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In-silico screening of cancer associated mutation on PLK1 protein and its structural consequences

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Abstract

The Polo-like kinases (Plks) are a conserved subfamily of serine-threonine protein kinases that have significant roles in cell proliferation. The serine/threonine protein kinases or polo-like kinase 1 (PLK1) exist in centrosome during interphase and is an important regulatory enzyme in cell cycle progression during M phase. Mutations in mammalian PLK1 were found to be over expressed in various human cancers and it is disrupting the binding ability of polo box domain with target peptide. In this analysis we implemented a computational approach to filter the most deleterious and cancer associated mutation on PLK1 protein. We found W414F as the most deleterious and cancer associated by Polyphen 2.0, SIFT, I-mutant 3.0, PANTHER, PhD-SNP, SNP&GO, Mutpred and Dr Cancer tools. Molecular docking and molecular dynamics simulation (MDS) approach was used to investigate the structural and functional behavior of PLK1 protein upon mutation. MDS and docking results showed stability loss in mutant PLK1 protein. Due to mutation, PLK1 protein became more flexible and alters the dynamic property of protein which might affect the interaction with target peptide and leads to cell proliferation. Our study provided a well designed computational methodology to examine the cancer associated nsSNPs and their molecular mechanism. It further helps scientists to develop a drug therapy against PLK1 cancer-associated diseases.

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References

  1. Barr FA, Sillje HH, Nigg EA (2004) Polo-like kinases and the orchestration of cell division. Nat Rev Mol Cell Biol 5:429–440

    Article  CAS  Google Scholar 

  2. Van de Weerdt BC, Medema RH (2006) Polo-like kinases: a team in control of the division. Cell Cycle 5:853–864

    Article  Google Scholar 

  3. Eckerdt F, Yuan J, Strebhardt K (2005) Polo-like kinases and oncogenesis. Oncogene 24:267–276

    Article  CAS  Google Scholar 

  4. Strebhardt K, Ullrich A (2006) Targeting polo-like kinase 1 for cancer therapy. Nat Rev Cancer 6:321–330

    Article  CAS  Google Scholar 

  5. Lee KS, Grenfell TZ, Yarm FR, Erikson RL (1998) Mutation of the polo-box disrupts localization and mitotic functions of the mammalian polo kinase plk. Proc Natl Acad Sci U S A 95:9301–9306

    Article  CAS  Google Scholar 

  6. Nigg EA (1998) Polo-like kinases: positive regulators of cell division from start to finish. Curr Opin Cell Biol 10:776–783

    Article  CAS  Google Scholar 

  7. Glover DM, Ohkura H, Tavares A (1996) Polo kinase: the choreographer of mitotic stage. J Cell Biol 135:1681–1684

    Article  CAS  Google Scholar 

  8. Lane H, Nigg EA (1997) Cell-cycle control: POLO-like kinases join the outer circle. Trends Cell Biol 7:63–68

    Article  CAS  Google Scholar 

  9. Llamazares S, Moreira A, Tavares A et al (1991) Polo encodes a protein kinase homolog required for mitosis in Drosophila. Genes Dev 5:2153–2165

    Article  CAS  Google Scholar 

  10. Ohkura H, Hagan IM, Glover DM (1995) The conserved chizosaccharomyces pombe kinase plo1, required to form a bipolar spindle, the actin ring, and septum, can drive septum formation in G1 and G2 cells. Genes Dev 9:1059–1073

    Article  CAS  Google Scholar 

  11. Lane HA, Nigg EA (1996) Antibody microinjection reveals an essential role for human polo-like kinase 1 (Plk1) in the functional maturation of mitotic centrosomes. J Cell Biol 135:1701–1713

    Article  CAS  Google Scholar 

  12. Kumagai A, Dunphy WG (1996) Purification and molecular cloning of Plx1, a Cdc25-regulatory kinase from Xenopus egg extracts. Science 273:1377–1380

