Cited by 494Protein Structure and DynamicsProtein purification and stabilityEnzyme Structure and Function

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The CamSol Method of Rational Design of Protein Mutants with Enhanced Solubility

Sormanni, Pietro, Aprile, Francesco A., Vendruscolo, Michele·2015·Journal of Molecular Biology

DOI 10.1016/j.jmb.2014.09.026

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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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Background
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Background
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BackgroundInfluential
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Background
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Influential
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Self-citation
The uniqueness of flow in probing the aggregation behavior of clinically relevant antibodies
Willis, L. F., Kumar, A., Jain, T. S., Caffry, I., Xu, Y., Radford, S. E., Kapur, N., Vásquez, M., & Brockwell, D. J. (2020) · Engineering Reports · doi:10.1002/eng2.12147 · Cited by 8
Cancer-Associated Substitutions in RNA Recognition Motifs of PUF60 and U2AF65 Reveal Residues Required for Correct Folding and 3′ Splice-Site Selection
Královičová, J., Borovská, I., Kubíčková, M., Lukavsky, P. J., & Vořechovský, I. (2020) · Cancers · doi:10.3390/cancers12071865 · Cited by 10
“Both L140P and A231P were resistant to TEV protease cleavage (Figure S7) and were predicted to alter solubility and protein stability by CamSol [27] and the mutation cutoff scanning matrix [28], respectively (Figure S8).”
BackgroundMethod
Prediction of Protein Aggregation and Amyloid Formation
Graña‐Montes, R., Pujols, J., Gómez-Picanyol, C., & Ventura, S. (2017) · Springer eBooks · doi:10.1007/978-94-024-1069-3_7 · Cited by 10
Energy Landscapes and Heat Capacity Signatures for Monomers and Dimers of Amyloid-Forming Hexapeptides
Nicy, & Wales, D. J. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms241310613 · Cited by 9
“Another predictor that can be useful to estimate amyloid formation propensity is CamSol86.”
BackgroundInfluential
Predictive Model Building for Aggregation Kinetics Based on Molecular Dynamics Simulations of an Antibody Fragment
Wang, Y., Williams, H. D., Dikicioǧlu, D., & Dalby, P. A. (2024) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.4c00859 · Cited by 9
A review on computational models for predicting protein solubility
Pimtawong, T., Ren, J., Lee, J., Lee, H., & Na, D. (2025) · The Journal of Microbiology · doi:10.71150/jm.2408001 · Cited by 9
“Additionally, when applied to the Camsol mutation data-set, consisting of 19 proteins with 56 variants from various organisms (excluding E. coli ) (Sormanni et al., 2015), NetSolP achieved an accuracy of 0.66.”
Influential
Bystander editing by adenine base editors impairs vision restoration in a mouse model of Leber congenital amaurosis
Lee, S., Wu, J., Im, D., Hwang, G., Jeong, Y. K., Jiang, H., Lee, S. J., Jo, D. H., Goddard, W. A., Kim, J. H., et al. (2025) · Molecular Therapy — Methods & Clinical Development · doi:10.1016/j.omtm.2025.101461 · Cited by 13
Prediction of aggregation in monoclonal antibodies from molecular surface curvature
Knez, B., Erzin, L., Kos, Ž., Kuzman, D., & Ravnik, M. (2025) · Scientific Reports · doi:10.1038/s41598-025-13527-w · Cited by 10
Exploration of Comprehensive Structural and Functional Potential of Recombinant Proteins Using Cutting-Edge Bioinformatics Tools
Shad, M., Liaqat, A., Nazir, A., Hussain, N., Yaqoob, K., Akhtar, M., & Sajjad, M. (2025) · Applied Biochemistry and Biotechnology · doi:10.1007/s12010-025-05366-2 · Cited by 9
“SOLpro (2007) [65], SPINE-D (2007) [66], SOLVE (2008), CamSol (2011) [67], PROSO II (2012) [68], CCSOL (2012) [69], Solubility Predictor (2014), Protein-Sol (2016) [70], DeepSol (2018), and SoluProt (2020) [71] are some of the computational tools that have been developed to predict protein…”
RP3Net: a deep learning model for predicting recombinant protein production in Escherichia coli
Tankhilevich, E., Cuesta, S. M., Barrett, I. P., Berg, C., Schiavone, L. H., & Leach, A. R. (2026) · Bioinformatics · doi:10.1093/bioinformatics/btag003 · Cited by 11
“CamSol (Sormanni et al. 2015, Sormanni et al. 2017) is a well-established relative solubility prediction tool for libraries of similar protein sequences.”
