A3D 2.0 Update for the Prediction and Optimization of Protein Solubility

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

*Autor corresponent d’aquest treball

Producció científica: Capítol de llibreCapítolRecercaAvaluat per experts

7 Cites (Scopus)

Resum

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.

Idioma originalAnglès
Títol de la publicacióMethods in Molecular Biology
Pàgines65-84
Nombre de pàgines20
DOIs
Estat de la publicacióPublicada - 2022

Sèrie de publicacions

NomMethods in Molecular Biology
Volum2406
ISSN (imprès)1064-3745
ISSN (electrònic)1940-6029

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