title: TM-align: a protein structure alignment algorithm based on the TM-score.
abstract: We have developed TM-align, a new algorithm to identify the best structural alignment between protein pairs that combines the TM-score rotation matrix and Dynamic Programming (DP). The algorithm is approximately 4 times faster than CE and 20 times faster than DALI and SAL. On average, the resulting structure alignments have higher accuracy and coverage than those provided by these most often-used methods. TM-align is applied to an all-against-all structure comparison of 10 515 representative protein chains from the Protein Data Bank (PDB) with a sequence identity cutoff <95%: 1996 distinct folds are found when a TM-score threshold of 0.5 is used. We also use TM-align to match the models predicted by TASSER for solved non-homologous proteins in PDB. For both folded and misfolded models, TM-align can almost always find close structural analogs, with an average root mean square deviation, RMSD, of 3 A and 87% alignment coverage. Nevertheless, there exists a significant correlation between the correctness of the predicted structure and the structural similarity of the model to the other proteins in the PDB. This correlation could be used to assist in model selection in blind protein structure predictions. The TM-align program is freely downloadable at http://bioinformatics.buffalo.edu/TM-align.
authors.affiliation: Center of Excellence in Bioinformatics, University at Buffalo 901 Washington Street, Buffalo, NY 14203, USA.
authors.forename: Yang
authors.initials: Y
authors.lastname: Zhang
authors.forename: Jeffrey
authors.initials: J
authors.lastname: Skolnick
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D030562:Databases, Protein; D008958:Models, Molecular; D008969:Molecular Sequence Data; D017510:Protein Folding; D016415:Sequence Alignment; D040681:Structural Homology, Protein