AggreProt: a web server for predicting and engineering aggregation prone regions in proteins.

ABSTRACT: Recombinant proteins play pivotal roles in numerous applications including industrial biocatalysts or therapeutics. Despite the recent progress in computational protein structure prediction, protein solubility and reduced aggregation propensity remain challenging attributes to design. Identification of aggregation-prone regions is essential for understanding misfolding diseases or designing efficient protein-based technologies, and as such has a great socio-economic impact. Here, we introduce AggreProt, a user-friendly webserver that automatically exploits an ensemble of deep neural networks to predict aggregation-prone regions (APRs) in protein sequences. Trained on experimentally evaluated hexapeptides, AggreProt compares to or outperforms state-of-the-art algorithms on two independent b

SUBMITTER: Planas-Iglesias J 

PROVIDER: S-EPMC11223854 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature