In-Silico Structural Analysis of SoxF Protein Through Molecular Modelling and Protein-Protein Docking from Hydrogenophilus thermoluteolus: An Approach to Understand the Molecular Mechanism of Thiosulfate Oxidation

  • Sujay Ray
  • Angshuman Bagchi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 340)


Microbial redox reactions of inorganic sulphur compounds play vital role for recycling of sulphur to maintain environmental sulphur balance. These important reactions are carried out by enzyme system encoded by sox operon. Central player of sulphur oxidation process is SoxY–Z protein complex. Thermophilic beta-proteobacterium-Hydrogenophilus thermoluteolus, oxidizes sulphur compounds including thiosulfate with the help of proteins encoded by sox operon. Protein SoxF having sulfide dehydrogenase activity has the ability to reactivate the inactivated SoxY–Z complex. Till date no structural details are available for SoxF protein from H. thermoluteolus. In present work, homology modeling has been used to build 3D structures of SoxY, SoxZ and SoxF of H. thermoluteolus. 3D structure of SoxY–Z–F complex was obtained by ClusPro2.0. Amino acid residues responsible for protein-protein interaction were identified. Interactions in SoxY–Z–F were found to be mediated through hydrogen bonding. Probable biophysical mechanism of the interactions of SoxF with SoxY–Z complex has been identified.


Sulphur oxidation Homology modelling Sox operon Protein-protein interaction Molecular docking 



Steepest descend


Conjugate gradient



The authors would like to thank the DST-PURSE programme 2012–2015 going on in the Department of Biochemistry and Biophysics, University of Kalyani for providing different instrumental and infrastructural support. The author is also thankful to the DBT sponsored Bioinformatics Infrastructure Facility in the Department of Biochemistry and Biophysics, University of Kalyani for the necessary support.


  1. 1.
    Freidrich, C.G., Bardischewsky, F., Rother, D., Quentmeier, A., Fischer, J.: Prokaryotic sulfur oxidation. Curr. Opin. Microbiol. 8, 253–259 (2005)CrossRefGoogle Scholar
  2. 2.
    Freidrich, C.G., Rother, D., Bardischewsky, F., Quentmeier, A., Fischer, J.: Oxidation of reduced inorganic sulphur compounds by bacteria: emergence of a common mechanism? Appl. Environ. Microbiol. 67, 2873–2882 (2001)CrossRefGoogle Scholar
  3. 3.
    Bagchi, A.: Structural insight into the mode of interactions of SoxL from Allochromatium vinosum in the global sulfur oxidation cycle. Mol. Biol. Rep. 39, 10243–10248 (2012)CrossRefGoogle Scholar
  4. 4.
    Freidrich, C.G.: Physiology and genetics of sulfur-oxidizing bacteria. Adv. Microb. Physiol. 39, 235–289 (1998)CrossRefGoogle Scholar
  5. 5.
    Ogawa, T., Furusawa, T., Shiga, M., Seo, D., Sakurai, H., Inoue, K.: Biochemical studies of a soxF-encoded monomeric flavoprotein purified from green sulfur bacterium Chlorobium tepidum that stimulates in Vitro thiosulfate oxidation. Biosci. Biotechnol. Biochem. 74, 771–780 (2010)CrossRefGoogle Scholar
  6. 6.
    Sano, R., et al.: Thiosulphate oxidation by a thermo-neutrophilic hydrogen-oxidizing bacterium Hydrogenobacter thermophilus. Biosci. Biotechnol. Biochem. 74, 892–894 (2010)CrossRefGoogle Scholar
  7. 7.
    Miyake, D., et al.: Thiosulfate oxidation by a moderately thermophilic hydrogen oxidizing bacterium, Hydrogenophilus thermoluteolus. Arch. Microbiol. 188, 199–204 (2007)CrossRefGoogle Scholar
  8. 8.
    Berman, M.H., et al.: The protein data bank. Nucleic Acids Res. 28, 235–242 (2000)CrossRefGoogle Scholar
  9. 9.
    Altschul, S.F., et al.: Basic local alignment search tool. J. Mol. Biol. 25, 403–410 (1990)CrossRefGoogle Scholar
  10. 10.
    Arnold, K., Bordoli, L., Kopp, J., Schwede, T.: The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinformatics 22, 195–201 (2006)CrossRefGoogle Scholar
  11. 11.
    Kiefer, F., Arnold, K., Künzli, M., Bordoli, L., Schwede, T.: The SWISS-MODEL repository and associated resources. Nucleic Acids Res. 37, D387–D392 (2009)CrossRefGoogle Scholar
  12. 12.
    Peitsch, M.C.: Protein modeling by E-mail. Bio/Technology 13, 658–660 (1995)CrossRefGoogle Scholar
  13. 13.
    Brooks, B.R., Bruccoleri, R.E., Olafson, B.D., States, D.J., Swaminathan, S., Karplus, M.: CHARMM: a program for macromolecular energy, minimization, and dynamics calculations. J Comp Chem 4, 187–217 (1983)CrossRefGoogle Scholar
  14. 14.
    Eswar, N., Marti-Renom, M.A., Webb, B., Madhusudhan, M.S., Eramian, D., Shen, M., Pieper, U., Sali, A.: Comparative Protein Structure Modeling With MODELLER. Current Protocols in Bioinformatics 15, 5.6.1–5.6.30 (2006)CrossRefGoogle Scholar
  15. 15.
    Laskowski, R.A., et al.: PROCHECK: a program to check the stereochemistry of protein structures. J. Appl. Crystallogr. 26, 283–291 (1993)CrossRefGoogle Scholar
  16. 16.
    Eisenberg, D., et al.: VERIFY3D: assessment of protein models with three-dimensional profiles. Methods Enzymol. 277, 396–404 (1997)CrossRefGoogle Scholar
  17. 17.
    Colovos, C., Yeates, T.O.: Verification of protein structures: patterns of nonbonded atomic interactions. Protein Sci. 2, 1511–1519 (1993)CrossRefGoogle Scholar
  18. 18.
    Ramachandran, G.N., Sashisekharan, V.: Conformation of polypeptides and proteins. Adv. Protein Chem. 23, 283–438 (1968)CrossRefGoogle Scholar
  19. 19.
    Comeau, S.R., et al.: ClusPro: An automated docking and discrimination method for the prediction of protein complexes. Bioinformatics 20, 45–50 (2004)CrossRefGoogle Scholar
  20. 20.
    Tina, K.G., Bhadra, R., Srinivasan, N.: PIC: protein interactions calculator. Nucleic Acids Res. 35, W473–W476 (2007)CrossRefGoogle Scholar

Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Department of Biochemistry and BiophysicsUniversity of KalyaniKalyani, NadiaIndia

Personalised recommendations