Case Study
SysGroup – A systems biology approach for grouping compounds

Summary

This case study will use the approach of the diXa / DECO2 (Cefic-LRI AIMT4) projects to reproduce and extend the results obtained on the identification of hepatotoxicant groups based on similarity in mechanisms of action (omics-based) and chemical structure using services from OpenRiskNet.

Objectives

The objective of this case study is to implement an integrated analysis using chemoinformatics and omics data for improved grouping of compounds with similar toxicity and/or mode of action.

Risk assessment framework

SysGroup covers the identification of use scenario / chemical of concern / collection of existing information (Tier 0 in the selected framework) and its steps related to:

  • Identification of molecular structure;
  • Collection of support data;
  • Identification of analogues / suitability assessment and existing data.

Use Cases Associated

This case study is associated with UC1 - Merge existing data by a common structure identifier and includes the following steps:

  1. Chemical similarity calculated by 2D or 3D Tanimoto coefficient
  2. Protein target prediction
  3. Interface to diXa for obtaining gene expression data
  4. Integration of the multiple data sources and grouping by iClusterPlus

Databases and tools

PubChem for Tanimoto scores, ChEMBL or PIDGIN for target predictions, (pre)processing tools for gene expression data (e.g. microarray data) and iClusterPlus for the integration of the multiple types of date.

Service integration

Integration with other case studies is needed. SysGroup acquires information from the DataCure case study and can feed into AOPLink and ModelRX.

Currently available services:

  • Interactive computing and workflows sharing
    Service type: Helper tool, Visualisation tool, Processing tool, Analysis tool, Software, Workflow
  • Scientific workflows make simple
    Service type: Database / data source, Service, Workflow