title: GS-align for glycan structure alignment and similarity measurement.
abstract: BACKGROUND
  Glycans play critical roles in many biological processes, and their structural diversity is key for specific protein-glycan recognition. Comparative structural studies of biological molecules provide useful insight into their biological relationships. However, most computational tools are designed for protein structure, and despite their importance, there is no currently available tool for comparing glycan structures in a sequence order- and size-independent manner.
  
  
  RESULTS
  A novel method, GS-align, is developed for glycan structure alignment and similarity measurement. GS-align generates possible alignments between two glycan structures through iterative maximum clique search and fragment superposition. The optimal alignment is then determined by the maximum structural similarity score, GS-score, which is size-independent. Benchmark tests against the Protein Data Bank (PDB) N-linked glycan library and PDB homologous/non-homologous N-glycoprotein sets indicate that GS-align is a robust computational tool to align glycan structures and quantify their structural similarity. GS-align is also applied to template-based glycan structure prediction and monosaccharide substitution matrix generation to illustrate its utility.
  
  
  METHODS
  http://www.glycanstructure.org/gsalign.
  
  
  BACKGROUND
  wonpil@ku.edu
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors: Department of Molecular Biosciences and Center for Computational Biology, University of Kansas, Lawrence, KS 66047, USA.
authors: Hui Sun
authors: HS
authors: Lee
authors: Department of Molecular Biosciences and Center for Computational Biology, University of Kansas, Lawrence, KS 66047, USA.
authors: Sunhwan
authors: S
authors: Jo
authors: Department of Biochemistry and Molecular Biology, University of Kansas Medical Center, Kansas City, KS 66160, USA.
authors: Srayanta
authors: S
authors: Mukherjee
authors: School of Computational Sciences and Center for In Silico Protein Science, Korea Institute for Advanced Study, Seoul 130-722, Korea and.
authors: Sang-Jun
authors: SJ
authors: Park
authors: Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, GA 30076, USA.
authors: Jeffrey
authors: J
authors: Skolnick
authors: School of Computational Sciences and Center for In Silico Protein Science, Korea Institute for Advanced Study, Seoul 130-722, Korea and.
authors: Jooyoung
authors: J
authors: Lee
authors: Department of Molecular Biosciences and Center for Computational Biology, University of Kansas, Lawrence, KS 66047, USA.
authors: Wonpil
authors: W
authors: Im
mesh_terms: D002236:Carbohydrate Conformation; D002240:Carbohydrate Sequence; D019295:Computational Biology / Q000379:methods*; D006023:Glycoproteins / Q000737:chemistry*; D006801:Humans; D008969:Molecular Sequence Data; D011134:Polysaccharides / Q000737:chemistry*; D016415:Sequence Alignment / Q000379:methods*; D012984:Software
chemical_list: D006023:Glycoproteins; D011134:Polysaccharides