    Article  CAS  Google Scholar 

  13. Toczyski DP, Galgoczy DJ, Hartwell LH (1997) CDC5 and CKII control adaptation to the yeast DNA damage checkpoint. Cell 90:1097–1106

    Article  CAS  Google Scholar 

  14. Shirayama M, Zachariae W, Ciosk R (1998) The Polo-like kinase Cdc5p and the WD-repeat protein Cdc20p/fizzy are regulators and substrates of the anaphase promoting complex in Saccharomyces cerevisiae. EMBO J 17:1336–1349

    Article  CAS  Google Scholar 

  15. Descombes P, Nigg EA (1998) The polo-like kinase Plx1 is required for M phase exit and destruction of mitotic regulators inXenopus egg extracts. EMBO J 17:1328–1335

    Article  CAS  Google Scholar 

  16. Lee KS, Erikson RL (1997) Plk is a functional homolog of Saccharomyces cerevisiae Cdc5, and elevated Plk. Mol Cell Biol 17(6):3408-3417.

    Google Scholar 

  17. Seong YS, Kamijo K, Lee JS et al (2002) A spindle checkpoint arrest and a cytokinesis failure by the dominant-negative polo-box domain of Plk1 in U-2 OS cells. J Biol Chem 277:32282–32293

    Article  CAS  Google Scholar 

  18. Song S, Grenfell TZ, Garfield S et al (2000) Essential function of the polo box of Cdc5 in subcellular localization and induction of cytokinetic structures. Mol Cell Biol 20:286–298

    Article  CAS  Google Scholar 

  19. Liu J, Lewellyn AL, Chen LG, Maller JL (2004) The polo box is required for multiple functions of Plx1 in mitosis. J Biol Chem 279:21367–21373

    Article  CAS  Google Scholar 

  20. Jeong K, Jeong JY, Lee HO (2010) Inhibition of Plk1 induces mitotic infidelity and embryonic growth defects in developing zebrafish embryos. Dev Biol 345:34–48

    Article  CAS  Google Scholar 

  21. García-Alvarez B, de Cárcer G, Ibañez S et al (2007) Molecular and structural basis of polo-like kinase 1 substrate recognition: implications in centrosomal localization. Proc Natl Acad Sci U S A 104:3107–3112

    Article  Google Scholar 

  22. Yun SM, Moulaei T, Lim D et al (2009) Structural and functional analyses of minimal phosphopeptides targeting the polo-box domain of polo-like kinase 1. Nat Struct Mol Biol 16:876–882

    Article  CAS  Google Scholar 

  23. Strebhardt K (2001) In: Creighton TE (ed) PLK (Polo-like kinase): encyclopedia of molecular medicine. Wiley, New York, pp 2530–2532

    Google Scholar 

  24. Balu K, Purohit R (2013) Mutational analysis of TYR gene and its structural consequences in OCA1A. Gene 513:184–195

    Article  Google Scholar 

  25. Kamaraj B, Purohit R (2013) In silico screening and molecular dynamics simulation of disease-associated nsSNP in TYRP1 gene and its structural consequences in OCA3. BioMed Res Int. doi:10.1155/2013/697051

    Google Scholar 

  26. Kamaraj B, Purohit R (2013) Computational screening of disease-associated mutations in oca2 gene. Cell Biochem Biophys. doi:10.1007/s12013-013-9697-2

    Google Scholar 

  27. Kumar A, Rajendran V, Sethumadhavan R et al (2013) Evidence of colorectal cancer-associated mutation in MCAK: a computational report. Cell Biochem Biophys. doi:10.1007/s12013-013-9572-1

    Google Scholar 

  28. Kumar A, Rajendran V, Sethumadhavan R et al (2013) Roadmap to determine the point mutations involved in cardiomyopathy disorder: a Bayesian approach. Gene 519:34–40

    Article  CAS  Google Scholar 

  29. Adzhubei IA, Schmidt S, Peshkin L et al (2010) A method and server for predicting damaging missense mutations. Nat Methods 7:248–249

