TM-align: a protein structure alignment algorithm based on the TM-score

TLDR

TM-align is a new algorithm that identifies optimal structural alignments between protein pairs by combining the TM‑score rotation matrix with dynamic programming. TM-align uses the TM‑score rotation matrix and dynamic programming to align protein pairs, and it was applied to an all‑against‑all comparison of 10 515 PDB chains (sequence identity <95%) revealing 1996 distinct folds at a TM‑score threshold of 0.5, while also matching TASSER‑predicted models of non‑homologous proteins. TM-align is roughly four times faster than CE and twenty times faster than DALI and SAL, produces alignments with higher accuracy and coverage, consistently finds close analogs for both folded and misfolded models (average RMSD 3 Å, 87 % coverage), and its strong correlation between model correctness and structural similarity can aid blind protein structure prediction. TM-align is freely available for download at http://bioinformatics.buffalo.edu/TM-align.

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 ∼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 Å 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 .