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Solubility prediction tools

LP Leonardo Pellizza
CS Clara Smal
GR Guido Rodrigo
MA Martín Arán
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All prediction tools used provide open accessibility. The URL addresses to access Protein-Sol7, CCSOL8, SOLpro9 and Recombinant Protein Solubility Prediction17 were https://protein-sol.manchester.ac.uk/, http://tartaglialab.crg.cat/ccsol.php, http://scratch.proteomics.ics.uci.edu and http://www.biotech.ou.edu, respectively. The performance of each tool was assessed by the Prediction Accuracy and the Matthews Correlation Coefficient (MCC) using the following equations,

where TP is the number of true positives, TN the number of true negatives, FP the number of false positives and FN the number of false negatives.

The tools were evaluated by setting the threshold value for classification of soluble class at 30% for our experimental data solubility, as previously reported by Niwa et al.14 and 50% for the prediction tools.

Copyright and License information: The Author(s) ©2018
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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