International E-publication: Publish Projects, Dissertation, Theses, Books, Souvenir, Conference Proceeding with ISBN.  International E-Bulletin: Information/News regarding: Academics and Research

Predicting functions of cytochrome c oxidase subunit 1 from Spinycheek crayfish using computational methods

Author Affiliations

  • 1University of Rwanda, College of Science and Technology, Department of Biology, Avenue de l’Armée, Po. Box 3900, Kigali-Rwanda
  • 2University of Rwanda, College of Science and Technology, Department of Biology, Avenue de l’Armée, Po. Box 3900, Kigali-Rwanda
  • 3University of Rwanda, College of Science and Technology, Department of Biology, Avenue de l’Armée, Po. Box 3900, Kigali-Rwanda

Int. Res. J. Biological Sci., Volume 6, Issue (1), Pages 6-14, January,10 (2017)

Abstract

Understanding the cell functioning at molecular level is the goal of most of molecular biology researchers. Molecular biology involves macromolecules which are block of life, on research scene. Among others, proteins have a big range of functions and can only be clear if their structures are available. Assigning functions to all known sequences that are being generated in the public domain by different genomic projects, constitutes a big challenge. It is for that very reason the functions of cytochrome c oxidase subunit 1 from Spinycheek crayfish (Uniprot id: G3GHF6) were predicted using computational methods. Local sequence alignment was conducted to retrieve potential structural homologs having structures determined using experimental methods. Multiple sequence alignment has shown conserved motifs which could be of biological interest. Prediction of three-dimensional structure of cytochrome c oxidase subunit 1 through homology modeling followed by structure assessment and validation using ERRAT and PROCHECK, suggested the predicted model was of acceptable quality. Docking studies using HEX software demonstrated that this protein has affinity with heme ligand with eleven residues involved in these interactions. These interactions are similar to those observed when the heme ligand was docked onto the x-ray structure of the protein used as template for homology modeling exercise. This research shades lights on the function of cytochrome c oxidase subunit 1from Spinycheek crayfish.