Rational design of a Nivolumab-based ANTI-PD-1 single chain variable fragment that blocks the interaction between PD-1 expressed on T-CELLS and PD-L1 ON CHO cells
Shin, J., Raissi, S., Phelan, P., & Bullock, P. A. (2022) · Protein Expression and Purification · doi:10.1016/j.pep.2022.106196 · Cited by 9
Analysis of Sheep and Goat IAPP Provides Insight into IAPP Amyloidogenicity and Cytotoxicity
Miller, M. E. T., Li, M., Baghai, A., Peetz, V. H., Zhyvoloup, A., & Raleigh, D. P. (2022) · Biochemistry · doi:10.1021/acs.biochem.2c00470 · Cited by 9
Amyloid β accelerates age-related proteome-wide protein insolubility
Anderton, E., Chamoli, M., Bhaumik, D., King, C. D., Xie, X., Foulger, A., Andersen, J. K., Schilling, B., & Lithgow, G. J. (2024) · GeroScience · doi:10.1007/s11357-024-01169-1 · Cited by 10
“Similarly, using the Cam-Sol solubility prediction score [47] we found that the CIP had a significantly higher median solubility prediction than the reference proteome (Fig.”
Method
Dissecting the Structural Organization of Multiprotein Amyloid Aggregates Using a Bottom-Up Approach
Chaudhary, H., Meister, S. W., Zetterberg, H., Löfblom, J., & Lendel, C. (2020) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.0c00110 · Cited by 9
“Far-UV CD spectroscopy of the Aβ(1-40) and Aβ(1-42) amyloid fibril samples was measured with 1:8 dilution in sodium phosphate buffer pH 7.”
Influential
SUMO: In Silico Sequence Assessment Using Multiple Optimization Parameters
Evers, A., Malhotra, S., Bolick, W.-G., Najafian, A., Borisovska, M., Warszawski, S., Fomekong‐Nanfack, Y., Kühn, D., Rippmann, F., Crespo, A., et al. (2023) · Methods in molecular biology · doi:10.1007/978-1-0716-3279-6_22 · Cited by 9
The diversity of SNCA transcripts in neurons, and its impact on antisense oligonucleotide therapeuticsPreprint
Evans, J. R., Gustavsson, E. K., Doykov, I., Murphy, D. P., Virdi, G. S., Lachica, J., Röntgen, A., Murtada, M. H., Pang, C. W., Macpherson, H. L., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.05.30.596437 · Cited by 9
“33,34 Residue-specific solubility profiles were plotted using GraphPad Prism Version 10.2.0, with higher values indicating greater predicted solubility, and lower values indicating poorer predicted solubility, respectively.”
BackgroundMethodInfluentialSelf-citation
Aggregation Limiting Cell-Penetrating Peptides Derived from Protein Signal Sequences
Porosk, L., Härk, H. H., Bicev, R. N., Gaidutšik, I., Nebogatova, J., Armolik, E.-J., Arukuusk, P., da Silva, E. R., & Langel, Ü. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24054277 · Cited by 8
“html (accessed on 1 September 2021) [52,53] and Peptide Property Calculator ver 3.”
