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Computational and Mathematical Methods in Medicine
Volume 2012, Article ID 790281, 11 pages
http://dx.doi.org/10.1155/2012/790281
Research Article

Membrane Protein Stability Analyses by Means of Protein Energy Profiles in Case of Nephrogenic Diabetes Insipidus

Department of Mathematics, Natural and Computer Sciences, Hochschule Mittweida, University of Applied Sciences, Technikumplatz 17, 09648 Mittweida, Germany

Received 24 November 2011; Accepted 4 January 2012

Academic Editor: Silvina Matysiak

Copyright © 2012 Florian Heinke and Dirk Labudde. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. G. E. Tusnády, Z. Dosztányi, and I. Simon, “PDB_TM: selection and membrane localization of transmembrane proteins in the protein data bank,” Nucleic Acids Research, vol. 33, pp. D275–D278, 2005. View at Publisher · View at Google Scholar
  2. G. E. Tusnády, Z. Dosztányi, and I. Simon, “Transmembrane proteins in the Protein Data Bank: identification and classification,” Bioinformatics, vol. 20, no. 17, pp. 2964–2972, 2004. View at Publisher · View at Google Scholar · View at Scopus
  3. P. W. Rose, B. Beran, C. Bi et al., “The RCSB Protein Data Bank: redesigned web site and web services,” Nucleic Acids Research, vol. 39, supplement 1, pp. D392–D401, 2011. View at Publisher · View at Google Scholar
  4. A. Marsico, D. Labudde, T. Sapra, D. J. Muller, and M. Schroeder, “A novel pattern recognition algorithm to classify membrane protein unfolding pathways with high-throughput single-molecule force spectroscopy,” Bioinformatics, vol. 23, no. 2, pp. e231–e236, 2007. View at Publisher · View at Google Scholar · View at Scopus
  5. A. C. M. Jansen, E. S. van Aalst-Cohen, M. W. Tanck et al., “The contribution of classical risk factors to cardiovascular disease in familial hypercholesterolaemia: data in 2400 patients,” Journal of Internal Medicine, vol. 256, no. 6, pp. 482–490, 2004. View at Publisher · View at Google Scholar · View at Scopus
  6. E. S. van Aalst-Cohen, A. C. M. Jansen, M. W. T. Tanck et al., “Diagnosing familial hypercholesterolaemia: the relevance of genetic testing,” European Heart Journal, vol. 27, no. 18, pp. 2240–2246, 2006. View at Publisher · View at Google Scholar · View at Scopus
  7. M. Sultan, S. Werlin, and N. Venkatasubramani, “The prevalence and characteristics of genetic pancreatitis in children with chronic and recurrent acute pancreatitis,” Journal of Pediatric Gastroenterology and Nutrition. In press. View at Publisher · View at Google Scholar
  8. G. L. Robertson, “Diabetes insipidus,” Endocrinology and Metabolism Clinics of North America, vol. 24, no. 3, pp. 549–572, 1995. View at Google Scholar
  9. S. Ananthakrishnan, “Diabetes insipidus in pregnancy: etiology, eva luation, and management,” Endocrine Practice, vol. 15, no. 4, pp. 377–382, 2009. View at Publisher · View at Google Scholar
  10. R. Krysiak, I. Kobielusz-Gembala, and B. Okopien, “Recurrent pregnancy-induced diabetes insipidus in a woman with hemochromatosis,” Endocrine Journal, vol. 57, no. 12, pp. 1023–1028, 2010. View at Publisher · View at Google Scholar · View at Scopus
  11. A. M. W. Van Den Ouweland, J. C. F. M. Dreesen, M. Verdijk et al., “Mutations in the vasopressin type 2 receptor gene (AVPR2) associated with nephrogenic diabetes insipidus,” Nature Genetics, vol. 2, no. 2, pp. 99–102, 1992. View at Google Scholar · View at Scopus
