MICAN : a protein structure alignment algorithm that can handle Multiple-chains, Inverse alignments, C α only models, Alternative alignments, and Non-sequential alignments

详细信息    查看全文

• 作者：Shintaro Minami (1)
  Kengo Sawada (2)
  George Chikenji (1)
  
• 刊名：BMC Bioinformatics
• 出版年：2013
• 出版时间：December 2013
• 年：2013
• 卷：14
• 期：1
• 全文大小：1569KB
• 参考文献：1. Matsuo Y, Bryant SH: Identification of homologous core structures. / Proteins 1999, 35:70-. CrossRef
  2. Cheng H, Kim B, Grishin NV: Discrimination between distant homologs and structural analogs: lessons from manually constructed, reliable data sets. / J Mol Biol 2008,377(4):1265-8. CrossRef
  3. Szustakowski JD, Kasif S, Weng Z: Less is more: towards an optimal universal description of protein folds. / Bioinformatics 2005,21(Suppl 2):ii66-1. CrossRef
  4. Novotny M, Madsen D, Kleywegt GJ: Evaluation of protein fold comparison servers. / Proteins 2004,54(2):260-0. CrossRef
  5. Kolodny R: Inverse Kinematics in Biology: The Protein Loop Closure Problem. / Int J Rob Res 2005,24(2-):151-63. CrossRef
  6. Mayr G, Domingues FS, Lackner P: Comparative analysis of protein structure alignments. / BMC Struct Biol 2007, 7:50. CrossRef
  7. Lindqvist Y, Schneider G: Circular permutations of natural protein sequences: structural evidence. / Curr Opin Struct Biol 1997,7(3):422-. CrossRef
  8. Jung J, Lee B: Circularly permuted proteins in the protein structure database. / Protein Sci 2001,10(9):1881-886. CrossRef
  9. Schmidt-Goenner T, Guerler A, Kolbeck B, Knapp EW: Circular permuted proteins in the universe of protein folds. / Proteins 2010,78(7):1618-0. CrossRef
  10. Abyzov A, Ilyin VA: A comprehensive analysis of non-sequential alignments between all protein structures. / BMC Struct Biol 2007, 7:78. CrossRef
  11. Grishin NV: Fold change in evolution of protein structures. / J Struct Biol 2001,134(2-):167-5. CrossRef
  12. Murzin A, Brenner S, Hubbard T, Chothia C: SCOP: a structural classification of proteins database for the investigation of sequences and structures. / J Mol Biol 1995,247(4):536-40.
  13. Dror O: MASS: multiple structural alignment by secondary structures. / Bioinformatics 2003,19(90001):95i-104. CrossRef
  14. Krissinel E, Henrick K: Secondary-structure matching (SSM), a new tool for fast protein structure alignment in three dimensions. / Acta crystallographica. Section D, Biological crystallography 2004,60(Pt 12 Pt 1):2256-8. CrossRef
  15. Ilyin V, Abyzov A, Leslin C: Structural alignment of proteins by a novel TOPOFIT method, as a superimposition of common volumes at a topomax point. / Protein Sci 2004,13(7):1865-874. CrossRef
  16. Yuan X, Bystroff C: Non-sequential structure-based alignments reveal topology-independent core packing arrangements in proteins. / Bioinformatics 2005,21(7):1010-. CrossRef
  17. Shih ESC, Gan RR, Hwang M: OPAAS: a web server for optimal, permuted, and other alternative alignments of protein structures. / Nucleic Acids Res 2006,34(Web Server issue):W95-.
  18. Chen L, Wu L, Wang Y, Zhang S, Zhang X: Revealing divergent evolution, identifying circular permutations and detecting active-sites by protein structure comparison. / BMC Struct Biol 2006, 6:18. CrossRef
  19. Dundas J, Binkowski TA, DasGupta B, Liang J: Topology independent protein structural alignment. / BMC Bioinformatics 2007, 8:388. CrossRef
  20. Kolbeck B, May P, Schmidt-Goenner T, Steinke T, Knapp E: Connectivity independent protein-structure alignment: a hierarchical approach. / BMC Bioinformatics 2006, 7:510. CrossRef
  21. Guerler A, Knapp E: Novel protein folds and their nonsequential structural analogs. / Protein Sci 2008,17(8):1374-382. CrossRef
  22. Salem S, Zaki M: Iterative non-sequential protein structural alignment. / Computational systems bioinformatics 2008,7(3):183.
  23. Cheng H, Kim B, Grishin NV: MALISAM: a database of structurally analogous motifs in proteins. / Nucleic Acids Res 2008,36(Database issue):D211-.
  24. Kinjo A: Similarity search for local protein structures at atomic resolution by exploiting a database management system. / Biophysics 2007, 3:75-4. CrossRef
  25. Kinjo AR, Nakamura H: Comprehensive structural classification of ligand-binding motifs in proteins. / Structure 2009,17(2):234-6. CrossRef
  26. Nussinov R, Wolfson HJ: Efficient detection of three-dimensional structural motifs in biological macromolecules by computer vision techniques. / Proc National Acad Sci U S A 1991,88(23):10495-. CrossRef
  27. Alesker V, Nussinov R, Wolfson HJ: Detection of non-topological motifs in protein structures. / Protein Eng 1996,9(12):1103-9. CrossRef
  28. Kim C, Lee B: Accuracy of structure-based sequence alignment of automatic methods. / BMC Bioinformatics 2007, 8:355. CrossRef
  29. Teichert F, Bastolla U, Porto M: SABERTOOTH: protein structural alignment based on a vectorial structure representation. / BMC Bioinformatics 2007, 8:425. CrossRef
  30. Berbalk C, Schwaiger CS, Lackner P: Accuracy analysis of multiple structure alignments. / Protein Sci 2009,18(10):2027-5. CrossRef
  31. Armougom F, Moretti S, Keduas V, Notredame C: The iRMSD: a local measure of sequence alignment accuracy using structural information. / Bioinformatics 2006,22(14):e35-. CrossRef
  32. Pei J, Kim B, Grishin NV: PROMALS3D: a tool for multiple protein sequence and structure alignments. / Nucleic Acids Res 2008,36(7):2295-00. CrossRef
  33. Daniluk P, Lesyng B: A novel method to compare protein structures using local descriptors. / BMC Bioinformatics 2011, 12:344. CrossRef
  34. Alexandrov NN: SARFing the PDB. / Protein Eng 1996,9(9):727-2. CrossRef
  35. Cheng H, Kim B, Grishin NV: MALIDUP: A database of manually constructed structure alignments for duplicated domain pairs. / Proteins 2008,70(4):1162-166. CrossRef
  36. Holm L, Park J: DaliLite workbench for protein structure comparison. / Bioinformatics 2000,16(6):566-. CrossRef
  37. Zhang Y, Skolnick J: TM-align: a protein structure alignment algorithm based on the TM-score. / Nucleic Acids Res 2005,33(7):2302-. CrossRef
  38. Shindyalov IN, Bourne PE: Protein structure alignment by incremental combinatorial extension (CE) of the optimal path. / Protein Eng 1998,11(9):739-7. CrossRef
  39. Chothia C, Lesk A: The relation between the divergence of sequence and structure in proteins. / EMBO j 1986,5(4):823-26.
  40. Sierk M, Pearson W: Sensitivity and selectivity in protein structure comparison. / Protein Sci 2004,13(3):773-85. CrossRef
  41. Guerler A, Knapp E: GIS: a comprehensive source for protein structure similarities. / Nucleic Acids Res 2010,38(Web Server issue):W46-2. CrossRef
  42. Xu J, Zhang Y: How significant is a protein structure similarity with TM-score = 0.5? / Bioinformatics 2010,26(7):889-5. CrossRef
  43. Johnston SC, Larsen CN, Cook WJ, Wilkinson KD, Hill CP: Crystal structure of a deubiquitinating enzyme (human UCH-L3) at 1.8 A resolution. / EMBO j 1997,16(13):3787-6. CrossRef
  44. Vivares D, Arnoux P, Pignol D: A papain-like enzyme at work: native and acyl-enzyme intermediate structures in phytochelatin synthesis. / Proc National Acad Sci U S A 2005,102(52):18848-3. CrossRef
  45. Kabsch W, Sander C: Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. / Biopolymers 1983,22(12):2577-37. CrossRef
  46. Frishman D, Argos P: Knowledge-based protein secondary structure assignment. / Proteins 1995,23(4):566-9. CrossRef
  47. Zhang Y, Skolnick J: Scoring function for automated assessment of protein structure template quality. / Proteins 2004,57(4):702-0. CrossRef
  48. Andreeva A, Prli? A, Hubbard TJP, Murzin AG: SISYPHUS–structural alignments for proteins with non-trivial relationships. / Nucleic Acids Res 2007,35(Database issue):D253-. CrossRef
  49. Stebbings LA, Mizuguchi K: HOMSTRAD: recent developments of the Homologous Protein Structure Alignment Database. / Nucleic Acids Res 2004,32(Database issue):D203-. CrossRef
  50. Hamprecht FA, Scott W, van Gunsteren WF: Generation of pseudonative protein structures for threading. / Proteins 1997,28(4):522-. CrossRef
  51. Taylor WR: Decoy models for protein structure comparison score normalisation. / J Mol Biol 2006,357(2):676-9. CrossRef
  
