Evidence map›Paper›PMID 42398027›Full record

ArticleBioinformatics (Oxford, England)2026

TEDLH: domain HMMs for sensitive detection of remote homologues.

Claudia Alvarez-Carreño, Anton S Petrov, Vaishali P Waman, Ian Sillitoe, Christine Orengo

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Claudia Alvarez-CarreñoDepartment of Structural and Molecular Biology, University College London, London, WC1E 6BT, United Kingdom.ORCID 0000-0002-1827-8946
Anton S PetrovNASA Center for the Origin of Life, Georgia Institute of Technology, Atlanta, GA 30332, United States.ORCID 0000-0003-3359-7299
Vaishali P WamanDepartment of Structural and Molecular Biology, University College London, London, WC1E 6BT, United Kingdom.ORCID 0000-0001-5627-8827
Ian SillitoeDepartment of Structural and Molecular Biology, University College London, London, WC1E 6BT, United Kingdom.ORCID 0000-0003-1091-9144
Christine OrengoDepartment of Structural and Molecular Biology, University College London, London, WC1E 6BT, United Kingdom.

Funding

Royal Society Newton International Fellowship NIF\R1\231037
6 · The paper itself

Abstract

motivationThe Encyclopedia of Domains (TED) provides domain annotations for proteins in the AlphaFold Protein Structure Database (AFDB) using a consensus of three state-of-the-art structure-based methods. We used these annotations to construct profile Hidden Markov models (HMMs), collectively forming the TED Library of HMMs (TEDLH). TEDLH enables sensitive sequence and profile searches, supporting systematic exploration of protein domain families and their evolutionary relationships.

resultsTEDLH links 934,186 domain HMMs to experimentally determined CATH-PDB structures through direct (primary) and transitive (secondary and tertiary) relationships. Fewer than half of TEDLH HMMs are directly linked to a CATH-PDB domain; the remaining models are connected through transitive relationships. These transitive links extend coverage into more divergent regions of sequence space and better represent CATH superfamily diversity. HMM-HMM comparisons within CATH superfamily 3.30.70.100 illustrate how transitive relationships expand sequence coverage. In this superfamily, 5640 TEDLH HMMs are connected to 173 CATH-PDB representatives. Primary, secondary, and tertiary relationships progressively capture more divergent sequences (pairwise sequence identity <20%) that retain structural similarity (TM-score ≥0.6) and a conserved two-layer α/β sandwich core fold. All-against-all HMM-HMM comparisons across TEDLH also reveal sequence similarities across the CATH hierarchy (cross-hits). At low query coverage (<50%), cross-hits are more frequent between CATH classes, architectures and topologies, whereas at higher coverage thresholds (≥70%) they predominantly occur between superfamilies. These cross-hits are not driven by superfamily size or sequence diversity and can provide guidance for CATH curation. As an example, analysis of cross-hits between superfamilies 2.170.130.30 and 3.10.20.30 reveals evolutionary relationships between these groups. AVAILABILITY: TEDLH is compatible with HH-suite3 and is available from FigShare https://doi.org/10.6084/m9.figshare.28531754 for local use.

Indexed as

Computational BiologyProtein DomainsProteinsSoftwareDatabases, ProteinHidden Markov ModelsProteins

Identifiers

PMID42398027
PMCPMC13385337

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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.