PON-Sol: Prediction of effects of amino acid substitutions on protein solubility

Yang Yang; Abhishek Niroula; Bairong Shen; Mauno Vihinen

doi:10.1093/bioinformatics/btw066

PON-Sol: Prediction of effects of amino acid substitutions on protein solubility

Yang Yang, Abhishek Niroula, Bairong Shen, Mauno Vihinen

Soochow University

Research output: Contribution to journal › Article › peer-review

Abstract

Motivation: Solubility is one of the fundamental protein properties. It is of great interest because of its relevance to protein expression. Reduced solubility and protein aggregation are also associated with many diseases. Results: We collected from literature the largest experimentally verified solubility affecting amino acid substitution (AAS) dataset and used it to train a predictor called PON-Sol. The predictor can distinguish both solubility decreasing and increasing variants from those not affecting solubility. PONSol has normalized correct prediction ratio of 0.491 on cross-validation and 0.432 for independent test set. The performance of the method was compared both to solubility and aggregation predictors and found to be superior. PON-Sol can be used for the prediction of effects of disease-related substitutions, effects on heterologous recombinant protein expression and enhanced crystallizability. One application is to investigate effects of all possible AASs in a protein to aid protein engineering.

Original language	English
Pages (from-to)	2032-2034
Journal	Bioinformatics
Volume	32
Issue number	13
DOIs	https://doi.org/10.1093/bioinformatics/btw066
Publication status	Published - 2016 Jul 1

Subject classification (UKÄ)

Other Basic Medicine
Medicinal Chemistry

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10.1093/bioinformatics/btw066

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abstract = "Motivation: Solubility is one of the fundamental protein properties. It is of great interest because of its relevance to protein expression. Reduced solubility and protein aggregation are also associated with many diseases. Results: We collected from literature the largest experimentally verified solubility affecting amino acid substitution (AAS) dataset and used it to train a predictor called PON-Sol. The predictor can distinguish both solubility decreasing and increasing variants from those not affecting solubility. PONSol has normalized correct prediction ratio of 0.491 on cross-validation and 0.432 for independent test set. The performance of the method was compared both to solubility and aggregation predictors and found to be superior. PON-Sol can be used for the prediction of effects of disease-related substitutions, effects on heterologous recombinant protein expression and enhanced crystallizability. One application is to investigate effects of all possible AASs in a protein to aid protein engineering.",

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AU - Yang, Yang

AU - Niroula, Abhishek

AU - Shen, Bairong

AU - Vihinen, Mauno

PY - 2016/7/1

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AB - Motivation: Solubility is one of the fundamental protein properties. It is of great interest because of its relevance to protein expression. Reduced solubility and protein aggregation are also associated with many diseases. Results: We collected from literature the largest experimentally verified solubility affecting amino acid substitution (AAS) dataset and used it to train a predictor called PON-Sol. The predictor can distinguish both solubility decreasing and increasing variants from those not affecting solubility. PONSol has normalized correct prediction ratio of 0.491 on cross-validation and 0.432 for independent test set. The performance of the method was compared both to solubility and aggregation predictors and found to be superior. PON-Sol can be used for the prediction of effects of disease-related substitutions, effects on heterologous recombinant protein expression and enhanced crystallizability. One application is to investigate effects of all possible AASs in a protein to aid protein engineering.

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PON-Sol: Prediction of effects of amino acid substitutions on protein solubility

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