• 作者单位：Shintaro Minami (1)
  Kengo Sawada (2)
  George Chikenji (1)
  
  1. Department of Computational Science and Engineering, Nagoya University, Nagoya, 464-8603, Japan
  2. Department of Applied Physics, Nagoya University, Nagoya, 464-8603, Japan
  
• ISSN：1471-2105

文摘

Background Protein pairs that have the same secondary structure packing arrangement but have different topologies have attracted much attention in terms of both evolution and physical chemistry of protein structures. Further investigation of such protein relationships would give us a hint as to how proteins can change their fold in the course of evolution, as well as a insight into physico-chemical properties of secondary structure packing. For this purpose, highly accurate sequence order independent structure comparison methods are needed. Results We have developed a novel protein structure alignment algorithm, MICAN (a structure alignment algorithm that can handle Multiple-chain complexes, Inverse direction of secondary structures, C α only models, Alternative alignments, and Non-sequential alignments). The algorithm was designed so as to identify the best structural alignment between protein pairs by disregarding the connectivity between secondary structure elements (SSE). One of the key feature of the algorithm is utilizing the multiple vector representation for each SSE, which enables us to correctly treat bent or twisted nature of long SSE. We compared MICAN with other 9 publicly available structure alignment programs, using both reference-dependent and reference-independent evaluation methods on a variety of benchmark test sets which include both sequential and non-sequential alignments. We show that MICAN outperforms the other existing methods for reproducing reference alignments of non-sequential test sets. Further, although MICAN does not specialize in sequential structure alignment, it showed the top level performance on the sequential test sets. We also show that MICAN program is the fastest non-sequential structure alignment program among all the programs we examined here. Conclusions MICAN is the fastest and the most accurate program among non-sequential alignment programs we examined here. These results suggest that MICAN is a highly effective tool for automatically detecting non-trivial structural relationships of proteins, such as circular permutations and segment-swapping, many of which have been identified manually by human experts so far. The source code of MICAN is freely download-able at http://www.tbp.cse.nagoya-u.ac.jp/MICAN.