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In Silico Structural and Functional Annotation of Hypothetical Proteins of Vibrio cholerae O139

  • Islam, Md. Saiful (Department of Genetic Engineering & Biotechnology, Faculty of Biological Sciences, University of Chittagong) ;
  • Shahik, Shah Md. (Department of Genetic Engineering & Biotechnology, Faculty of Biological Sciences, University of Chittagong) ;
  • Sohel, Md. (Department of Genetic Engineering & Biotechnology, Faculty of Biological Sciences, University of Chittagong) ;
  • Patwary, Noman I.A. (Department of Genetic Engineering & Biotechnology, Faculty of Biological Sciences, University of Chittagong) ;
  • Hasan, Md. Anayet (Department of Genetic Engineering & Biotechnology, Faculty of Biological Sciences, University of Chittagong)
  • Received : 2015.02.14
  • Accepted : 2015.05.27
  • Published : 2015.06.30

Abstract

In developing countries threat of cholera is a significant health concern whenever water purification and sewage disposal systems are inadequate. Vibrio cholerae is one of the responsible bacteria involved in cholera disease. The complete genome sequence of V. cholerae deciphers the presence of various genes and hypothetical proteins whose function are not yet understood. Hence analyzing and annotating the structure and function of hypothetical proteins is important for understanding the V. cholerae. V. cholerae O139 is the most common and pathogenic bacterial strain among various V. cholerae strains. In this study sequence of six hypothetical proteins of V. cholerae O139 has been annotated from NCBI. Various computational tools and databases have been used to determine domain family, protein-protein interaction, solubility of protein, ligand binding sites etc. The three dimensional structure of two proteins were modeled and their ligand binding sites were identified. We have found domains and families of only one protein. The analysis revealed that these proteins might have antibiotic resistance activity, DNA breaking-rejoining activity, integrase enzyme activity, restriction endonuclease, etc. Structural prediction of these proteins and detection of binding sites from this study would indicate a potential target aiding docking studies for therapeutic designing against cholera.

