Assessing predictors of changes in protein stability upon mutation using self-consistency
Open accessAbstract
The ability to predict the effect of mutations on protein stability is important for a wide range of tasks, from protein engineering to assessing the impact of SNPs to understanding basic protein biophysics. A number of methods have been developed that make these predictions, but assessing the accuracy of these tools is difficult given the limitations and inconsistencies of the experimental data. We evaluate four different methods based on the ability of these methods to generate consistent results for forward and back mutations, and examine how this ability varies with the nature and location of the mutation. We find that, while one method seems to outperform the others, the ability of these methods to make accurate predictions is limited.
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A change in binding affinity of a mutation from wild-type to mutant is equivalent to the negative change in binding free energy of the hypothetical reverse mutation, from mutant to wild-type.
“Since the Gibbs free energy formulation is a thermodynamic state function a change in binding affinity of a mutation from a wild-type protein to its mutant (ΔΔGWT→MT) should be equivalent to the negative change binding free energy of the hypothetical reverse mutation, from the mutant to the wild-type protein (–ΔΔGMT→WT) (40).”
From mCSM-PPI2: predicting the effects of mutations on protein–protein interactions (2019) · cites this paper as [40]
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References 23 · Cited by 110
- Authors
- Thiltgen, G., & Goldstein, R. A.
- Affiliations
- National Institute for Medical Research (GB)
- Corresponding author
- Goldstein, Richard A.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2012-10-29
- Volume
- 7
- Issue
- 10
- Pages
- e46084
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3483175
- OpenAlex
- W2056053449
- Cited by
- 110
- References
- 23
- Citations by year
- 2026: 1 · 2025: 6 · 2024: 3 · 2023: 9 · 2022: 10 · 2021: 22 · 2020: 12 · 2019: 7 · 2018: 8 · 2017: 7 · 2016: 7 · 2015: 6 · 2014: 9 · 2013: 3
- FWCI
- 2.32
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- UCL Discovery (University College London) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Funders
- Medical Research Council
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Keywords
- protein stability, mutation effects, self-consistency, prediction accuracy, protein engineering, single nucleotide polymorphisms, protein biophysics, method comparison
- MeSH terms
- Mutation, Proteins, Thermodynamics, Reproducibility of Results, Computational Biology, Polymorphism, Single Nucleotide, Protein Stability
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