Aggregating amyloid resources: A comprehensive review of databases on amyloid-like aggregation

Protein aggregation is responsible for several degenerative conditions in humans, and it is also a bottleneck in industrial protein production and storage of biotherapeutics. Bioinformatics tools have been developed to predict and redesign protein solubility more efficiently by understanding the und...

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Detalles Bibliográficos
Autores: Iglesias, Valentín, Chilimoniuk, Jarosław, Pintado-Grima, Carlos, Bárcenas, Oriol, Ventura, Salvador, Burdukiewicz, Michał
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/372084
Acceso en línea:http://hdl.handle.net/10261/372084
https://api.elsevier.com/content/abstract/scopus_id/85208481285
Access Level:acceso abierto
Palabra clave:Protein solubility
Amyloid
Bioinformatics
Biotherapeutics
Database
Prion
Protein aggregation
http://metadata.un.org/sdg/3
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Descripción
Sumario:Protein aggregation is responsible for several degenerative conditions in humans, and it is also a bottleneck in industrial protein production and storage of biotherapeutics. Bioinformatics tools have been developed to predict and redesign protein solubility more efficiently by understanding the underlying principles behind aggregation. As more experimental data become available, dedicated resources for storing, indexing, classifying and consolidating experimental results have emerged. These resources vary in focus, including aggregation-prone regions, 3D patches or protein stretches capable of forming amyloid fibrils. Some of these resources also consider the experimental conditions that cause protein aggregation and how they affect the process. This review article explores how protein aggregation databases have evolved and surveys state-of-the-art resources. We highlight their applications, complementarity and existing limitations. Moreover, we showcase the existing symbiosis between amyloid-related databases and predictive tools. To increase the usefulness of our review, we supplement it with a comprehensive list of present and past amyloid databases: https://biogenies.info/amyloid-database-list/.