Background
AA amyloidosis in vertebrates: epidemiology, pathology and molecular aspects
Moccia, V., Tucciarone, C. M., Garutti, S., Milazzo, M., Ferri, F., Palizzotto, C., Mazza, M., Basset, M., Zini, E., Ricagno, S., et al. (2024) · Amyloid · doi:10.1080/13506129.2024.2417219 · Cited by 8
Elucidating the regulatory mechanism of Swi1 prion in global transcription and stress responses
Du, Z., Regan, J. M., Bartom, E. T., Wu, W.-S., Zhang, L., Goncharoff, D. K., & Li, L. (2020) · Scientific Reports · doi:10.1038/s41598-020-77993-0 · Cited by 8
On the evolution of chaperones and co-chaperones and the exponential expansion of proteome complexityPreprint
Rebeaud, M. E., Mallik, S., Goloubinoff, P., & Tawfik, D. S. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.06.08.140319 · Cited by 7
solPredict: Antibody Apparent Solubility Prediction from Sequence by Transfer LearningPreprint
Feng, J., Jiang, M., Shih, J., & Chai, Q. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.12.07.471655 · Cited by 8
ProG-SOL: Predicting Protein Solubility Using Protein Embeddings and Dual-Graph Convolutional Networks
Li, G., Zhang, N., & Fan, L. (2025) · ACS Omega · doi:10.1021/acsomega.4c09688 · Cited by 7
Improvement of the Antimicrobial Peptide Activity by Means of Chitosan‐Based Nanoparticles
Gálvez-Rodríguez, S., Asensio‐Calavia, P., Otazo‐Pérez, A., Abad‐Chico, P., de la Lastra, J. M. P., & Pérez‐Herrero, E. (2025) · Biotechnology Journal · doi:10.1002/biot.70062 · Cited by 7
Generation of bispecific antibodies by structure-guided redesign of IgG constant regions
Iwasaki, Y. W., Tharakaraman, K., Subramanian, V., Khongmanee, A., Hatas, A., Fleischer, E., Rurak, T. T., Ngok-ngam, P., Tit-oon, P., Ruchirawat, M., et al. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2022.1063002 · Cited by 7
“CamSol has been successfully employed for rational design of protein variants having improved solubility (26).”
MethodInfluential
Amyloid Aggregation Is Potently Slowed Down by Osmolytes Due to Compaction of Partially Folded State
Garfagnini, T., Bemporad, F., Harries, D., Chiti, F., & Friedler, A. (2023) · Journal of Molecular Biology · doi:10.1016/j.jmb.2023.168281 · Cited by 7
Extensive antibody search with whole spectrum black-box optimization
Tučs, A., Ito, T., Kurumida, Y., Kawada, S., Nakazawa, H., Saitō, Y., Umetsu, M., & Tsuda, K. (2024) · Scientific Reports · doi:10.1038/s41598-023-51095-z · Cited by 8
Study of the interaction between a novel, protein-stabilizing dipeptide and Interferon-alpha-2a by construction of a Markov state model from molecular dynamics simulations
Tosstorff, A., Peters, G. H. J., & Winter, G. (2020) · European Journal of Pharmaceutics and Biopharmaceutics · doi:10.1016/j.ejpb.2020.01.020 · Cited by 7
“Identification of aggregation prone regions Three different methods were used to identify aggregation prone regions on the surface of Interferonalpha-2A: Aggrescan3D[32], AggScore[33] and CamSol[34].”
MethodInfluential
Development of a fast screening method for selecting excipients in formulations using MD simulations, NMR and microscale thermophoresis
Indrakumar, S., Zalar, M., Tschammer, N., Pohl, C., Nørgaard, A., Streicher, W. W., Harris, P., Golovanov, A. P., & Peters, G. H. J. (2020) · European Journal of Pharmaceutics and Biopharmaceutics · doi:10.1016/j.ejpb.2020.10.015 · Cited by 7
“The residue is colored red if it is predicted as aggregation prone by any one of the webservers (AGGRESCAN3D[26], CAMSOL[27], CSSP[43]).”
MethodInfluential
Peptide-based inhibitors of Tau aggregation as a potential therapeutic for Alzheimer’s disease and other TauopathiesPreprint
Aggidis, A., Chatterjee, S., Townsend, D. J., Fullwood, N. J., Ortega, E. R., Tarutani, A., Hasegawa, M., Lucas, H., Mudher, A. K., & Allsop, D. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.06.04.447069 · Cited by 9
“The peptide (306)VQIVYK(311) was favoured as it is present in all Tau isoforms and shares similarity to (275)VQIINK(280) which might promote binding to both targets [45].”
