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BioAssay: AID 588209

Literature-mined public compounds from Greene et al multi-species hepatotoxicity modelling dataset

Drug-induced liver injury is a major issue of concern and has led to the withdrawal of a significant number of marketed drugs. An understanding of structure-activity relationships (SARs) of chemicals can make a significant contribution to the identification of potential toxic effects early in the drug development process and aid in avoiding such problems. This process can be supported by the use more ..
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 Tested Compounds
 Tested Compounds
All(520)
 
 
Unspecified(520)
 
 
 Tested Substances
 Tested Substances
All(558)
 
 
Unspecified(558)
 
 
AID: 588209
Data Source: ChEMBL (736782)
Depositor Category: Literature, Extracted
BioAssay Version:
Deposit Date: 2011-09-18
Modify Date: 2014-12-06

Data Table ( Complete ):           View All Data
Tested Compounds:
Description:
Title: Developing structure-activity relationships for the prediction of hepatotoxicity.

Abstract: Drug-induced liver injury is a major issue of concern and has led to the withdrawal of a significant number of marketed drugs. An understanding of structure-activity relationships (SARs) of chemicals can make a significant contribution to the identification of potential toxic effects early in the drug development process and aid in avoiding such problems. This process can be supported by the use of existing toxicity data and mechanistic understanding of the biological processes for related compounds. In the published literature, this information is often spread across diverse sources and can be varied and unstructured in quality and content. The current work has explored whether it is feasible to collect and use such data for the development of new SARs for the hepatotoxicity endpoint and expand upon the limited information currently available in this area. Reviews of hepatotoxicity data were used to build a structure-searchable database, which was analyzed to identify chemical classes associated with an adverse effect on the liver. Searches of the published literature were then undertaken to identify additional supporting evidence, and the resulting information was incorporated into the database. This collated information was evaluated and used to determine the scope of the SARs for each class identified. Data for over 1266 chemicals were collected, and SARs for 38 classes were developed. The SARs have been implemented as structural alerts using Derek for Windows (DfW), a knowledge-based expert system, to allow clearly supported and transparent predictions. An evaluation exercise performed using a customized DfW version 10 knowledge base demonstrated an overall concordance of 56% and specificity and sensitivity values of 73% and 46%, respectively. The approach taken demonstrates that SARs for complex endpoints can be derived from the published data for use in the in silico toxicity assessment of new compounds.
(PMID: 20553011)
Comment
Putative Target:
ChEMBL Target ID: 103956
Target Type: PHENOTYPE
Pref Name: Hepatotoxicity
Confidence: Target assigned is non-molecular
Relationship Type: Non-molecular target assigned
Categorized Comment - additional comments and annotations
From ChEMBL:
Assay Type: ADME
Assay Data Source: Scientific Literature
Result Definitions
TIDNameDescriptionHistogramTypeUnit
OutcomeThe BioAssay activity outcomeOutcome
1Hepatotoxicity activity commentHepatotoxicity activity commentString
2Hepatotoxicity standard flagHepatotoxicity standard flagInteger
3Hepatotoxicity qualifierHepatotoxicity qualifierString
4Hepatotoxicity published valueHepatotoxicity published valueFloat
5Hepatotoxicity standard valueHepatotoxicity standard valueFloat

Data Table (Concise)
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