DynaMut: predicting the impact of mutations on protein conformation, flexibility and stability
Open accessAbstract
Proteins are highly dynamic molecules, whose function is intrinsically linked to their molecular motions. Despite the pivotal role of protein dynamics, their computational simulation cost has led to most structure-based approaches for assessing the impact of mutations on protein structure and function relying upon static structures. Here we present DynaMut, a web server implementing two distinct, well established normal mode approaches, which can be used to analyze and visualize protein dynamics by sampling conformations and assess the impact of mutations on protein dynamics and stability resulting from vibrational entropy changes. DynaMut integrates our graph-based signatures along with normal mode dynamics to generate a consensus prediction of the impact of a mutation on protein stability. We demonstrate our approach outperforms alternative approaches to predict the effects of mutations on protein stability and flexibility (P-value < 0.001), achieving a correlation of up to 0.70 on blind tests. DynaMut also provides a comprehensive suite for protein motion and flexibility analysis and visualization via a freely available, user friendly web server at http://biosig.unimelb.edu.au/dynamut/.
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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 [27]
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Mishra, S., Pandey, N., Rawat, A., Srivastava, D., Ray, A., & Kumar, V. (2023) · IEEE Access · doi:10.1109/access.2023.3337260
- Authors
- Rodrigues, C. H., Pires, D. E., & Ascher, D. B.
- Affiliations
- The University of Melbourne (AU)
- Fiocruz Minas (BR)
- Corresponding author
- Pires, Douglas EV
- Ascher, David B
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-04-30
- Volume
- 46
- Issue
- W1
- Pages
- W350-W355
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC6031064
- OpenAlex
- W2801491392
- Cited by
- 1,086
- References
- 49
- Citations by year
- 2026: 93 · 2025: 119 · 2024: 156 · 2023: 165 · 2022: 182 · 2021: 183 · 2020: 136 · 2019: 43 · 2018: 5 · 2013: 1
- FWCI
- 32.73
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- 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, other-oa)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Arca - Repositório Institucional da Fiocruz (submittedVersion)
- Apollo (cc-by)
- Funders
- Jack Brockhoff Foundation (JBF 4186)
- Pesquisa do Estado de Minas Gerais (MR/M026302/1)
- National Health and Medical Research Council (APP1072476)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Keywords
- mutation effect prediction, protein dynamics, protein flexibility, protein stability, normal mode analysis, vibrational entropy, consensus forecasts, protein conformation
- MeSH terms
- Mutation, Protein Conformation, Proteins, Software, Entropy, Internet, Protein Stability, Molecular Dynamics Simulation
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