ChemPert

ChemPert maps chemical perturbations to transcriptional responses in non-cancer cell types to enable analysis of drug effects and mechanisms.

Key Features:

• Extensive Database: Contains 82,270 transcriptional signatures derived from 2,566 unique perturbagens, including drugs, small molecules, and protein ligands, across 167 non-cancer cell types.
• Protein Target Information: Includes detailed protein target annotations for 57,818 perturbagens.
• Advanced Computational Tool: Provides a computational tool developed to leverage non-cancer cell datasets to predict transcriptional responses and drug effects, compared with cancer-based databases.
• Successful Applications: Demonstrated predictions of drug effects for hepatitis and identification of novel therapeutic candidates for osteoarthritis.

Scientific Applications:

• Drug Discovery: Enables in silico screening and prioritization of compounds using non-cancer cell perturbation transcriptomics.
• Disease Research: Supports analysis of transcriptional changes induced by chemical perturbations in non-cancer diseases, immunological conditions, and aging.
• Algorithm Development: Provides comprehensive non-cancer perturbation transcriptomics datasets for development and benchmarking of predictive algorithms for drug responses.

Methodology:

Computational analyses leverage non-cancer perturbation transcriptomic signatures and a dedicated prediction tool to infer transcriptional responses and drug effects.