355

    Article  CAS  PubMed  Google Scholar 

  5. Hanks SK, Hunter T (1995) Protein kinases 6. The eukaryotic protein kinase superfamily: kinase (catalytic) domain structure and classification. FASEB J 9:576–596

    CAS  PubMed  Google Scholar 

  6. Krupa A, Abhinandan KR, Srinivasan N (2004) KinG: a database of protein kinases in genomes. Nucleic Acids Res 32:D153–D155. doi:10.1093/nar/gkh019

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Eddy SR (2011) Accelerated profile HMM searches. PLoS Comput Biol 7, e1002195. doi:10.1371/journal.pcbi.1002195

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Altschul SF, Madden TL, Schäffer AA et al (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25:3389–3402

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Deshmukh K, Anamika K, Srinivasan N (2010) Evolution of domain combinations in protein kinases and its implications for functional diversity. Prog Biophys Mol Biol 102:1–15. doi:10.1016/j.pbiomolbio.2009.12.009

    Article  CAS  PubMed  Google Scholar 

  10. Bhaskara RM, Mehrotra P, Rakshambikai R et al (2014) The relationship between classification of multi-domain proteins using an alignment-free approach and their functions: a case study with immunoglobulins. Mol Biosyst 10:1082–1093. doi:10.1039/c3mb70443b

    Article  CAS  PubMed  Google Scholar 

  11. Rakshambikai R, Manoharan M, Gnanavel M, Srinivasan N (2015) Typical and atypical domain combinations in human protein kinases: functions, disease causing mutations and conservation in other primates. RSC Adv 5:25132–25148. doi:10.1039/C4RA11685B

    Article  CAS  Google Scholar 

  12. Malumbres M, Harlow E, Hunt T et al (2009) Cyclin-dependent kinases: a family portrait. Nat Cell Biol 11:1275–1276. doi:10.1038/ncb1109-1275

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Pei J, Grishin NV (2014) PROMALS3D: multiple protein sequence alignment enhanced with evolutionary and three-dimensional structural information. Methods Mol Biol 1079:263–271. doi:10.1007/978-1-62703-646-7_17

    Article  PubMed  PubMed Central  Google Scholar 

  14. Fox NK, Brenner SE, Chandonia JM (2014) SCOPe: structural classification of proteins—extended, integrating SCOP and ASTRAL data and classification of new structures. Nucleic Acids Res 42:D304–D309. doi:10.1093/nar/gkt1240

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Zhu J, Weng Z (2005) FAST: a novel protein structure alignment algorithm. Proteins 58:618–627. doi:10.1002/prot.20331

    Article  CAS  PubMed  Google Scholar 

  16. Zhang Y, Skolnick J (2005) TM-align: a protein structure alignment algorithm based on the TM-score. Nucleic Acids Res 33:2302–2309. doi:10.1093/nar/gki524

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Das AA, Sharma OP, Kumar MS et al (2013) PepBind: a comprehensive database and computational tool for analysis of protein-peptide interactions. Genomics Proteomics Bioinformatics 11:241–246. doi:10.1016/j.gpb.2013.03.002

    Article  PubMed  PubMed Central  Google Scholar 

  18. Ubersax JA, Ferrell JE (2007) Mechanisms of specificity in protein phosphorylation. Nat Rev Mol Cell Biol 8:530–541. doi:10.1038/nrm2203

    Article  CAS  PubMed  Google Scholar 

  19. Altschul SF, Gish W, Miller W et al (1990) Basic local alignment search tool. J Mol Biol 215:403–410. doi:10.1016/S0022-2836(05)80360-2

    Article  CAS  PubMed  Google Scholar 

  20. Bairoch A, Apweiler R (1998) The SWISS-PROT protein sequence data bank and its supplement TrEMBL in 1998. Nucleic Acids Res 26:38–42

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Thompson JD, Higgins DG, Gibson TJ (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 22:4673–4680

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Manning G (2005) Genomic overview of protein kinases. WormBook 13:1–19. doi:10.1895/wormbook.1.60.1

    Google Scholar 

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Acknowledgments

This research is supported by Department of Biotechnology, Government of India as well as by the Mathematical Biology initiative sponsored by Department of Science and Technology, Government of India. MM is supported by Kothari fellowship, University Grants Commission. NS is a J C Bose National Fellow. CJ gratefully acknowledges the support provided by her research supervisor at C-DAC, Dr Sarat Chandra Babu, in carrying out her research work.

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Correspondence to Narayanaswamy Srinivasan .

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Janaki, C., Srinivasan, N., Manoharan, M. (2016). Classification of Protein Kinases Influenced by Conservation of Substrate Binding Residues. In: Carugo, O., Eisenhaber, F. (eds) Data Mining Techniques for the Life Sciences. Methods in Molecular Biology, vol 1415. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3572-7_15

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  • DOI: https://doi.org/10.1007/978-1-4939-3572-7_15

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-3570-3

  • Online ISBN: 978-1-4939-3572-7

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