A3D 2.0 Update for the Prediction and Optimization of Protein Solubility

Jordi Pujols, Valentín Iglesias, Jaime Santos, Aleksander Kuriata, Sebastian Kmiecik, Salvador Ventura*

*Corresponding author for this work

Research output: Chapter in BookChapterResearchpeer-review

3 Citations (Scopus)


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 chapter is conceived to train and assist A3D non-experts in the study of aggregation-prone regions and protein solubility redesign.

Original languageEnglish
Title of host publicationMethods in Molecular Biology
Number of pages20
Publication statusPublished - 2022

Publication series

NameMethods in Molecular Biology
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029


  • Bioinformatics
  • Protein aggregation
  • Protein redesign
  • Protein solubility


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