Protein–Sol: a web tool for predicting protein solubility from sequence

By M. Hebditch, Alejandro M. Carballo‐Amador, Spyros Charonis, R. Curtis, J. Warwicker. 2017

725 citations recorded by the source corpus.

Motivation: Protein solubility is an important property in industrial and therapeutic applications. Prediction is a challenge, despite a growing understanding of the relevant physicochemical properties. Results: Protein‐Sol is a web server for predicting protein solubility. Using available data for Escherichia coli protein solubility in a cell‐free expression system, 35 sequence‐based properties are calculated. Feature weights are determined from separation of low and high solubility subsets. The model returns a predicted solubility and an indication of the features which deviate most from average values. Two other properties are profiled in windowed calculation along the sequence: fold propensity, and net segment charge. The utility of these additional features is demonstrated with the example of thioredoxin. Availability and implementation: The Protein‐Sol webserver is available at http://protein‐sol.manchester.ac.uk. Contact: jim.warwicker@manchester.ac.uk

Subfields: Molecular Biology

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In Molecular Biology

1. Alex Hawkins-Hooker
2. Sebastien Baur
3. Guillaume Couairon
4. F. Depardieu
5. David Bikard
6. A. Chen

Citations in the corpus

• Generating functional protein variants with variational autoencoders (2020, methodology): “We considered P19839 to be a suitable 255 target to test the use of conditional VAE models for solubility engineering as it was predicted to be 256 insoluble by a recent sequence-based computational solubility prediction method, protein-sol [48], 257 with subsequent experimentation confirming that i”