bookmark PON-Sol Predicts the effects of amino acid substitution on protein solubility. PON-Sol is a machine learning-based method and utilizes amino acid features and evolutionary information. The predictor can distinguish both solubility decreasing and increasing variants from those not affecting solubility. PON-Sol 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 amino acid substitutions (AAs) in a protein to aid protein engineering.