Background
Protein Properties
Tomii, K. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-809633-8.20266-5 · Cited by 7
In silico energetic and molecular dynamic simulations studies demonstrate potential effect of the point mutations with implications for protein engineering in BDNF
M., D. D. V., Arumugam, N., Almansour, A. I., Sivaramakrishnan, V., & Kanchi, S. (2024) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2024.132247 · Cited by 7
AggNet : Advancing protein aggregation analysis through deep learning and protein language model
He, W., Xu, X., Li, H., Zhou, J., & Gao, X. (2025) · Protein Science · doi:10.1002/pro.70031 · Cited by 6
RESP2: An Uncertainty Aware Multi‐Target Multi‐Property Optimization AI Pipeline for Antibody Discovery
Parkinson, J., Hard, R. L., Ko, Y. S., & Wang, W. (2025) · Advanced Science · doi:10.1002/advs.202504350 · Cited by 7
A novel alpha-synuclein G14R missense variant is associated with atypical neuropathological features
Brücke, C., Al‐Azzani, M., Ramalingam, N., Ramón, M., Sousa, R. L., Buratti, F. A., Zech, M., Sicking, K., Amaral, L., Gelpí, E., et al. (2025) · Molecular Neurodegeneration · doi:10.1186/s13024-025-00889-y · Cited by 10
“An additional positive charge is expected to increase G14R solubility and arginine has been used in several studies to suppress aggregation [83–87].”
Two physics‐based models for pH ‐dependent calculations of protein solubility
Spassov, V. Z., Kemmish, H., & Yan, L. (2022) · Protein Science · doi:10.1002/pro.4299 · Cited by 5
“The ESM method is implemented in the existing Calculate Protein Formulation Properties Discovery Studio protocol, along with calculations of the developability index,3 DI and viscosity scores.7 Although our structurebased approach requires protein 3D structures as input to the calculation, the results are more accurat…”
Method
In silico screening and heterologous expression of soluble dimethyl sulfide monooxygenases of microbial origin in Escherichia coli
Karaiyan, P., Chang, C. C. H., Chan, E., Tey, B. T., Ramanan, R. N., & Ooi, C. W. (2022) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-022-12008-8 · Cited by 6
“Apart from bioinformatic tools involving the information at gene level, numerous machine learningbased methods have been developed to predict the solubility of protein, based on its amino acid sequence (Agostini et al. 2014; Habibi et al. 2014; Hebditch et al. 2017; Hon et al. 2021; Khurana et al. 2018; Madani et al.…”
Method
Predicting small molecules solubility on endpoint devices using deep ensemble neural networks
Ramos, M. C., & White, A. D. (2024) · Digital Discovery · doi:10.1039/d3dd00217a · Cited by 6
“[1] The solubility of molecules is essential in many chemistry-related fields, including drug development[2–5], protein design[6], chemical[7, 8] and separation[9] processes.”
Background
ProSol-multi: Protein solubility prediction via amino acids multi-level correlation and discriminative distribution
Ghafoor, H., Asim, M. N., Ibrahim, M. A., & Dengel, A. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e36041 · Cited by 6
“In the classiﬁcation category, predictors analyze amino acids distribution patterns and utilize these patterns to categorize proteins into either soluble or insoluble classes [95,106].”
Influential
Biomimetic androgen receptor-based AIE biosensor for detecting bisphenol analogues: An integrating in silico topological analysis, molecular docking, and experimental validation study
Li, N., Liu, X., Bian, C., Ren, C., Hu, Q., Yang, Z., Xiao, L., & Guan, T. (2024) · Talanta · doi:10.1016/j.talanta.2024.126827 · Cited by 6

Authors: Sormanni, P., Aprile, F. A., & Vendruscolo, M.
Affiliations: University of Cambridge (GB)
Corresponding author: Vendruscolo, Michele
ORCID: Sormanni, Pietro
Aprile, Francesco A.
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)
DOI: 10.1016/j.jmb.2014.09.026
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
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
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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The CamSol Method of Rational Design of Protein Mutants with Enhanced Solubility

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