The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Protein Function Prediction Using Local 3D Templates
Abstract
The prediction of a protein's function from its 3D structure is becoming more and more important as the worldwide structural genomics initiatives gather pace and continue to solve 3D structures, many of which are of proteins of unknown function. Here, we present a methodology for predicting function from structure that shows great promise. It is based on 3D templates that are defined as specific 3D conformations of small numbers of residues. We use four types of template, covering enzyme active sites, ligand-binding residues, DNA-binding residues and reverse templates. The latter are templates generated from the target structure itself and scanned against a representative subset of all known protein structures. Together, the templates provide a fairly thorough coverage of the known structures and ensure that if there is a match to a known structure it is unlikely to be missed. A new scoring scheme provides a highly sensitive means of discriminating between true positive and false positive template matches. In all, the methodology provides a powerful new tool for function prediction to complement those already in use.
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In the citing paper
“Conserved local conformations of specific residues can be used to identify important functions, such as enzyme activity, ion or ligand binding beyond global sequence and fold similarities38.”
From A structural biology community assessment of AlphaFold2 applications (2022) · cites this paper as [38]
In the citing paper
“A scan of 400 auto-generated 3-residue templates from the AF2-predicted structure against representative structures in the PDB (reverse template comparison38) yielded a possible 3-residue template match: PDB entry 4ZYO (EC 1.14.19.1, human stearoyl-CoA desaturase39, Fig. 4d).”
From A structural biology community assessment of AlphaFold2 applications (2022) · cites this paper as [38]
Citations
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Self-citationProFunc: a server for predicting protein function from 3D structure
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Research works printed but not linked: 1
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Corrêa, L. D. L., & Dorn, M. (2019) · IGI Global eBooks · doi:10.4018/978-1-5225-8903-7.ch040
Djeddi, W. E., Yahia, S. B., & Nguifo, E. M. (2020) · doi:10.21203/rs.2.21071/v3
Characterization and Classification of Local Protein Surfaces Using Self-Organizing Map
Sael, L., & Kihara, D. (2013) · IGI Global eBooks · doi:10.4018/978-1-4666-1785-8.ch004
Novel techniques for protein structure characterization using graph representation of proteins
Küçükural, A. (2008) · Sabanci University
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20 Years of the ISCB Student Council Symposium: shaping computational biology and future leaders
Fernandez-Martin, M., Castillo-Orozco, A., Poley-Gil, M., Pose-Lagoa, I., Urquiza-Zurich, S., Hayoun-Mya, O., Reyes, D. M., Treccani, M., Veschetti, L., Carvajal-Agudelo, J. D., et al. (2026) · Bioinformatics Advances · doi:10.1093/bioadv/vbag097
Investigating enzyme function by geometric matching of catalytic motifs
Hackett, R., Riziotis, I. G., Larralde, M. F., Ribeiro, A. J. M., Zeller, G., & Thornton, J. M. (2026) · Protein Science · doi:10.1002/pro.70744
Self-citation
Metadata
- Authors
- Laskowski, R. A., Watson, J. D., & Thornton, J. M.
- Affiliations
- European Bioinformatics Institute (GB)
- Corresponding author
- Thornton, Janet M.
- Venue
- Journal of Molecular Biology
- Publisher
- Elsevier BV
- Published
- 2005-08
- Volume
- 351
- Issue
- 3
- Pages
- 614-626
- ISSN
- 0022-2836 (ISSN-L)
- OpenAlex
- W2088534163
- Cited by
- 213
- References
- 38
- Citations by year
- 2026: 6 · 2025: 1 · 2024: 2 · 2023: 5 · 2022: 4 · 2021: 10 · 2020: 6 · 2019: 2 · 2018: 2 · 2017: 8 · 2016: 6 · 2015: 8 · 2014: 11 · 2013: 10 · 2012: 15
- FWCI
- 8.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Molecular Biology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- European Commission
- National Institute of General Medical Sciences (P50GM062414, GM62414)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Keywords
- protein function prediction, 3D templates, enzyme active site, ligand binding residues, DNA-binding residues, template matching, scoring system, structural genomics
- MeSH terms
- Models, Molecular, Protein Conformation, Proteins, Structure-Activity Relationship
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