Open Targets Platform: supporting systematic drug–target identification and prioritisation

Abstract

The Open Targets Platform (https://www.targetvalidation.org/) provides users with a queryable knowledgebase and user interface to aid systematic target identification and prioritisation for drug discovery based upon underlying evidence. It is publicly available and the underlying code is open source. Since our last update two years ago, we have had 10 releases to maintain and continuously improve evidence for target–disease relationships from 20 different data sources. In addition, we have integrated new evidence from key datasets, including prioritised targets identified from genome-wide CRISPR knockout screens in 300 cancer models (Project Score), and GWAS/UK BioBank statistical genetic analysis evidence from the Open Targets Genetics Portal. We have evolved our evidence scoring framework to improve target identification. To aid the prioritisation of targets and inform on the potential impact of modulating a given target, we have added evaluation of post-marketing adverse drug reactions and new curated information on target tractability and safety. We have also developed the user interface and backend technologies to improve performance and usability. In this article, we describe the latest enhancements to the Platform, to address the fundamental challenge that developing effective and safe drugs is difficult and expensive.

Mexican Ganoderma Lucidum Extracts Decrease Lipogenesis Modulating Transcriptional Metabolic Networks and Gut Microbiota in C57BL/6 Mice Fed with a High-Cholesterol Diet

“…The Open Targets Platform website [ 31 , 32 ], to prioritize and identify the gene targets associated with hypercholesterolemia. The Open Targets Platform score target-disease associations based on evidence from six levels: genetics, genomics, transcriptomics, drugs, animal models, and scientific literature.…”

Identification and drug-induced reversion of molecular signatures of Alzheimer’s disease onset and progression inAppNL-G-F,AppNL-Fand 3xTg-AD mouse models

“…More specifically, we looked for compounds chemically similar to drugs clinically tested for AD ( 62 ) or with similar mechanisms of action (1), or compounds that elicited similar transcriptional responses to these drugs (2). In addition, we searched for molecules that could bind putative AD targets, as defined by OpenTargets ( 63 ) (3). Moreover, we used the CC gene expression signatures to identify compounds that trigger transcriptional changes in the opposite direction to those observed in our AD mice models (4).…”

“…We also (2) selected small molecules that showed similar transcriptional (D1) or cell sensitivity (D2) to these drugs. In addition, (3) we looked for small molecules known to bind putative AD targets, as defined by OpenTargets ( 63 ). Furthermore, we designed two ‘biological queries’ to capture connectivities between the discovered molecular changes in AD models and the bioactivity data available in the CC.…”

A single-cell based precision medicine approach using glioblastoma patient-specific models

“…Understanding tumor evolutionary trajectories could have important implications for therapeutic strategy. Therefore, we sought to identify potential therapeutics that putatively target TF regulators and/or their associated regulon gene members exhibiting positive activity across tumor cell states within specific timeframes (Table S12) using the Open Targets platform (30). Briefly, the Open Targets platform provides an extensive curated database that enables users to identify drug-target genes/proteins pairings.…”