Prediction of Aggregation Prone Regions in Proteins Using Deep Neural Networks and Their Suppression by Computational Design

Cima, V.; Kunka, A.; Grakova, E.; Planas-Iglesias, J.; Havlasek, M.; Subramanian, M.; Beloch, M.; Marek, M.; Slaninova, K.; Damborsky, J.; Prokop, Z.; Bednar, D.; Martinovic, J.

doi:10.1101/2024.03.06.583680

bioRxiv · 10.1101/2024.03.06.583680

Prediction of Aggregation Prone Regions in Proteins Using Deep Neural Networks and Their Suppression by Computational Design

Cima, V.·Kunka, A.·Grakova, E.·Planas-Iglesias, J.·Havlasek, M.·Subramanian, M.·Beloch, M.·Marek, M.·Slaninova, K.·Damborsky, J.·Prokop, Z.·Bednar, D.·Martinovic, J.

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Abstract

Identification of aggregation-prone regions in proteins and their suppression through mutations is a powerful strategy to enhance protein solubility and yield, significantly expanding their application potential. Here, we developed a deep neural network-based predictor AggreProt, that generates a residue-level aggregation profile for protein sequences. The model outperformed or matched current state-of-the-art algorithms, as validated on two independent datasets comprising hexapeptides and full-length proteins with annotated aggregation-prone regions. We further validated the model experimentally using a set of 34 hexapeptides identified in the model protein haloalkane dehalogenase LinB, along with seven proteins from the AmyPro database. Experimental results agreed with our predictions in 79% of cases and also revealed inaccuracies in some database annotations. Finally, the algorithms utility was demonstrated by identifying aggregation-prone regions in the LinB enzyme and designing mutations to suppress aggregation in its exposed regions. The resulting variants exhibited reduced aggregation propensity, improved solubility, and up to a 100% increase in yield compared to the wild type. AggreProt is freely available to the scientific community via a user- friendly web server: https://loschmidt.chemi.muni.cz/aggreprot.

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Cima, V., Kunka, A., Grakova, E., Planas-Iglesias, J., Havlasek, M., Subramanian, M., Beloch, M., Marek, M., Slaninova, K., Damborsky, J., Prokop, Z., Bednar, D., Martinovic, J.. 2024-03-11. Prediction of Aggregation Prone Regions in Proteins Using Deep Neural Networks and Their Suppression by Computational Design. https://doi.org/10.1101/2024.03.06.583680

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