    Article  CAS  Google Scholar 

  30. Kumar P, Henikoff S, Ng PC (2009) Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc 4:1073–1081

    Article  CAS  Google Scholar 

  31. Capriotti E, Fariselli P, Rossi I, Casadio R (2008) A three-state prediction of single point mutations on protein stability changes. BMC Bioinforma 9S6

  32. Thomas PD, Campbell MJ, Kejariwal A et al (2003) PANTHER: a library of protein families and subfamilies indexed by function. Genome Res 13:2129–2141

    Article  CAS  Google Scholar 

  33. Capriotti E, Calabrese R, Casadio R (2006) Predicting the insurgence of human genetic diseases associated to single point protein mutations with support vector machines and evolutionary information. Bioinformatics 22:2729–2734

    Article  CAS  Google Scholar 

  34. Calabrese R, Capriotti E, Fariselli P et al (2009) Functional annotations improve the predictive score of human disease-related mutations in proteins. Hum Mutat 30:1237–1244

    Article  CAS  Google Scholar 

  35. Li B, Krishnan VG, Mort ME et al (2009) Automated inference of molecular mechanisms of disease from amino acid substitutions. Bioinformatics 25:2744–2750

    Article  CAS  Google Scholar 

  36. Capriotti E, Altman RB (2011) A new disease-specific machine learning approach for the prediction of cancer-causing missense variants. Genomics 98:310–317

    Article  CAS  Google Scholar 

  37. Purohit R, Rajendran V, Sethumadhavan R (2011) Relationship between mutation of serine residue at 315th position in M. tuberculosis catalase-peroxidase enzyme and isoniazid susceptibility: an in silico analysis. J Mol Model 17:869–877

    Article  CAS  Google Scholar 

  38. Purohit R, Rajendran V, Sethumadhavan R (2011) Studies on adaptability of binding residues and flap region of TMC-114 resistance HIV-1 protease mutants. J Biomol Struct Dyn 29:137–152

    Article  CAS  Google Scholar 

  39. Rajendran V, Sethumadhavan R (2013) Drug resistance mechanism of PncA in Mycobacterium tuberculosis. J Biomol Struct Dyn. doi:10.1080/07391102.2012.759885

    Google Scholar 

  40. Rajendran V, Purohit R, Sethumadhavan R (2012) In silico investigation of molecular mechanism of laminopathy cause by a pointmutation (R482W) in lamin A/C protein. Amino Acids 43:603–615

    Article  CAS  Google Scholar 

  41. Purohit R (2013) Role of ELA region in auto-activation of mutant KIT receptor; a molecular dynamics simulation insight. J Biomol Struct Dyn. doi:10.1080/07391102.2013.803264

  42. Balu K, Rajendran V, Sethumadhavan R et al (2013) Investigation of binding phenomenon of NSP3 and p130Cas mutants and their effect on cell signalling. Cell Biochem Biophys: 1–11

  43. Yip YL, Scheib H, Diemand AV et al (2004) The Swiss-Prot variant page and the ModSNP database: a resource for sequence and structure information on human protein variants. Hum Mutat 23:464–470

    Article  CAS  Google Scholar 

  44. Yip YL, Famiglietti M, Gos A et al (2008) Annotating single amino acid polymorphisms in the UniProt/Swiss-Prot knowledgebase. Hum Mutat 29:361–366

    Article  CAS  Google Scholar 

  45. Boeckmann B, Bairoch A, Apweiler R et al (2003) The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003. Nucleic Acids Res 31:365–370

    Article  CAS  Google Scholar 

  46. Berman HM, Westbrook J, Feng Z et al (2000) The protein data bank. Nucleic Acids Res 28:235–242

    Article  CAS  Google Scholar 

  47. Kaplan W, Littlejohn TG (2001) Swiss-PDB viewer (deep view). Brief Bioinform 2:195–197

    Article  CAS  Google Scholar 

  48. Hess B, Kutzner C, Spoel DVD, Lindahl E. GROMACS 4: algorithms for highly efficient, load-balanced, and scalable molecular simulation. J Chem Theory Comput 4:435–447