  12. W. Rosenthal, A. Seibold, A. Antaramian et al., “Molecular identification of the gene responsible for congenital nephrogenic diabetes insipidus,” Nature, vol. 359, no. 6392, pp. 233–235, 1992. View at Publisher · View at Google Scholar · View at Scopus
  13. P. M. T. Deen, M. A. J. Verdijk, N. V. A. M. Knoers et al., “Requirement of human renal water channel aquaporin-2 for vasopressin-dependent concentration of urine,” Science, vol. 264, no. 5155, pp. 92–95, 1994. View at Google Scholar · View at Scopus
  14. S. M. Mulders, D. G. Bichet, J. P. L. Rijss et al., “An aquaporin-2 water channel mutant which causes autosomal dominant nephrogenic diabetes insipidus is retained in the golgi complex,” The Journal of Clinical Investigation, vol. 102, no. 1, pp. 57–66, 1998. View at Google Scholar · View at Scopus
  15. E. L. Los, P. M. Deen, and J. H. Robben, “Potential of nonpeptide (ant)agonists to rescue vasopressin V2 receptor mutants for the treatment of X-linked nephrogenic diabetes insipidus,” Journal of Neuroendocrinology, vol. 22, no. 5, pp. 393–399, 2010. View at Publisher · View at Google Scholar · View at Scopus
  16. J. H. Robben, N. V. A. M. Knoers, and P. M. T. Deen, “Cell biological aspects of the vasopressin type-2 receptor and aquaporin 2 water channel in nephrogenic diabetes insipidus,” American Journal of Physiology, vol. 291, no. 2, pp. F257–F270, 2006. View at Publisher · View at Google Scholar · View at Scopus
  17. C. Barberis, B. Mouillac, and T. Durroux, “Structural bases of vasopressin/oxytocin receptor function,” Journal of Endocrinology, vol. 156, no. 2, pp. 223–229, 1998. View at Publisher · View at Google Scholar · View at Scopus
  18. M. J. Ślusarz, A. Giełdoń, R. Ślusarz, and J. Ciarkowski, “Analysis of interactions responsible for vasopressin binding to human neurohypophyseal hormone receptors—molecular dynamics study of the activated receptor-vasopressin-Gα systems,” Journal of Peptide Science, vol. 12, no. 3, pp. 180–189, 2006. View at Publisher · View at Google Scholar
  19. M. J. Ślusarz, E. Sikorska, R. Ślusarz, and J. Ciarkowski, “Molecular docking-based study of vasopressin analogues modified at positions 2 and 3 with N-methylphenylalanine: influence on receptor-bound conformations and interactions with vasopressin and oxytocin receptors,” Journal of Medicinal Chemistry, vol. 49, no. 8, pp. 2463–2469, 2006. View at Publisher · View at Google Scholar
  20. A. Roy, A. Kucukural, and Y. Zhang, “I-TASSER: a unified platform for automated protein structure and function prediction,” Nature Protocols, vol. 5, no. 4, pp. 725–738, 2010. View at Google Scholar · View at Scopus
  21. L. Kalé, R. Skeel, M. Bhandarkar et al., “NAMD2: greater scalability for parallel molecular dynamics,” Journal of Computational Physics, vol. 151, no. 1, pp. 283–312, 1999. View at Publisher · View at Google Scholar · View at Scopus
  22. A. D. MacKerell, B. Brooks, and C. L. Brooks, “CHARMM: the energy function and its parameterization with an overview of the program,” in The Encyclopedia of Computational Chemistry. 1, P. V. R. Schleyer et al., Ed., pp. 271–277, John Wiley & Sons, Chichester, UK, 1998. View at Google Scholar
  23. L. S. King, D. Kozono, and P. Agre, “From structure to disease: the evolving tale of aquaporin biology,” Nature Reviews Molecular Cell Biology, vol. 5, no. 9, pp. 687–698, 2004. View at Publisher · View at Google Scholar · View at Scopus
