CPAD 2.0: a repository of curated experimental data on aggregating proteins and peptides.


Journal

Amyloid : the international journal of experimental and clinical investigation : the official journal of the International Society of Amyloidosis
ISSN: 1744-2818
Titre abrégé: Amyloid
Pays: England
ID NLM: 9433802

Informations de publication

Date de publication:
Jun 2020
Historique:
pubmed: 26 1 2020
medline: 30 1 2021
entrez: 26 1 2020
Statut: ppublish

Résumé

The Curated Protein Aggregation Database (CPAD) is a manually curated and open-access database dedicated to providing comprehensive information related to mechanistic, kinetic and structural aspects of protein and peptide aggregation. The database has been updated to CPAD 2.0 by significantly expanding datasets and improving the user-interface. Key features of CPAD 2.0 are (i) 83,098 data points on aggregation kinetics experiments, (ii) 565 structures related to aggregation, which are classified into proteins, fibrils, and protein-ligand complexes, (iii) 2031 aggregating/non-aggregating peptides with pre-calculated aggregation properties, and (iv) 912 aggregation-prone regions in amyloidogenic proteins. This database will help the scientific community (a) by facilitating research leading to improved understanding of protein aggregation, (b) by helping develop, validate and benchmark mechanistic and kinetic models of protein aggregation, and (c) by assisting experimentalists with design of their investigations and dissemination of data generated by their studies. CPAD 2.0 can be accessed at https://web.iitm.ac.in/bioinfo2/cpad2/index.html.

Identifiants

pubmed: 31979981
doi: 10.1080/13506129.2020.1715363
doi:

Substances chimiques

Amyloid 0
Peptides 0
Protein Aggregates 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

128-133

Auteurs

Puneet Rawat (P)

Protein Bioinformatics Lab, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, India.

R Prabakaran (R)

Protein Bioinformatics Lab, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, India.

R Sakthivel (R)

Protein Bioinformatics Lab, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, India.

A Mary Thangakani (A)

Protein Bioinformatics Lab, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, India.

Sandeep Kumar (S)

Biotherapeutics Discovery, Boehringer-Ingelheim Inc, Ridgefield, CT, USA.

M Michael Gromiha (MM)

Protein Bioinformatics Lab, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, India.
Advanced Computational Drug Discovery Unit (ACDD), Tokyo Tech World Research Hub Initiative (WRHI), Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan.

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Classifications MeSH