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CSM-lig: a web server for assessing and comparing protein-small molecule affinities
Open accessAbstract
Determining the affinity of a ligand for a given protein is a crucial component of drug development and understanding their biological effects. Predicting binding affinities is a challenging and difficult task, and despite being regarded as poorly predictive, scoring functions play an important role in the analysis of molecular docking results. Here, we present CSM-Lig (http://structure.bioc.cam.ac.uk/csm_lig), a web server tailored to predict the binding affinity of a protein-small molecule complex, encompassing both protein and small-molecule complementarity in terms of shape and chemistry via graph-based structural signatures. CSM-Lig was trained and evaluated on different releases of the PDBbind databases, achieving a correlation of up to 0.86 on 10-fold cross validation and 0.80 in blind tests, performing as well as or better than other widely used methods. The web server allows users to rapidly and automatically predict binding affinities of collections of structures and assess the interactions made. We believe CSM-lig would be an invaluable tool for helping assess docking poses, the effects of multiple mutations, including insertions, deletions and alternative splicing events, in protein-small molecule affinity, unraveling important aspects that drive protein-compound recognition.
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“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 [32]
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Metadata
- Authors
- Pires, D. E. V., & Ascher, D. B.
- Affiliations
- Fiocruz Minas (BR)
- The University of Melbourne (AU)
- Corresponding author
- Pires, Douglas E.V.
- Ascher, David B.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-05-05
- Volume
- 44
- Issue
- W1
- Pages
- W557-W561
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC4987933
- OpenAlex
- W2346940354
- Cited by
- 115
- References
- 29
- Citations by year
- 2026: 4 · 2025: 6 · 2024: 11 · 2023: 7 · 2022: 8 · 2021: 16 · 2020: 26 · 2019: 13 · 2018: 13 · 2017: 8 · 2016: 3
- FWCI
- 11.35
- 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)
- Americanae (AECID Library) (submittedVersion, other-oa)
- Arca - Repositório Institucional da Fiocruz (submittedVersion, other-oa)
- HighWire Press Open Archive (submittedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, other-oa)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Funders
- Research Councils UK
- Fundação de Amparo à Pesquisa do Estado de Minas Gerais
- Fundação Oswaldo Cruz
- Conselho Nacional das Fundações Estaduais de Amparo à Pesquisa
- Medical Research Council
- 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 › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Interaction Studies and Fluorescence Analysis
- Keywords
- protein-ligand binding affinity prediction, scoring functions, molecular docking, PDBbind, web server, protein mutations, alternative splicing, drug development
- MeSH terms
- Ligands, Mutation, Protein Binding, Proteins, Software, Substrate Specificity, User-Computer Interface, Reproducibility of Results, Internet, Databases, Protein, Small Molecule Libraries, Molecular Docking Simulation, Datasets as Topic
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