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Community-Wide Experimental Evaluation of the PROSS Stability-Design Method

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Suppmann,  Sabine
Scientific Service Groups, Max Planck Institute of Biochemistry, Max Planck Society;

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Peleg, Y., Vincentelli, R., Collins, B. M., Chen, K.-E., Livingstone, E. K., Weeratunga, S., et al. (2021). Community-Wide Experimental Evaluation of the PROSS Stability-Design Method. Journal of Molecular Biology, 433(13): 166964. doi:10.1016/j.jmb.2021.166964.


Cite as: http://hdl.handle.net/21.11116/0000-0008-B9DA-2
Abstract
Recent years have seen a dramatic improvement in protein-design methodology. Nevertheless, most methods demand expert intervention, limiting their widespread adoption. By contrast, the PROSS algorithm for improving protein stability and heterologous expression levels has been successfully applied to a range of challenging enzymes and binding proteins. Here, we benchmark the application of PROSS as a stand-alone tool for protein scientists with no or limited experience in modeling. Twelve laboratories from the Protein Production and Purification Partnership in Europe (P4EU) challenged the PROSS algorithm with 14 unrelated protein targets without support from the PROSS developers. For each target, up to six designs were evaluated for expression levels and in some cases, for thermal stability and activity. In nine targets, designs exhibited increased heterologous expression levels either in prokaryotic and/or eukaryotic expression systems under experimental conditions that were tailored for each target protein. Furthermore, we observed increased thermal stability in nine of ten tested targets. In two prime examples, the human Stem Cell Factor (hSCF) and human Cadherin-Like Domain (CLD12) from the RET receptor, the wild type proteins were not expressible as soluble proteins in E. coli, yet the PROSS designs exhibited high expression levels in E. coli and HEK293 cells, respectively, and improved thermal stability. We conclude that PROSS may improve stability and expressibility in diverse cases, and that improvement typically requires target-specific expression conditions. This study demonstrates the strengths of community-wide efforts to probe the generality of new methods and recommends areas for future research to advance practically useful algorithms for protein science. (C) 2021 Elsevier Ltd. All rights reserved.