Amino Acids

, Volume 39, Issue 2, pp 417–425 | Cite as

SANA: an algorithm for sequential and non-sequential protein structure alignment

  • Lin Wang
  • Ling-Yun Wu
  • Yong Wang
  • Xiang-Sun ZhangEmail author
  • Luonan ChenEmail author
Original Article


Protein structure alignment algorithms play an important role in the studies of protein structure and function. In this paper, a novel approach for structure alignment is presented. Specifically, core regions in two protein structures are first aligned by identifying connected components in a network of neighboring geometrically compatible aligned fragment pairs. The initial alignments then are refined through a multi-objective optimization method. The algorithm can produce both sequential and non-sequential alignments. We show the superior performance of the proposed algorithm by the computational experiments on several benchmark datasets and the comparisons with the well-known structure alignment algorithms such as DALI, CE and MATT. The proposed method can obtain accurate and biologically significant alignment results for the case with occurrence of internal repeats or indels, identify the circular permutations, and reveal conserved functional sites. A ranking criterion of our algorithm for fold similarity is presented and found to be comparable or superior to the Z-score of CE in most cases from the numerical experiments. The software and supplementary data of computational results are available at


Protein structure alignment Fold comparison Circular permutation Functional sites 



Protein data bank


Root mean square distance


Aligned fragment pair


Protein structure alignment based on sequence neighborhood alignment



We are grateful to the anonymous referees for many helpful comments that greatly improved the paper. This work is partly supported by the National Natural Science Foundation of China (NSFC) under Key Research Grant No. 10631070, Research Grant No. 60503004, and JSPS-NSFC collaborative project (No. 10711140116). This work is also partially supported by the Chief Scientist Program of Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences with the grant no. 2009CSP002.


  1. Aung Z, Tan KL (2006) MatAlign: precise protein structure comparison by matrix alignment. J Bioinform Comput Biol 4:1197–1216CrossRefPubMedGoogle Scholar
  2. Bachar O, Fischer D, Nussinov R, Wolfson H (1993) A computer version based technique for 3-d sequence independent structural comparison of proteins. Protein Eng 6:279–288CrossRefPubMedGoogle Scholar
  3. Betancourt MR, Skolnick J (2001) Universal similarity measure for comparing protein structures. Biopolymers 59:305–309CrossRefPubMedGoogle Scholar
  4. Bhattacharya S, Bhattacharyya C, Chandra NR (2007) Comparison of protein structures comparison by growing neighborhood alignments. BMC Bioinformatics 8:77CrossRefPubMedGoogle Scholar
  5. Birzele F, Gewehr JE, Csaba G, Zimmer R (2007) Vorolign-fast structural alignment using Voronoi contacts. Bioinformatics 23:e205–e211CrossRefPubMedGoogle Scholar
  6. Chen L, Wu LY, Wang Y, Zhang SH, Zhang XS (2006) Revealing divergent evolution, identifying circular permutations and detecting active sites by protein structure comparison. BMC Struct Biol 6:18CrossRefPubMedGoogle Scholar
  7. Fischer D, Elofsson A, Rice DW, Eisenberg D (1996) Assessing the performance of fold recognition methods by means of a comprehensive benchmark. In: Proceedings of 1996 Pacific Symposium on Biocomputing, pp 300–318Google Scholar
  8. Gazit H (1991) An optimal randomized parallel algorithm for finding connected components in a graph. SIAM J Comput 20:1046–1067CrossRefGoogle Scholar
  9. Holm L, Sander C (1993) Protein structure comparison by alignment of distance matrices. J Mol Biol 233:123–128CrossRefPubMedGoogle Scholar
  10. Krissinel E, Henrick K (2004) Secondary-structure matching (SSM), a new tool for fast protein structure alignment in three dimensions. Acta Crystallogr Sect D 60:2256–2268CrossRefGoogle Scholar
  11. Lo WC, Lyu PC (2008) CPSARST: an efficient circular permutation search tool applied to the detection of novel protein structural relationships. Genome Biol 9:R11CrossRefPubMedGoogle Scholar
  12. Mayr G, Domingues FS, Lackner P (2007) Comparative analysis of protein structure alignments. BMC Struct Biol 7:50CrossRefPubMedGoogle Scholar
  13. Menke M, Berger B, Cowen L (2008) Matt: local flexibility aids protein multiple structure alignment. PLoS Comput Biol 4:1–12CrossRefGoogle Scholar
  14. Novotny M, Madsen D, Kleywegt GJ (2004) Evaluation of protein fold comparison servers. Proteins Struct Funct Bioinform 54:260–270CrossRefGoogle Scholar
  15. Shatsky M, Nussinov R, Wolfson H (2004) A method for simultaneous alignment of multiple protein structures. Proteins Struct Funct Bioinform 56:143–156CrossRefGoogle Scholar
  16. Shindyalov IN, Bourne PE (1998) Protein structure alignment by incremental combinatorial extension (CE) of the optimal path. Protein Eng 11:739–747CrossRefPubMedGoogle Scholar
  17. Van Walle I, Lasters I, Wyns L (2005) SABmark—a benchmark for sequence alignment that covers the entire known fold space. Bioinformatics 21:1267–1268CrossRefPubMedGoogle Scholar
  18. Ye Y, Godzik A (2003) Flexible structure alignment by chaining aligned fragment pairs allowing twists. Bioinformatics 19:e246–e255Google Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Computer Science and Information Engineering CollegeTianjin University of Science and TechnologyTianjinChina
  2. 2.Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijingChina
  3. 3.Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological SciencesChinese Academy of SciencesShanghaiChina

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