RT Journal Article SR Electronic T1 A3D 2.0 update for the prediction and optimization of protein solubility JF bioRxiv FD Cold Spring Harbor Laboratory SP 2021.04.13.439600 DO 10.1101/2021.04.13.439600 A1 Pujols, Jordi A1 Iglesias, Valentín A1 Santos, Jaime A1 Kuriata, Aleksander A1 Kmiecik, Sebastian A1 Ventura, Salvador YR 2021 UL http://biorxiv.org/content/early/2021/04/14/2021.04.13.439600.abstract AB Protein aggregation propensity is a property imprinted in protein sequences and structures, being associated with the onset of human diseases and limiting the implementation of protein-based biotherapies. Computational approaches stand as cost-effective alternatives for reducing protein aggregation and increasing protein solubility. AGGRESCAN 3D (A3D) is a structure-based predictor of aggregation that takes into account the conformational context of a protein, aiming to identify aggregation-prone regions exposed in protein surfaces. Here we inspect the updated 2.0 version of the algorithm, which extends the application of A3D to previously inaccessible proteins and incorporates new modules to assist protein redesign. Among these features, the new server includes stability calculations and the possibility to optimize protein solubility using an experimentally validated computational pipeline. Finally, we employ defined examples to navigate the A3D RESTful service, a routine to handle extensive protein collections. Altogether, this work is conceived to train and assist A3D non-experts in the study of aggregation-prone regions and protein solubility redesign.Competing Interest StatementThe authors have declared no competing interest.