  24. T. D. Pollard and W. C. Earnshaw, Cell Biology, Springer, Heidelberg, Germany, 2004.
  25. B. L. de Groot, T. Frigato, V. Helms, and H. Grubmüller, “The mechanism of proton exclusion in the aquaporin-1 water channel,” Journal of Molecular Biology, vol. 333, no. 2, pp. 279–293, 2003. View at Publisher · View at Google Scholar · View at Scopus
  26. N. Chakrabarti, E. Tajkhorshid, B. Roux, and R. Pomès, “Molecular basis of proton blockage in aquaporins,” Structure, vol. 12, no. 1, pp. 65–74, 2004. View at Publisher · View at Google Scholar · View at Scopus
  27. N. Chakrabarti, B. Roux, and R. Pomès, “Structural determinants of proton blockage in aquaporins,” Journal of Molecular Biology, vol. 343, no. 2, pp. 493–510, 2004. View at Publisher · View at Google Scholar · View at Scopus
  28. U. Pieper, B. M. Webb, D. T. Barkan et al., “ModBase,a database of annotated comparative protein structure models,and associated resources,” Nucleic Acids Research, vol. 39, supplement 1, pp. D465–D474, 2011. View at Publisher · View at Google Scholar
  29. L. Willard, A. Ranjan, H. Zhang et al., “VADAR: a web server for quantitative evaluation of protein structure quality,” Nucleic Acids Research, vol. 31, no. 13, pp. 3316–3319, 2003. View at Publisher · View at Google Scholar · View at Scopus
  30. C. B. Anfinsen, “Principles that govern the folding of protein chains,” Science, vol. 181, no. 4096, pp. 223–230, 1973. View at Google Scholar · View at Scopus
  31. J. Wang, R. M. Wolf, J. W. Caldwell, P. A. Kollman, and D. A. Case, “Development and testing of a general Amber force field,” Journal of Computational Chemistry, vol. 25, no. 9, pp. 1157–1174, 2004. View at Publisher · View at Google Scholar
  32. J. Wang, R. M. Wolf, J. W. Caldwell, P. A. Kollman, and D. A. Case, “Erratum: ‘Development and testing of a general amber force field (Journal of Computational Chemistry (2004) 25 (1157))’,” Journal of Computational Chemistry, vol. 26, no. 1, article 114, 2005. View at Publisher · View at Google Scholar · View at Scopus
  33. A. D. MacKerell, D. Bashford, M. Bellott et al., “All-atom empirical potential for molecular modeling and dynamics studies of proteins,” Journal of Physical Chemistry B, vol. 102, no. 18, pp. 3586–3616, 1998. View at Google Scholar · View at Scopus
  34. S. Tanaka and H. A. Scheraga, “Medium- and long-range interaction parameters between amino acids for predicting three-dimensional structures of proteins,” Macromolecules, vol. 9, no. 6, pp. 945–950, 1976. View at Google Scholar · View at Scopus
  35. D. H. Wertz and H. A. Scheraga, “Influence of water on protein structure. An analysis of the preferences of amino acid residues for the inside or outside and for specific conformations in a protein molecule,” Macromolecules, vol. 11, no. 1, pp. 9–15, 1978. View at Google Scholar · View at Scopus
  36. F. Dressel, A. Marsico, A. Tuukkanen, M. Schroeder, and D. Labudde, “Understanding of SMFS barriers by means of energy profiles,” in Proceedings of the German Conference on Bioinformatics, pp. 90–99, 2007.
  37. J. U. Bowie, R. Luthy, and D. Eisenberg, “A method to identify protein sequences that fold into a known three-dimensional structure,” Science, vol. 253, no. 5016, pp. 164–170, 1991. View at Google Scholar · View at Scopus
  38. H. Singh and S. Ahmad, “Context dependent reference states of solvent accessibility derived from native protein structures and assessed by predictability analysis,” BMC Structural Biology, vol. 9, article 25, 2009. View at Publisher · View at Google Scholar · View at Scopus
  39. M. J. Sippl, “Boltzmann's principle, knowledge-based mean fields and protein folding. An approach to the computational determination of protein structures,” Journal of Computer-Aided Molecular Design, vol. 7, no. 4, pp. 473–501, 1993. View at Google Scholar · View at Scopus
  40. S. B. Needleman and C. D. Wunsch, “A general method applicable to the search for similarities in the amino acid sequence of two proteins,” Journal of Molecular Biology, vol. 48, no. 3, pp. 443–453, 1970. View at Google Scholar · View at Scopus
