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Reciprocal Best Structure Hits: Using AlphaFold models to discover distant homologues
Open accessPreprint — published as 10.1093/bioadv/vbac072 · Paper page
Abstract
1 The conventional methods to detect homologous protein pairs use the comparison of protein sequences. But the sequences of two homologous proteins may diverge significantly and consequently may be undetectable by standard approaches. The release of the AlphaFold 2.0 software enables the prediction of highly accurate protein structures and opens many opportunities to advance our understanding of protein functions, including the detection of homologous protein structure pairs. In this proof-of-concept work, we search for the closest homologous protein pairs using the structure models of five model organisms from the AlphaFold database. We compare the results with homologous protein pairs detected by their sequence similarity and show that the structural matching approach finds a similar set of results. Additionally, we detect potential novel homologues solely with the structural matching approach, which can help to understand the function of uncharacterised proteins and make previously overlooked connections between well-characterised proteins. We also observe limitations of our implementation of the structure based approach, particularly when handling highly disordered proteins or short protein structures. Our work shows that high accuracy protein structure models can be used to discover homologous protein pairs, and we expose areas for improvement of this structural matching approach.
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Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
Highly accurate protein structure prediction for the human proteome
Tunyasuvunakool, K., Adler, J., Wu, Z., Green, T., Zielinski, M., Žídek, A., Bridgland, A., Cowie, A., Meyer, C., Laydon, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03828-1 · Cited by 3,025
Self-citationAlphaFold and Implications for Intrinsically Disordered Proteins
Ruff, K. M., & Pappu, R. V. (2021) · Journal of Molecular Biology · doi:10.1016/j.jmb.2021.167208 · Cited by 635
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Metadata
- Authors
- Monzon, V., Paysan-Lafosse, T., Wood, V., & Bateman, A.
- Affiliations
- European Bioinformatics Institute (GB)
- University of Cambridge (GB)
- Corresponding author
- Monzon, Vivian
- Venue
- Bioinformatics Advances
- Publisher
- openRxiv
- Published
- 2022-07-04
- Volume
- 2
- Issue
- 1
- Pages
- vbac072-vbac072
- ISSN
- 2635-0041 (ISSN-L)
- PMC
- PMC9666668
- OpenAlex
- W4303184143
- Cited by
- 46
- References
- 3
- Citations by year
- 2026: 6 · 2025: 5 · 2024: 13 · 2023: 16 · 2022: 6
- FWCI
- 3.27
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Bioinformatics Advances (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, public-domain)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Apollo (University of Cambridge) (submittedVersion)
- Apollo
- Funders
- Wellcome Trust (218236/Z/19/Z, 218236)
- Biotechnology and Biological Sciences Research Council (BB/S020381/1)
- 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 › Genomics and Phylogenetic Studies
- Keywords
- AlphaFold, protein structure prediction, sequence divergence, protein function prediction, protein disorder, model organisms
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