AICD

AICD aggregates and curates chemical, bioassay, and target data for 79,781 small molecules and 232 inflammation-related targets to support discovery of anti-inflammatory therapeutics.

Key Features:

• Comprehensive Data Integration: integrates and curates physicochemical properties and bioassay results from multiple open-access databases.
• Target Diversity: covers 232 inflammation-related targets identified through gene set enrichment analysis across diverse disease-relevant pathways.
• Annotated Compound Collection: contains 79,781 small molecules annotated with chemical properties, candidate targets, bioassay models, and results.
• Systematic Bioassay Curation: bioassay data for the targets have been systematically gathered to support robust analysis and comparison.
• Chemical Diversity: includes a chemically diverse compound set to increase the chance of novel mechanisms of action.
• Chemical Space Analysis (PCA): uses principal component analysis to compare compound chemical space with US Food and Drug Administration (FDA)-approved drugs.
• Pathway-Based Screening: supports pathway-based screening approaches for identifying potential drug combinations or multi-target therapeutics.

Scientific Applications:

• Anti-inflammatory drug discovery: prioritizes small molecules and targets for development of therapeutics against inflammation-related diseases.
• Multi-target and combination strategies: enables identification of candidate multi-target drugs or synergistic drug combinations via pathway-focused data.
• Target identification and validation: facilitates selection of inflammation-related targets identified by gene set enrichment analysis for experimental follow-up.
• Lead selection and chemical-space benchmarking: aids selection of lead compounds and benchmarking against FDA-approved drugs using principal component analysis.
• Bioassay-driven hypothesis generation: leverages curated bioassay results to generate hypotheses on compound–target activity relationships.

Methodology:

Integrates and curates data from open-access databases; identifies 232 inflammation-related targets via gene set enrichment analysis; systematically gathers bioassay data; annotates 79,781 small molecules with physicochemical properties, candidate targets, bioassay models and results; and applies principal component analysis for chemical-space comparisons with FDA-approved drugs.