  41. T. F. Smith and M. S. Waterman, “Identification of common molecular subsequences,” Journal of Molecular Biology, vol. 147, no. 1, pp. 195–197, 1981. View at Google Scholar · View at Scopus
  42. D. G. Higgins, J. D. Thompson, and T. J. Gibson, “[22] Using CLUSTAL for multiple sequence alignments,” Methods in Enzymology, vol. 266, pp. 383–400, 1996. View at Google Scholar · View at Scopus
  43. K. A. Dill and H. S. Chan, “From levinthal to pathways to funnels,” Nature Structural Biology, vol. 4, no. 1, pp. 10–19, 1997. View at Publisher · View at Google Scholar · View at Scopus
  44. E. Krissinel and K. Henrick, “Secondary-structure matching (SSM), a new tool for fast protein structure alignment in three dimensions,” Acta Crystallographica Section D, vol. 60, no. 12, part 1, pp. 2256–2268, 2004. View at Publisher · View at Google Scholar
  45. C. Guyon, Y. Lussier, P. Bissonnette et al., “Characterization of D150E and G196D aquaporin-2 mutations responsible for nephrogenic diabetes insipidus: importance of a mild phenotype,” American Journal of Physiology, vol. 297, no. 2, pp. F489–F498, 2009. View at Publisher · View at Google Scholar
  46. T. M. Martinetz and K. J. Schulten, “A neural-gas network learns topologies,” in Artificial Neural Networks, T. Kohonen, K. Mkisara, O. Simula, and J. Kangas, Eds., pp. 397–402, North-Holland, Amsterdam, The Netherlands, 1991. View at Google Scholar
  47. I. H. Witten and F. Eibe, Data Mining: Practical Machine Learning Tools and Techniques, Morgan Kaufmann, Amsterdam, The Netherlands, 2005.
  48. Z. Bikadi and E. Hazai, “Application of the PM6 semi-empirical method to modeling proteins enhances docking accuracy of AutoDock,” Journal of Cheminformatics, vol. 1, no. 1, article 15, 2009. View at Publisher · View at Google Scholar · View at Scopus
  49. F. Heinke, A. Tuukkanen, and D. Labudde, “Analysis of Membrane Protein Stability in Diabetes Insipidus,” K. Kamoi, Ed., InTech, 2011. View at Google Scholar
  50. K. Arnold, L. Bordoli, J. Kopp, and T. Schwede, “The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling,” Bioinformatics, vol. 22, no. 2, pp. 195–201, 2006. View at Publisher · View at Google Scholar · View at Scopus
  51. F. Kiefer, K. Arnold, M. Künzli, L. Bordoli, and T. Schwede, “The SWISS-MODEL Repository and associated resources,” Nucleic Acids Research, vol. 37, no. 1, pp. D387–D392, 2009. View at Publisher · View at Google Scholar · View at Scopus
  52. E. Albertazzi, D. Zanchetta, P. Barbier et al., “Nephrogenic diabetes insipidus: functional analysis of new AVPR2 mutations identified in Italian families,” Journal of the American Society of Nephrology, vol. 11, no. 6, pp. 1033–1043, 2000. View at Google Scholar · View at Scopus
  53. K. Pasel, A. Schulz, K. Timmermann et al., “Functional characterization of the molecular defects causing nephrogenic diabetes insipidus in eight families,” Journal of Clinical Endocrinology and Metabolism, vol. 85, no. 4, pp. 1703–1710, 2000. View at Publisher · View at Google Scholar
  54. J. H. Robben, N. V. A. M. Knoers, and P. M. T. Deen, “Characterization of vasopressin V2 receptor mutants in nephrogenic diabetes insipidus in a polarized cell model,” American Journal of Physiology, vol. 289, no. 2, pp. F265–F272, 2005. View at Publisher · View at Google Scholar · View at Scopus
  55. D. Morin, Y. Ala, N. Sabatier et al., “Functional study of two V2 vasopressin mutant receptors related to NDI P322S and P322H,” Advances in Experimental Medicine and Biology, vol. 449, pp. 391–393, 1998. View at Google Scholar · View at Scopus
  56. R. Vargas-Poussou, L. Forestier, M. D. Dautzenberg, P. Niaudet, M. Déchaux, and C. Antignac, “Mutations in the vasopressin V2 receptor and aquaporin-2 genes in 12 families with congenital nephrogenic diabetes insipidus,” Journal of the American Society of Nephrology, vol. 8, no. 12, pp. 1855–1862, 1997. View at Google Scholar