A3D Model Organism Database (A3D-MODB): a database for proteome aggregation predictions in model organisms

Author:

Badaczewska-Dawid Aleksandra E1,Kuriata Aleksander2,Pintado-Grima Carlos3ORCID,Garcia-Pardo Javier3ORCID,Burdukiewicz Michał34ORCID,Iglesias Valentín3ORCID,Kmiecik Sebastian2ORCID,Ventura Salvador3ORCID

Affiliation:

1. Genome Informatics Facility, Office of Biotechnology, Iowa State University , Ames 50011  IA , USA

2. Biological and Chemical Research Center, Faculty of Chemistry, University of Warsaw , Pasteura 1, 02-093 Warsaw , Poland

3. Institut de Biotecnologia i de Biomedicina (IBB) and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona , 08193 Bellaterra, Barcelona , Spain

4. Clinical Research Centre, Medical University of Białystok , Kilińskiego 1, 15-369, Białystok , Poland

Abstract

Abstract Protein aggregation has been associated with aging and different pathologies and represents a bottleneck in the industrial production of biotherapeutics. Numerous past studies performed in Escherichia coli and other model organisms have allowed to dissect the biophysical principles underlying this process. This knowledge fuelled the development of computational tools, such as Aggrescan 3D (A3D) to forecast and re-design protein aggregation. Here, we present the A3D Model Organism Database (A3D-MODB) http://biocomp.chem.uw.edu.pl/A3D2/MODB, a comprehensive resource for the study of structural protein aggregation in the proteomes of 12 key model species spanning distant biological clades. In addition to A3D predictions, this resource incorporates information useful for contextualizing protein aggregation, including membrane protein topology and structural model confidence, as an indirect reporter of protein disorder. The database is openly accessible without any need for registration. We foresee A3D-MOBD evolving into a central hub for conducting comprehensive, multi-species analyses of protein aggregation, fostering the development of protein-based solutions for medical, biotechnological, agricultural and industrial applications.

Funder

European Union's Horizon 2020

Spanish Ministry of Science and Innovation

ICREA

Juan de la Cierva Incorporación

Maria Zambrano grant funded by the European Union-NextGenerationEU

Spanish Ministry of Science and Innovation and the European Union-NextGenerationEU

Secretariat of Universities and Research of the Catalan Government and the European Social Fund

National Science Centre

Publisher

Oxford University Press (OUP)

Subject

Genetics

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