References

  1. G. Pandey, V. Kumar, M. Steinbach (2006)., Computational Approaches for Protein Function Prediction: A Survey 2007.,
  2. Rahmah M., Mohd F.M.R., Ahmad T.S., Zulkeflie Z. and Mohd N.E. (2003)., A predicted structure of the cytochrome c oxidase from Burkholderia pseudomallei., Electronic Journal of Biotechnology, 6, 17-28.
  3. S.K.M. Habeeb, K.P. Sanjayan (2011)., Sequencing and phylogenetic analysis of the mitochondrial cytochrome c oxidase subunit i of Oxycarenus laetus (hemiptera: lygaeidae)., Intern, J of Plant, Animal and Envir Sc, 1, 85-92.
  4. J.C. (2000)., A. Phylogeography: The history and formation of species: Cambridge (Massachusetts):, Harvard University Press.
  5. Reza G.M. and Y.P. (2013)., Genetic polymorphisms in cytochrome C oxidase subunit I of the Malaysian population., Annals of Biological Research, 4, 56-60.
  6. M.B.W. (1985)., The mitochondrial genome of animals., R.J. Maclntyre ed. New York: Plenum Press.
  7. Hoeh W., Folmer R.L. and Black M.R.V. (1994)., DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates., Molecular Marine Biology and Biotechnology, 3, 294-296.
  8. L.A. Kelley and M.J.E. Sternberg (2009)., Protein structure prediction on the Web: a case study using the Phyre server., Nature protocols, 4, 363.
  9. Donald P., Markus F. and HB (2009)., Structural relationships among proteins with different global topologies and their implications for function annotation strategies., PNAS, 106, 17377-17382.
  10. Catherine C.H.C., Beng T.T., Jiangning S. and Ramakrishnan N.R. (2014)., Towards more accurate prediction of protein folding rates: a review of the existing web-based bioinformatics approaches., Briefings in Bioinformatics, 1-11.
  11. Caitlyn L.M., Penny J.B. and O M.J. (2015)., Biochemical functional predictions for protein structures of unknown or uncertain function., Comput Struct Biotechnol J, 13, 182-191.
  12. D. Lee, O. Redfern and C. Orengo (2007)., Predicting protein function from sequence and structure., Nature Reviews, Molecular Cell Biology, 8, 995-1005.
  13. S. Oliver (1999)., A network approach to the systematic analysis of yeast gene function., Trends in Genetics, 12, 241-242.
  14. R.J. Roberts (2004)., Identifying protein functional call for community action., PLoS Biology, 2, 293-294.
  15. Teichmann S.A. and G. M. (2000)., Computing protein function., Nature Biotechnology, 18, 27.
  16. Marcotte E.M. (2000)., Computational genetics: finding protein function by nonhomology methods., Curr Opin Struct Biol, 10, 359-365.
  17. Marcotte E.M. (2004)., Practical computational approaches to inferring protein function., Drug Discovery Today, 2, 24-29.
  18. T. Gabaldon and M.A. Huynen (2004)., Prediction of protein function and pathways in the genome era., Cell Mol Life Sci., 61, 930-944.
  19. UniProtConsortium (2014)., UniProt: a hub for protein information., Nucleic acids research.
  20. Krogh A., Larsson B., Von Heijne G. and Sonnhammer E.L.L. (2001)., Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes., J Mol Biol, 305, 567-580.
  21. Altschul S.F., Madden T.L., Schäffer A.A., Zhang J., Zhang Z., Miller W. and L.D. J. (1997)., Gapped BLAST and PSI-BLAST: a new generation of protein database search programs., Nucleic Acids Research, 25, 389-3402.
  22. Sievers F., Wilm A. D.D., Gibson T.J. , Karplus K., Li W., Lopez R., McWilliam H., Remmert M., Söding J., Thompson J.D. and D.G. H. (2011)., Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega., Molecular Systems Biology, 7, 539.
  23. Sahraeian S.M.E., Luo K.R. and SE B. (2015)., SIFTER search: a web server for accurate phylogeny-based protein function prediction., Nucleic Acids Research, 43, W141-W147.
  24. Engelhardt B.E., Jordan M.I., Srouji J.R. and SE B.(2011), Genome-scale phylogenetic function annotation of large and diverse protein families., Genome Research, 21, 1969-1980.
  25. Arnold K., Bordoli L., Kopp J. and T. S. (2006)., The SWISS-MODEL Workspace: A web-based environment for protein structure homology modelling., Bioinformatics, 22, 195-201.
  26. Guex N., Peitsch M.C. and T. S. (2009)., Automated comparative protein structure modeling with SWISS-MODEL and Swiss-PdbViewer: A historical perspective., Electrophoresis, 30, S162-S173.
  27. Colovos C. and Yeates T.O. (1993)., Verification of protein structures: Patterns of nonbonded atomic interactions., Protein Science, 2, 1511-1519.
  28. Fiser A. and A. S. (2003)., ModLoop: automated modeling of loops in protein structures., Bioinformatics, 19, 2500-2501.
  29. Mutangana D., Simurabiye J.B., Uwiringiyimana T. and Rwibasira P. (2016)., Docking Studies of Heme Ligand onto the predicted 3D Structure of Faty Acid Desaturase 2 from rat., Research Journal of Recent Sciences, 5, 30-37.
  30. D.W. Ritchie (2003)., Evaluation of protein docking predictions using Hex 3.1 in CAPRI rounds 1 and Proteins., Proteins: Struct, Funct, Bioinf, 52, 98-106.
  31. DeLano W.L. (2002)., The PyMOL molecular graphics system., Version 1.5.0.4 Schrödinger, LLC. 2002.
  32. Mutangana D. and Ramesh K.V. (2015)., Modeling the interactions between MC2R and ACTH models from human., Journal of Biomolecular Structure and Dynamics, 33, 770-788.
  33. Prabhavathi M., Ashokkumar K., Geetha N. and M. S.D.K. (2011)., Homology modeling and structure prediction of thioredoxin (TRX) protein in wheat., Intl J Biosci, 1, 20-30.
  34. Alberts B., Johnson A., Lewis J., Raff M., Roberts K. and P. W. (2002)., Membrane Proteins., New York: Garland Science.
  35. Mohamed R., Rain M.F.M., Ahmad T.S., Zulkeflie Z. and Mohamed N.E. (2003)., predicted structure of the cytochrome c oxidase from Burkholderia pseudomallei., Electronic Journal of Biotechnology, 6, 17-28.
  36. Ren J.X., Gao N.N., Cao X.S., Hu Q.A. and Xie Y. (2016)., Homology modeling and virtual screening for inhibitors of lipid kinase PI(4)K from Plasmodium., Biomed Pharmacother, 83, 798-808.
  37. Ekins S., Liebler J., Neves B.J., Lewis W.G., Coffee M., Bienstock R., Southan C. and Andrade C.H. (2016)., Illustrating and homology modeling the proteins of the Zika virus., F1000Research, 5, 275.
  38. G.J. Kleywegt and T.A. Jones (1996)., Phi/Psi-chology: Ramachandran revisited., Structure, 4, 1395-1400.
  39. Mohamed R., Mohd F.M.R., Ahmad T.S., Zulkeflie Z. and Mohd N.E. (2003)., A predicted structure of the cytochrome c oxidase from Burkholderia pseudomallei., Journal of Biotechnology, 6, 17-28.
  40. Guo M., Lu X., Wang Y. and Brodelius P.E. (2017)., Comparison of the interaction between lactoferrin and isomeric drugs., Spectrochim Acta A Mol Biomol Spectrosc, 173.
  41. Ma G.H., Ye Y. and Zhang D. et. al. (2016)., Identification and biochemical characterization of DC07090 as a novel potent small molecule inhibitor against human enterovirus 71 3C protease by structure-based virtual screening., Eur J Med Chem, 124, 981-991.
  42. Aprodu I., Ursache F.M., Turturică M., Râpeanu G. and N. S. (2017)., Thermal stability of the complex formed between carotenoids from sea buckthorn (Hippophae rhamnoides L.) and bovine β-lactoglobulin., Spectrochim Acta A Mol Biomol Spectrosc, 173, 562-571.