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A comprehensive dataset of protein-protein interactions and ligand binding pockets for advancing drug discovery.
Moine-Franel, Alexandra; Mareuil, Fabien; Nilges, Michael; Ciambur, Constantin Bogdan; Sperandio, Olivier.
Afiliación
  • Moine-Franel A; Structural Bioinformatics Unit, Department of Structural Biology and Chemistry, Institut Pasteur, Université de Paris, CNRS UMR3528, Paris, France.
  • Mareuil F; Collège Doctoral, Sorbonne Université, Paris, F-75005, France.
  • Nilges M; Structural Bioinformatics Unit, Department of Structural Biology and Chemistry, Institut Pasteur, Université de Paris, CNRS UMR3528, Paris, France.
  • Ciambur CB; Structural Bioinformatics Unit, Department of Structural Biology and Chemistry, Institut Pasteur, Université de Paris, CNRS UMR3528, Paris, France.
  • Sperandio O; Structural Bioinformatics Unit, Department of Structural Biology and Chemistry, Institut Pasteur, Université de Paris, CNRS UMR3528, Paris, France.
Sci Data ; 11(1): 402, 2024 Apr 20.
Article en En | MEDLINE | ID: mdl-38643260
ABSTRACT
This dataset represents a collection of pocket-centric structural data related to protein-protein interactions (PPIs) and PPI-related ligand binding sites. The dataset includes high-quality structural information on more than 23,000 pockets, 3,700 proteins on more than 500 organisms, and nearly 3500 ligands that can aid researchers in the fields of bioinformatics, structural biology, and drug discovery. It encompasses a diverse set of PPI complexes with more than 1,700 unique protein families including some with associated ligands, enabling detailed investigations into molecular interactions at the atomic level. This article introduces an indispensable resource designed to unlock the full potential of PPIs while pioneering a novel metric for pocket similarity for hypothesizing protein partners repurposing.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Proteínas / Dominios y Motivos de Interacción de Proteínas / Descubrimiento de Drogas Idioma: En Revista: Sci Data Año: 2024 Tipo del documento: Article País de afiliación: Francia

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Proteínas / Dominios y Motivos de Interacción de Proteínas / Descubrimiento de Drogas Idioma: En Revista: Sci Data Año: 2024 Tipo del documento: Article País de afiliación: Francia