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Platinum: a database of experimentally measured effects of mutations on structurally defined protein-ligand complexes
Open accessAbstract
Drug resistance is a major challenge for the treatment of many diseases and a significant concern throughout the drug development process. The ability to understand and predict the effects of mutations on protein-ligand affinities and their roles in the emergence of resistance would significantly aid treatment and drug design strategies. In order to study and understand the impacts of missense mutations on the interaction of ligands with the proteome, we have developed Platinum (http://structure.bioc.cam.ac.uk/platinum). This manually curated, literature-derived database, comprising over 1000 mutations, associates for the first time experimental information on changes in affinity with three-dimensional structures of protein-ligand complexes. To minimize differences arising from experimental techniques and to directly compare binding affinities, Platinum considers only changes measured by the same group and with the same amino-acid sequence used for structure determination, providing a direct link between protein structure, how a ligand binds and how mutations alter the affinity of the ligand of the protein. We believe Platinum will be an invaluable resource for understanding the effects of mutations that give rise to drug resistance, a major problem emerging in pandemics including those caused by the influenza virus, in infectious diseases such as tuberculosis, in cancer and in many other life-threatening illnesses.
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The graph-based signatures concept has proven to be a powerful approach and has been widely applied to the study of protein structure, including how mutations alter protein stability, dynamics and interactions with other molecules.
“Our previously described graph-based signatures concept has proven to be a powerful approach and has been widely applied to the study of protein structure, including how mutations alter protein stability (20,26), dynamics (27) and interactions with other molecules (20,28–34).”
From mCSM-PPI2: predicting the effects of mutations on protein–protein interactions (2019) · cites this paper as [34]
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Metadata
- Authors
- Pires, D. E. V., Blundell, T. L., & Ascher, D. B.
- Affiliations
- University of Cambridge (GB)
- Corresponding author
- Ascher, David B.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-10-16
- Volume
- 43
- Issue
- D1
- Pages
- D387-D391
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC4384026
- OpenAlex
- W2125359610
- Cited by
- 91
- References
- 30
- Citations by year
- 2026: 5 · 2025: 5 · 2023: 11 · 2022: 8 · 2021: 3 · 2020: 14 · 2019: 12 · 2018: 8 · 2017: 13 · 2016: 11 · 2015: 1
- FWCI
- 8.62
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nucleic Acids Research (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Funders
- Wellcome Trust
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- National Health and Medical Research Council (1072476)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Interaction Studies and Fluorescence Analysis
- Keywords
- missense mutations, protein-ligand binding affinity, drug resistance, protein-ligand complex, structure-based drug design, influenza virus, tuberculosis, cancer
- MeSH terms
- Ligands, Mutation, Protein Binding, Proteins, Drug Design, Internet, Databases, Protein
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