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Ligand Binding Sites

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...

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A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions

Published on: May 27, 2021

The ChEMBL database in 2017.

Anna Gaulton¹, Anne Hersey¹, Michał Nowotka¹

¹European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK.

Nucleic Acids Research

|December 1, 2016

Summary

This summary is machine-generated.

The ChEMBL database has expanded its collection of drug discovery data, incorporating new sources and features for improved bioactivity analysis. This open resource facilitates research in medicinal chemistry and drug development.

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Area of Science:

Biomedical Sciences
Drug Discovery
Bioinformatics

Background:

ChEMBL is a comprehensive, open-access database of bioactive molecules with drug-like properties.
Previous descriptions were published in the 2012 and 2014 Nucleic Acids Research Database Issues.
The database continuously expands its data through literature curation and new data submissions.

Purpose of the Study:

To detail the recent updates and enhancements to the ChEMBL database.
To highlight the integration of diverse new data sources.
To showcase new features improving data accessibility and utility for researchers.

Main Methods:

Continued extraction of bioactivity data from medicinal chemistry literature.
Inclusion of deposited datasets from neglected disease screening and crop protection.
Integration of drug metabolism and disposition data, and patent bioactivity data.
Annotation of assays and targets using ontologies.
Inclusion of clinical candidate targets and indications.
Addition of drug metabolic pathways and calculation of structural alerts.

Main Results:

Expanded ChEMBL database with new datasets, including neglected diseases, crop protection, drug metabolism, and patents.
Enhanced data utility through ontology-based annotation of assays and targets.
Improved information on clinical candidates, drug metabolism, and structural alerts.
Data accessibility maintained and enhanced via web interface, RDF, downloads, and web services.

Conclusions:

The ChEMBL database has significantly grown in scope and utility.
New data sources and features enhance its value for drug discovery and related research.
The database remains a vital, accessible resource for the scientific community.