Protein solubility is an attractive engineering target primarily due to its relation to yields in protein production and manufacturing. Moreover, better knowledge of the mutational effects on protein solubility could connect several serious human diseases with protein aggregation. However, we have limited understanding of the protein structural determinants of solubility, and the available data have mostly been scattered in the literature. Here, we present SoluProtMut^DB – the first database containing data on protein solubility changes upon mutations. Our database accommodates 33 000 measurements of 17 000 protein variants in 103 different proteins. The database can serve as an essential source of information for the researchers designing improved protein variants or those developing machine learning tools to predict the effects of mutations on solubility. The database comprises all the previously published solubility datasets and thousands of new data points from recent publications, including deep mutational scanning experiments. Moreover, it features many available experimental conditions known to affect protein solubility. The datasets have been manually curated with substantial corrections, improving suitability for machine learning applications. The database is available at loschmidt.chemi.muni.cz/soluprotmutdb

蛋白质溶解度是一个有吸引力的工程目标，主要是因为它与蛋白质生产和制造的产量有关。此外，更好地了解突变对蛋白质溶解度的影响可以将几种严重的人类疾病与蛋白质聚集联系起来。然而，我们对溶解度的蛋白质结构决定因素的了解有限，可用数据大多分散在文献中。在这里，我们介绍了 SoluProtMut DB——^第一个包含突变后蛋白质溶解度变化数据的数据库。我们的数据库可容纳 17 种动物的 33 000 次测量 103 种不同蛋白质中的 000 种蛋白质变体。该数据库可以作为研究人员设计改进蛋白质变体或开发机器学习工具以预测突变对溶解度影响的重要信息来源。该数据库包含所有先前发布的溶解度数据集和最近发布的数千个新数据点，包括深度突变扫描实验。此外，它还具有许多已知会影响蛋白质溶解度的可用实验条件。数据集经过人工整理并进行了大量更正，提高了机器学习应用程序的适用性。该数据库位于 loschmidt.chemi.muni.cz/soluprotmutdb