Table of Contents Author Guidelines Submit a Manuscript
International Journal of Biomedical Imaging
Volume 2010, Article ID 923780, 9 pages
http://dx.doi.org/10.1155/2010/923780
Research Article

Molecular Surface Mesh Generation by Filtering Electron Density Map

Communications and Remote Sensing Laboratory, Catholic University of Louvain, B-1348 Louvain-la-Neuve, Belgium

Received 25 September 2009; Revised 23 November 2009; Accepted 6 January 2010

Academic Editor: Guo Wei

Copyright © 2010 Joachim Giard and Benoît Macq. 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. J. S. Fetrow and J. Skolnick, “Method for prediction of protein function from sequence using the sequence-to-structure-to-function paradigm with application to glutaredoxins/thioredoxins and T1 ribonucleases,” Journal of Molecular Biology, vol. 281, no. 5, pp. 949–968, 1998. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  2. C. Zhang and S.-H. Kim, “Overview of structural genomics: from structure to function,” Current Opinion in Chemical Biology, vol. 7, no. 1, pp. 28–32, 2003. View at Publisher · View at Google Scholar · View at Scopus
  3. J. D. Watson, R. A. Laskowski, and J. M. Thornton, “Predicting protein function from sequence and structural data,” Current Opinion in Structural Biology, vol. 15, no. 3, pp. 275–284, 2005. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  4. I. D. Kuntz, “Structure-based strategies for drug design and discovery,” Science, vol. 257, no. 5073, pp. 1078–1082, 1992. View at Google Scholar · View at Scopus
  5. M. Congreve, C. Murray, and T. Blundell, “Keynote review: structural biology and drug discovery,” Drug Discovery Today, vol. 10, no. 13, pp. 895–907, 2005. View at Google Scholar
  6. M. Prevost, S. J. Wodak, B. Tidor, and M. Karplus, “Contribution of the hydrophobic effect to protein stability: analysis based on simulations of the ile-96- ala mutation in barnase,” Proceedings of the National Academy of Sciences, vol. 88, no. 23, pp. 10880–10884, 1991. View at Google Scholar
  7. Z. W. Cao, L. Y. Han, C. J. Zheng et al., “Computer prediction of drug resistance mutations in proteins,” Drug Discovery Today, vol. 10, no. 7, pp. 521–529, 2005. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  8. S. Bespamyatnikh, V. Choi, H. Edelsbrunner, and J. Rudolph, Accurate Protein Docking by Shape Complementarity Alone, Duke University, Durham, NC, USA, 2004.
  9. W. DeLano, The PyMOL Molecular Graphics System, DeLano Scientific, San Carlos, Calif, USA, 2002.
  10. D. Fischer, S. L. Lin, H. L. Wolfson, and R. Nussinov, “A geometry-based suite of molecular docking processes,” Journal of Molecular Biology, vol. 248, no. 2, pp. 459–477, 1995. View at Google Scholar · View at Scopus
  11. H. A. Gabb, R. M. Jackson, and M. J. E. Sternberg, “Modelling protein docking using shape complementarity, electrostatics and biochemical information,” Journal of Molecular Biology, vol. 272, no. 1, pp. 106–120, 1997. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  12. N. Brooijmans and I. D. Kuntz, “Molecular recognition and docking algorithms,” Annual Review of Biophysics and Biomolecular Structure, vol. 32, pp. 335–373, 2003. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  13. Y. Wang, P. K. Agarwal, P. Brown, H. Edelsbrunner, and J. Rudolph, “Coarse and reliable geometric alignment for protein docking,” in Proceedings of the Pacific Symposium on Biocomputing, pp. 65–75, 2005.
  14. G. J. Bartlett, C. T. Porter, N. Borkakoti, and J. M. Thornton, “Analysis of catalytic residues in enzyme active sites,” Journal of Molecular Biology, vol. 324, no. 1, pp. 105–121, 2002. View at Publisher · View at Google Scholar · View at Scopus
  15. P. Bate and J. Warwicker, “Enzyme/non-enzyme discrimination and prediction of enzyme active site location using charge-based methods,” Journal of Molecular Biology, vol. 340, no. 2, pp. 263–276, 2004. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  16. R. Chakrabarti, A. M. Klibanov, and R. A. Friesner, “Computational prediction of native protein ligand-binding and enzyme active site sequences,” Proceedings of the National Academy of Sciences of the United States of America, vol. 102, no. 29, pp. 10153–10158, 2005. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  17. J. R. Bradford, C. J. Needham, A. J. Bulpitt, and D. R. Westhead, “Insights into protein-protein interfaces using a Bayesian network prediction method,” Journal of Molecular Biology, vol. 362, no. 2, pp. 365–386, 2006. