AlloMAPS 2: allosteric fingerprints of the AlphaFold and Pfam-trRosetta predicted structures for engineering and design
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AlloMAPS 2 is an update of the Allosteric Mutation Analysis and Polymorphism of Signalling database, which contains data on allosteric communication obtained for predicted structures in the AlphaFold database (AFDB) and trRosetta-predicted Pfam domains. The data update contains Allosteric Signalling Maps (ASMs) and Allosteric Probing Maps (APMs) quantifying allosteric effects of mutations and of small probe binding, respectively. To ensure quality of the ASMs and APMs, we performed careful and accurate selection of protein sets containing high-quality predicted structures in both databases for each organism/structure, and the data is available for browsing and download. The data for remaining structures are available for download and should be used at user's discretion and responsibility. We believe these massive data can facilitate both diagnostics and drug design within the precision medicine paradigm. Specifically, it can be instrumental in the analysis of allosteric effects of pathological and rescue mutations, providing starting points for fragment-based design of allosteric effectors. The exhaustive character of allosteric signalling and probing fingerprints will be also useful in future developments of corresponding machine learning applications. The database is freely available at: http://allomaps.bii.a-star.edu.sg.
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Systematic annotation of putative allosteric binding cavities is possible and has already been attempted on a proteome-wide scale.
“Systematic annotation of putative allosteric binding cavities is also possible, and has already been attempted on a proteome-wide scale.267”
From Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence (2023) · cites this paper as [267]
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Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence
Duran-Frigola, M., Cigler, M., & Winter, G. E. (2023) · Journal of the American Chemical Society · doi:10.1021/jacs.2c11098 · Cited by 50 · see citing works
- Authors
- Tan, Z. W., Tee, W.-V., Guarnera, E., & Berezovsky, I. N.
- Affiliations
- Agency for Science, Technology and Research (SG)
- Corresponding author
- Berezovsky, Igor N
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2022-09-28
- Volume
- 51
- Issue
- D1
- Pages
- D345-D351
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC9825619
- OpenAlex
- W4297460855
- Cited by
- 28
- References
- 43
- Citations by year
- 2026: 6 · 2025: 10 · 2024: 6 · 2023: 6
- FWCI
- 1.80
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Agency for Science, Technology and Research (C210812031)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Receptor Mechanisms and Signaling
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- allosteric communication, AlloMap, AlphaFold, Pfam domains, protein structure prediction, mutation effects, protein engineering, fragment-based drug discovery, precision medicine, protein polymorphism
- MeSH terms
- Allosteric Regulation, Mutation, Proteins, Drug Design, Signal Transduction, Databases, Protein
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