TM-align: a protein structure alignment algorithm based on the TM-score
Open accessAbstract
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.
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Comparing the wolframin prediction for this region (median pLDDT of 86.0) to existing PDB chains identified 3F1Z as the most similar known chain (TM-score of 0.472).
“Comparing our prediction for this region (median pLDDT of 86.0) to existing PDB chains using TM-align42,57 identified 3F1Z58 as the most similar known chain (TM-score of 0.472) (Fig. 3c, magenta).”
From Highly accurate protein structure prediction for the human proteome (2021) · cites this paper as [57]
For complexes not covered by ECOD, TMalign with a cutoff of 0.5 was used to further remove similar complexes.
“For these complexes, we leveraged the TMalign software (with a cutoff of 0.5) [58] to further remove the similar complexes.”
From Deep geometric representations for modeling effects of mutations on protein-protein binding affinity (2021) · cites this paper as [58]
Most structural aligners, such as TM-align, Dali and CE, solve the alignment optimization problem by iterative or stochastic optimization.
“Most structural aligners, such as the popular TM-align, Dali and CE11,13,14, solve the alignment optimization problem by iterative or stochastic optimization.”
From Fast and accurate protein structure search with Foldseek (2024) · cites this paper as [11]
Searching with a single query structure through a database with 100 million protein structures would take TM-align a month on one CPU core, and an all-versus-all comparison would take 10 millennia on a 1,000-core cluster.
“Searching with a single query structure through a database with 100 million protein structures would take the popular TM-align11 tool a month on one CPU core, and an all-versus-all comparison would take 10 millennia on a 1,000-core cluster.”
From Fast and accurate protein structure search with Foldseek (2024) · cites this paper as [11]
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Novel machine learning approaches revolutionize protein knowledge
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- Authors
- Zhang, Y.
- Affiliations
- University at Buffalo, State University of New York (US)
- Corresponding author
- Zhang, Y.
- ORCID
- Zhang, Y.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-04-11
- Volume
- 33
- Issue
- 7
- Pages
- 2302-2309
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC1084323
- OpenAlex
- W2102245393
- Cited by
- 3,774
- References
- 38
- Citations by year
- 2026: 362 · 2025: 459 · 2024: 405 · 2023: 310 · 2022: 314 · 2021: 266 · 2020: 200 · 2019: 183 · 2018: 148 · 2017: 148 · 2016: 158 · 2015: 141 · 2014: 120 · 2013: 136 · 2012: 103
- FWCI
- 10.67
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- other-oa
- Locations
- Nucleic Acids Research (publishedVersion, other-oa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- SMARTech Repository (Georgia Institute of Technology) (submittedVersion)
- Funders
- National Institutes of Health
- National Institute of General Medical Sciences (GM 37408, R01GM037408, GM-48835, R01GM048835)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- protein structure alignment, TM-score, TM-align, structural similarity, protein folding prediction, model selection, Protein Data Bank, structural analogues
- MeSH terms
- Algorithms, Amino Acid Sequence, Models, Molecular, Molecular Sequence Data, Sequence Alignment, Protein Folding, Databases, Protein, Structural Homology, Protein
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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