Keywords

References

  1. Reidl J, Klose KE. Vibrio cholerae and cholera: out of the water and into the host. FEMS Microbiol Rev 2002;26:125-139. https://doi.org/10.1111/j.1574-6976.2002.tb00605.x
  2. Finkelstein RA. Cholera, Vibrio cholerae O1 and O139, and other pathogenic Vibrios. In: Medical Microbiology (Baron S, ed.). 4th ed. Galveston: University of Texas Medical Branch at Galveston, 1996. pp. 158-67.
  3. Shanan S, Abd H, Hedenstrom I, Saeed A, Sandstrom G. Detection of Vibrio cholerae and Acanthamoeba species from same natural water samples collected from different cholera endemic areas in Sudan. BMC Res Notes 2011;4:109. https://doi.org/10.1186/1756-0500-4-109
  4. Siddique AK, Baqui AH, Eusof A, Haider K, Hossain MA, Bashir I, et al. Survival of classic cholera in Bangladesh. Lancet 1991;337:1125-1127. https://doi.org/10.1016/0140-6736(91)92789-5
  5. Alam AN, Alam NH, Ahmed T, Sack DA. Randomised double blind trial of single dose doxycycline for treating cholera in adults. BMJ 1990;300:1619-1621. https://doi.org/10.1136/bmj.300.6740.1619
  6. Large epidemic of cholera-like disease in Bangladesh caused by Vibrio cholerae O139 synonym Bengal. Cholera Working Group, International Centre for Diarrhoeal Diseases Research, Bangladesh. Lancet 1993;342:387-390. https://doi.org/10.1016/0140-6736(93)92811-7
  7. Krishna BV, Patil AB, Chandrasekhar MR. Fluoroquinoloneresistant Vibrio cholerae isolated during a cholera outbreak in India. Trans R Soc Trop Med Hyg 2006;100:224-226. https://doi.org/10.1016/j.trstmh.2005.07.007
  8. Roberts RJ. Identifying protein function: a call for community action. PLoS Biol 2004;2:E42. https://doi.org/10.1371/journal.pbio.0020042
  9. Galperin MY, Koonin EV. 'Conserved hypothetical' proteins: prioritization of targets for experimental study. Nucleic Acids Res 2004;32:5452-5463. https://doi.org/10.1093/nar/gkh885
  10. Friedberg I. Automated protein function prediction: the genomic challenge. Brief Bioinform 2006;7:225-242. https://doi.org/10.1093/bib/bbl004
  11. Eisen JA. Phylogenomics: improving functional predictions for uncharacterized genes by evolutionary analysis. Genome Res 1998;8:163-167. https://doi.org/10.1101/gr.8.3.163
  12. Gill SC, von Hippel PH. Calculation of protein extinction coefficients from amino acid sequence data. Anal Biochem 1989;182:319-326. https://doi.org/10.1016/0003-2697(89)90602-7
  13. Guruprasad K, Reddy BV, Pandit MW. Correlation between stability of a protein and its dipeptide composition: a novel approach for predicting in vivo stability of a protein from its primary sequence. Protein Eng 1990;4:155-161. https://doi.org/10.1093/protein/4.2.155
  14. Ikai A. Thermostability and aliphatic index of globular proteins. J Biochem 1980;88:1895-1898.
  15. Kyte J, Doolittle RF. A simple method for displaying the hydropathic character of a protein. J Mol Biol 1982;157:105-132. https://doi.org/10.1016/0022-2836(82)90515-0
  16. Sonnhammer EL, Eddy SR, Durbin R. Pfam: a comprehensive database of protein domain families based on seed alignments. Proteins 1997;28:405-420. https://doi.org/10.1002/(SICI)1097-0134(199707)28:3<405::AID-PROT10>3.0.CO;2-L
  17. Finn RD, Mistry J, Schuster-Bockler B, Griffiths-Jones S, Hollich V, Lassmann T, et al. Pfam: clans, web tools and services. Nucleic Acids Res 2006;34:D247-D251. https://doi.org/10.1093/nar/gkj149
  18. Bru C, Courcelle E, Carrere S, Beausse Y, Dalmar S, Kahn D. The ProDom database of protein domain families: more emphasis on 3D. Nucleic Acids Res 2005;33:D212-D215.
  19. Marchler-Bauer A, Lu S, Anderson JB, Chitsaz F, Derbyshire MK, DeWeese-Scott C, et al. CDD: a Conserved Domain Database for the functional annotation of proteins. Nucleic Acids Res 2011;39:D225-D229. https://doi.org/10.1093/nar/gkq1189
  20. Szklarczyk D, Franceschini A, Kuhn M, Simonovic M, Roth A, Minguez P, et al. The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored. Nucleic Acids Res 2011;39:D561-D568. https://doi.org/10.1093/nar/gkq973
  21. Ceroni A, Passerini A, Vullo A, Frasconi P. DISULFIND: a disulfide bonding state and cysteine connectivity prediction server. Nucleic Acids Res 2006;34:W177-W181. https://doi.org/10.1093/nar/gkl266
  22. Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 1997;25:3389-3402. https://doi.org/10.1093/nar/25.17.3389
  23. Schaffer AA, Aravind L, Madden TL, Shavirin S, Spouge JL, Wolf YI, et al. Improving the accuracy of PSI-BLAST protein database searches with composition-based statistics and other refinements. Nucleic Acids Res 2001;29:2994-3005. https://doi.org/10.1093/nar/29.14.2994
  24. Notredame C, Higgins DG, Heringa J. T-Coffee: a novel method for fast and accurate multiple sequence alignment. J Mol Biol 2000;302:205-217. https://doi.org/10.1006/jmbi.2000.4042
  25. Marti-Renom MA, Stuart AC, Fiser A, Sanchez R, Melo F, Sali A. Comparative protein structure modeling of genes and genomes. Annu Rev Biophys Biomol Struct 2000;29:291-325. https://doi.org/10.1146/annurev.biophys.29.1.291
  26. Fiser A, Do RK, Sali A. Modeling of loops in protein structures. Protein Sci 2000;9:1753-1773. https://doi.org/10.1110/ps.9.9.1753
  27. Hasan MA, Alauddin SM, Al Amin M, Nur SM, Mannan A. In silico molecular characterization of cysteine protease YopT from Yersinia pestis by homology modeling and binding site identification. Drug Target Insights 2014;8:1-9.
  28. Chen CC, Hwang JK, Yang JM. (PS)2: protein structure prediction server. Nucleic Acids Res 2006;34:W152-W157. https://doi.org/10.1093/nar/gkl187
  29. Laurie AT, Jackson RM. Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites. Bioinformatics 2005;21:1908-1916. https://doi.org/10.1093/bioinformatics/bti315
  30. Peri S, Navarro JD, Amanchy R, Kristiansen TZ, Jonnalagadda CK, Surendranath V, et al. Development of human protein reference database as an initial platform for approaching systems biology in humans. Genome Res 2003;13:2363-2371. https://doi.org/10.1101/gr.1680803
  31. Hasan A, Mazumder HH, Khan A, Hossain MU, Chowdhury HK. Molecular characterization of legionellosis drug target candidate enzyme phosphoglucosamine mutase from Legionella pneumophila (strain Paris): an in silico approach. Genomics Inform 2014;12:268-275. https://doi.org/10.5808/GI.2014.12.4.268

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