溶解度
蛋白质聚集
球状蛋白
蛋白质稳定性
化学
生物信息学
蛋白质结构
生物物理学
理论(学习稳定性)
生物化学
计算机科学
生物
有机化学
基因
机器学习
作者
Marcos Gil-García,Manuel Bañó‐Polo,Nathalia Varejão,Michał H. Jamróz,Aleksander Kuriata,Marta Díaz-Caballero,Jara Lascorz,Bertrand Morel,Susanna Navarro,David Reverter,Sebastian Kmiecik,Salvador Ventura
标识
DOI:10.1021/acs.molpharmaceut.8b00341
摘要
The aggregation propensity of each particular protein seems to be shaped by evolution according to its natural abundance in the cell. The production and downstream processing of recombinant polypeptides implies attaining concentrations that are orders of magnitude above their natural levels, often resulting in their aggregation; a phenomenon that precludes the marketing of many globular proteins for biomedical or biotechnological applications. Therefore, there is a huge interest in methods aimed to increase the proteins solubility above their natural limits. Here, we demonstrate that an updated version of our AGGRESCAN 3D structural aggregation predictor, that now takes into account protein stability, allows for designing mutations at specific positions in the structure that improve the solubility of proteins without compromising their conformation. Using this approach, we have designed a highly soluble variant of the green fluorescent protein and a human single-domain VH antibody displaying significantly reduced aggregation propensity. Overall, our data indicate that the solubility of unrelated proteins can be easily tuned by in silico-designed nondestabilizing amino acid changes at their surfaces.
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