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The Phyre2 web portal for protein modeling, prediction and analysis
Open accessAbstract
Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which we previously published a paper in Nature Protocols. In this updated protocol, we describe Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they determine. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain composition and model quality. A range of additional available tools is described to find a protein structure in a genome, to submit large number of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2. A typical structure prediction will be returned between 30 min and 2 h after submission.
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“With the exception of the Unknown class, high confidence structural templates were identified for the vast majority of proteins for at least part of the sequence (Supplementary Fig. 2 and Supplementary Data File 3).”
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Metadata
- Authors
- Kelley, L. A., Mezulis, S., Yates, C. M., Wass, M. N., & Sternberg, M. J. E.
- Affiliations
- Imperial College London (GB)
- University College London (GB)
- University of Kent (GB)
- Corresponding author
- Kelley, Lawrence A
- Venue
- Nature Protocols
- Published
- 2015-05-07
- Volume
- 10
- Issue
- 6
- Pages
- 845-858
- ISSN
- 1750-2799 (ISSN-L)
- 1754-2189
- PMC
- PMC5298202
- OpenAlex
- W1803102843
- Cited by
- 9,652
- References
- 36
- Citations by year
- 2026: 250 · 2025: 512 · 2024: 778 · 2023: 902 · 2022: 1173 · 2021: 1401 · 2020: 1278 · 2019: 1062 · 2018: 905 · 2017: 734 · 2016: 529 · 2015: 116
- FWCI
- 331.62
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Protocols (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (publishedVersion)
- PubMed Central (acceptedVersion)
- Kent Academic Repository (University of Kent) (submittedVersion)
- Spiral (Imperial College London) (submittedVersion)
- Funders
- Medical Research Council (G1000390-1/1)
- Biotechnology and Biological Sciences Research Council (BB/F020481/1, BB/J019240/1, BB/M011526/1, BB/G003912/1, BB/G022569/1)
- 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
- Phyre2, protein structure prediction, remote homology detection, protein modeling, ligand binding site prediction, amino acid variants, non-synonymous SNPs, protein function prediction, protein domains, web server, model quality assessment
- MeSH terms
- Models, Molecular, Protein Conformation, Software, Computational Biology, Internet
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