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The CamSol Method of Rational Design of Protein Mutants with Enhanced Solubility
Abstract
Protein solubility is often an essential requirement in biotechnological and biomedical applications. Great advances in understanding the principles that determine this specific property of proteins have been made during the past decade, in particular concerning the physicochemical characteristics of their constituent amino acids. By exploiting these advances, we present the CamSol method for the rational design of protein variants with enhanced solubility. The method works by performing a rapid computational screening of tens of thousand of mutations to identify those with the greatest impact on the solubility of the target protein while maintaining its native state and biological activity. The application to a single-domain antibody that targets the Alzheimer's Aβ peptide demonstrates that the method predicts with great accuracy solubility changes upon mutation, thus offering a cost-effective strategy to help the production of soluble proteins for academic and industrial purposes.
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“To predict the solubility and aggregation propensity of protein, several prediction tools have been developed, such as the Camsol [25], and SOLart [26], with SOLart currently holding state-of-the-art performance.”
From Computational and artificial intelligence-based methods for antibody development (2023) · cites this paper as [25]
In the citing paper
“Good solubility is crucial [202, 203] to avoid aggregation that can potentially lead to loss of activity, degradation of antibodies or immunogenicity, as discussed previously.”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [202]
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Metadata
- Authors
- Sormanni, P., Aprile, F. A., & Vendruscolo, M.
- Affiliations
- University of Cambridge (GB)
- Corresponding author
- Vendruscolo, Michele
- Venue
- Journal of Molecular Biology
- Publisher
- Elsevier BV
- Published
- 2015-01
- Volume
- 427
- Issue
- 2
- Pages
- 478-490
- ISSN
- 0022-2836 (ISSN-L)
- OpenAlex
- W2103083136
- Cited by
- 494
- References
- 62
- Citations by year
- 2026: 52 · 2025: 77 · 2024: 60 · 2023: 42 · 2022: 62 · 2021: 59 · 2020: 44 · 2019: 33 · 2018: 28 · 2017: 20 · 2016: 9 · 2015: 7
- FWCI
- 4.92
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Molecular Biology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein purification and stability
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Keywords
- protein solubility, rational protein design, site-directed mutagenesis, nanobodies, amyloid-beta, Alzheimer's disease, soluble protein production, native state stability
- MeSH terms
- Amino Acids, Circular Dichroism, Cloning, Molecular, Computer Simulation, Escherichia coli, Models, Molecular, Protein Conformation, Recombinant Proteins, Solubility, Protein Engineering, Molecular Structure, Mutant Proteins, Chemical Phenomena
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