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  18. F. K. Pettit, E. Bare, A. Tsai, and J. U. Bowie, “HotPatch: a statistical approach to finding biologically relevant features on protein surfaces,” Journal of Molecular Biology, vol. 369, no. 3, pp. 863–879, 2007. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  19. J. Giard, J. Ambroise, J. L. Gala, and B. Macq, “Regression applied to protein binding site prediction and comparison with classification,” BMC Bioinformatics, vol. 10, no. 1, p. 276, 2009. View at Google Scholar · View at Scopus
  20. T. Arakawa and S. N. Timasheff, “Stabilization of protein structure by sugars,” Biochemistry, vol. 21, no. 25, pp. 6536–6544, 1982. View at Google Scholar · View at Scopus
  21. N. Max, “Progress in scientific visualization,” The Visual Computer, vol. 21, no. 12, pp. 979–984, 2005. View at Publisher · View at Google Scholar · View at Scopus
  22. M. L. Connolly, Molecular Surfaces: A Review, Network Science, 1996.
  23. M. L. Connolly, “Analytical molecular surface calculation,” Journal of Applied Crystallography, vol. 6, pp. 548–558, 1983. View at Google Scholar
  24. C. L. Bajaj, V. Pascucci, A. Shamir, R. J. Holt, and A. N. Netravali, “Dynamic maintenance and visualization of molecular surfaces,” Discrete Applied Mathematics, vol. 127, no. 1, pp. 23–51, 2003. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  25. P. Laug and H. Borouchaki, “Molecular surface modeling and meshing,” Engineering with Computers, vol. 18, no. 3, pp. 199–210, 2002. View at Publisher · View at Google Scholar · View at Scopus
  26. M. F. Sanner, A. J. Olson, and J.-C. Spehner, “Reduced surface: an efficient way to compute molecular surfaces,” Biopolymers, vol. 38, no. 3, pp. 305–320, 1996. View at Google Scholar · View at Scopus
  27. H. Edelsbrunner and E. Mücke, “Three-dimensional alpha shapes,” in Proceedings of the Workshop on Volume Visualization, pp. 75–82, ACM, Boston, Mass, USA, 1992.
  28. D.-S. Kim, J. Seo, D. Kim, J. Ryu, and C.-H. Cho, “Three-dimensional beta shapes,” Computer-Aided Design, vol. 38, no. 11, pp. 1179–1191, 2006. View at Publisher · View at Google Scholar · View at Scopus
  29. J. Ryu, R. Park, and D.-S. Kim, “Molecular surfaces on proteins via beta shapes,” Computer-Aided Design, vol. 39, no. 12, pp. 1042–1057, 2007. View at Publisher · View at Google Scholar · View at Scopus
  30. H.-L. Cheng and X. Shi, “Quality mesh generation for molecular skin surfaces using restricted union of balls,” Computational Geometry, vol. 42, no. 3, pp. 196–206, 2009. View at Publisher · View at Google Scholar · View at Scopus
  31. Y. Zhang, G. Xu, and C. L. Bajaj, “Quality meshing of implicit solvation models of biomolecular structures,” Computer-Aided Geometric Design, vol. 23, no. 6, pp. 510–530, 2006. View at Google Scholar
  32. T. Can, C.-I. Chen, and Y.-F. Wang, “Efficient molecular surface generation using level-set methods,” Journal of Molecular Graphics and Modelling, vol. 25, no. 4, pp. 442–454, 2006. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  33. W. Lorensen and H. Cline, “Marching cubes: a high resolution 3D surface construction algorithm,” in Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH '87), pp. 163–169, ACM, Anaheim, Calif, USA, July 1987.
  34. E. Brigham and C. Yuen, “The fast Fourier transform,” IEEE Transactions on Systems, Man and Cybernetics, vol. 8, no. 2, p. 146, 1978. View at Google Scholar
  35. H. Hoppe, T. DeRose, T. Duchamp et al., “Piecewise smooth surface reconstruction,” in Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH '94), vol. 94, pp. 295–302, 1994.
  36. D. Zorin, P. Schröder, and W. Sweldens, “Interpolating subdivision for meshes with arbitrary topology,” in Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH '96), pp. 189–192, ACM, New Orleans, La, USA, 1996.
  37. E. F. Pettersen, T. D. Goddard, C. C. Huang et al., “UCSF Chimera—a visualization system for exploratory research and analysis,” Journal of Computational Chemistry, vol. 25, no. 13, pp. 1605–1612, 2004. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  38. N. Guex and M. Peitsch, “SWISS-MODEL and the Swiss-Pdb viewer: an environment for comparative protein modeling,” Electrophoresis, vol. 18, no. 15, 1997. View at Google Scholar