ArticleIEEE/ACM transactions on computational biology and bioinformatics
Touring protein space with Matt.
Article in IEEE/ACM transactions on computational biology and bioinformatics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 19 citations in OpenAlex.
- A review of visualisations of protein fold networks and their relationship with sequence and function.Biological reviews of the Cambridge Philosophical Society · 2023Review
- Correlations between alignment gaps and nucleotide substitution or amino acid replacement.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Bridging the gaps in statistical models of protein alignment.Bioinformatics (Oxford, England) · 2022Article
- MAFFT-DASH: integrated protein sequence and structural alignment.Nucleic acids research · 2019Article
- Evaluating Statistical Multiple Sequence Alignment in Comparison to Other Alignment Methods on Protein Data Sets.Systematic biology · 2019Article
- Global view of the protein universe.Proceedings of the National Academy of Sciences of the United States of America · 2014Article
- Automatic classification of protein structures using low-dimensional structure space mappings.BMC bioinformatics · 2014Article
- Formatt: Correcting protein multiple structural alignments by incorporating sequence alignment.BMC bioinformatics · 2012Article
- SMURFLite: combining simplified Markov random fields with simulated evolution improves remote homology detection for beta-structural proteins into the twilight zone.Bioinformatics (Oxford, England) · 2012Article
- Touring protein space with Matt.IEEE/ACM transactions on computational biology and bioinformaticsArticle
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Using the Matt structure alignment program, we take a tour of protein space, producing a hierarchical clustering scheme that divides protein structural domains into clusters based on geometric dissimilarity. While it was known that purely structural, geometric, distance-based measures of structural similarity, such as Dali/FSSP, could largely replicate hand-curated schemes such as SCOP at the family level, it was an open question as to whether any such scheme could approximate SCOP at the more distant superfamily and fold levels. We partially answer this question in the affirmative, by designing a clustering scheme based on Matt that approximately matches SCOP at the superfamily level, and demonstrates qualitative differences in performance between Matt and DaliLite. Implications for the debate over the organization of protein fold space are discussed. Based on our clustering of protein space, we introduce the Mattbench benchmark set, a new collection of structural alignments useful for testing sequence aligners on more distantly homologous proteins.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.