Open AccessGR-Align: fast and flexible alignment of protein 3D structures using graphlet degree similarity
Author(s) -
Noël Malod-Dognin,
Nataša Pržulj
Publication year - 2014
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btu020
Subject(s) - similarity (geometry) , benchmark (surveying) , structural alignment , computer science , domain (mathematical analysis) , heuristic , structural similarity , protein structure , smith–waterman algorithm , set (abstract data type) , protein domain , data mining , sequence alignment , scale (ratio) , algorithm , pattern recognition (psychology) , theoretical computer science , artificial intelligence , mathematics , biology , physics , geography , peptide sequence , image (mathematics) , mathematical analysis , biochemistry , geodesy , gene , programming language , quantum mechanics
Protein structure alignment is key for transferring information from well-studied proteins to less studied ones. Structural alignment identifies the most precise mapping of equivalent residues, as structures are more conserved during evolution than sequences. Among the methods for aligning protein structures, maximum Contact Map Overlap (CMO) has received sustained attention during the past decade. Yet, known algorithms exhibit modest performance and are not applicable for large-scale comparison.