Solubis: a webserver to reduce protein aggregation through mutation.

TitleSolubis: a webserver to reduce protein aggregation through mutation.
Publication TypeJournal Article
Year of Publication2016
AuthorsVan Durme J, De Baets G, Van Der Kant R, Ramakers M, Ganesan A, Wilkinson H, Gallardo R, Rousseau F, Schymkowitz J
JournalProtein Eng Des Sel
Volume29
Issue8
Pagination285-9
Date Published2016 Aug
ISSN1741-0134
KeywordsAlgorithms, Computational Biology, Databases, Protein, Internet, Models, Molecular, Mutation, Protein Aggregates, Protein Conformation, Protein Stability, Proteins, Software, Thermodynamics, User-Computer Interface
Abstract

Protein aggregation is a major factor limiting the biotechnological and therapeutic application of many proteins, including enzymes and monoclonal antibodies. The molecular principles underlying aggregation are by now sufficiently understood to allow rational redesign of natural polypeptide sequences for decreased aggregation tendency, and hence potentially increased expression and solubility. Given that aggregation-prone regions (APRs) tend to contribute to the stability of the hydrophobic core or to functional sites of the protein, mutations in these regions have to be carefully selected in order not to disrupt protein structure or function. Therefore, we here provide access to an automated pipeline to identify mutations that reduce protein aggregation by reducing the intrinsic aggregation propensity of the sequence (using the TANGO algorithm), while taking care not to disrupt the thermodynamic stability of the native structure (using the empirical force-field FoldX). Moreover, by providing a plot of the intrinsic aggregation propensity score of APRs corrected by the local stability of that region in the folded structure, we allow users to prioritize those regions in the protein that are most in need of improvement through protein engineering. The method can be accessed at http://solubis.switchlab.org/.

DOI10.1093/protein/gzw019
Alternate JournalProtein Eng. Des. Sel.
PubMed ID27284085