  49. Gallivan JP, Dougherty DA (1999) Cation-pi interactions in structural biology. Proc Natl Acad Sci U S A 96:9459–9464

    Article  CAS  Google Scholar 

  50. Magyar C, Gromiha MM, Pujadas G et al (2005) SRide: a server for identifying stabilizing residues in proteins. Nucleic Acids Res 33:W303–W305

    Article  CAS  Google Scholar 

  51. Berendsen HJC, Postma JPM, van Gunsteren WF et al (1984) Molecular dynamics with coupling to an external bath. J Chem Phys 8:3684–3690

    Article  Google Scholar 

  52. Cheatham TE III, Miller JL, Fox T et al (1995) Molecular dynamics simulations on solvated biomolecular systems: the particle mesh Ewald method leads to stable trajectories of DNA, RNA, and proteins. J Am Chem Soc 117:4193–4194

    Article  CAS  Google Scholar 

  53. Turner PJ (2005) XMGRACE, version 5.1.19. Center for Coastal and Land-Margin Research, Oregon Graduate Institute of Science and Technology, Beaverton

    Google Scholar 

  54. Amadei A, Linssen AB, Berendsen HJ (1993) Essential dynamics of proteins. Proteins 17:412–425

    Article  CAS  Google Scholar 

  55. Duhovny D, Nussinov R, Wolfson HJ (2002) Efficient unbound docking of rigid molecules. In Gusfield et al. (ed) Proceedings of the 2’nd Workshop on Algorithms in Bioinformatics(WABI) Rome, Italy, lecture notes in computer science 2452. Springer Verlag, pp 185–200

  56. Schneidman-Duhovny D, Inbar Y, Nussinov R, Wolfson HJ (2005) PatchDock and SymmDock: servers for rigid and symmetric docking. Nucleic Acids Res 33:W363–W367

    Article  CAS  Google Scholar 

  57. Andrusier N, Nussinov R, Wolfson HJ (2007) FireDock: fast interaction refinement in molecular docking. Proteins 69(1):139–159

    Article  CAS  Google Scholar 

  58. Mashiach E, Schneidman-Duhovny D, Andrusier N et al (2008) FireDock: a web server for fast interaction refinement in molecular docking. Nucleic Acids Res 36:W229–W232

    Article  CAS  Google Scholar 

  59. Verma D, Jacobs DJ, Livesay DR (2012) Changes in lysozyme flexibility upon mutation are frequent, large and long-ranged. PLoS Comput Biol 8:e1002409

    Article  CAS  Google Scholar 

  60. Ribeiro AA, de Alencastro RB (2013) Mixed Monte Carlo/molecular dynamics simulations of the prion protein. J Mol Graph Model 42:1–6

    Article  CAS  Google Scholar 

  61. Kabsch W, Sander C (1983) Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 22:2577–2637

    Article  CAS  Google Scholar 

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Acknowledgments

Authors gratefully acknowledge the management of Vellore Institute of Technology for providing the facilities to carry out this work.

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Authors and Affiliations

  1. School of Bio Sciences and Technology (SBST), Bioinformatics Division, Vellore Institute of Technology University, Vellore, 632014, Tamil Nadu, India

    Balu Kamaraj, Vidya Rajendran, Rao Sethumadhavan & Rituraj Purohit

  2. Human Genetics Foundation, Torino, Via Nizza 52, 10126, Torino, Italy

    Rituraj Purohit

Authors
  1. Balu Kamaraj
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  2. Vidya Rajendran
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  3. Rao Sethumadhavan
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  4. Rituraj Purohit
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Correspondence to Rituraj Purohit.

Additional information

Balu Kamaraj and Vidya Rajendran equally contributed to this paper.

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Kamaraj, B., Rajendran, V., Sethumadhavan, R. et al. In-silico screening of cancer associated mutation on PLK1 protein and its structural consequences. J Mol Model 19, 5587–5599 (2013). https://doi.org/10.1007/s00894-013-2044-0

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  • DOI: https://doi.org/10.1007/s00894-013-2044-0

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