AGGRESCAN3D: Toward the Prediction of the Aggregation Propensities of Protein Structures

Jordi Pujols; Samuel Peña-Díaz; Salvador Ventura

doi:10.1007/978-1-4939-7756-7_21

AGGRESCAN3D: Toward the Prediction of the Aggregation Propensities of Protein Structures

Methods Mol Biol. 2018:1762:427-443. doi: 10.1007/978-1-4939-7756-7_21.

Authors

Jordi Pujols^{1

2}, Samuel Peña-Díaz^{1

2}, Salvador Ventura^{3

4}

Affiliations

¹ Institut de Biotecnologia i Biomedicina, Universitat Autònoma de Barcelona, Bellaterra, Spain.
² Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, Spain.
³ Institut de Biotecnologia i Biomedicina, Universitat Autònoma de Barcelona, Bellaterra, Spain. salvador.ventura@uab.es.
⁴ Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, Spain. salvador.ventura@uab.es.

PMID: 29594784
DOI: 10.1007/978-1-4939-7756-7_21

Abstract

Protein aggregation is responsible for the onset and spread of many human diseases, ranging from neurodegenerative disorders to cancer and diabetes. Moreover, it is one of the major bottlenecks for the production of protein-based therapeutics such as antibodies or enzymes. AGGRESCAN3D (A3D) is a web server aimed to identify and evaluate structural aggregation prone regions, overcoming the limitations of sequence-based algorithms in the prediction of the aggregation propensity of globular proteins. A3D allows the redesign of protein solubility by predicting in silico the impact of mutations and protein conformational fluctuations on the aggregation of native polypeptides.

Keywords: 3D structure; AGGRESCAN3D; Bioinformatics; Protein aggregation; Protein misfolding; Protein production; Protein solubility.

MeSH terms

Algorithms
Computational Biology / methods*
Humans
Internet
Models, Molecular
Protein Aggregates
Protein Conformation
Protein Folding
Proteins / chemistry*
Solubility

Substances

Protein Aggregates
Proteins