Sequence-Based Prediction of Protein Secretion Success in Aspergillus niger

摘要

The cell-factory Aspergillus niger is widely used for industrial enzyme production. To select potential proteins for large-scale production, we developed a sequence-based classifier that predicts if an over-expressed homologous protein will successfully be produced and secreted. A dataset of 638 proteins was used to train and validate a classifier, using a 10-fold cross-validation protocol. Using a linear discriminant classifier, an average accuracy of 0.85 was achieved. Feature selection results indicate what features are mostly defining for successful protein production, which could be an interesting lead to couple sequence characteristics to biological processes involved in protein production and secretion.