PS4DR

PS4DR identifies candidate drugs for repositioning by integrating GWAS data, gene expression signatures, and pathway databases to compute pathway signatures that link disease dysregulations to drug perturbations.

Key Features:

• Integration of High-Throughput Data: Integrates genome-wide association study (GWAS) data and gene expression signatures derived from disease states and drug perturbations for combined analysis.
• Pathway Knowledge Integration: Incorporates pathway databases to provide mechanistic, pathway-level context for drug–disease relationships.
• Customizable Workflow: Implements a modular workflow that can be tailored to specific datasets or research questions.
• Prediction of Drug Candidates: Computes pathway signatures and simulates disease dysregulations to predict new indications for approved and investigational drugs.
• Validation and Evidence Support: Recovers FDA-approved drugs for known indications and supplies candidate lists supported by epidemiological evidence from the literature.

Scientific Applications:

• Computational Drug Repositioning: Identifies new uses for existing drugs by matching drug perturbation signatures to disease-associated pathway signatures.
• Mechanistic Interpretation: Provides pathway-level mechanistic insights into how drugs modulate disease dysregulations using pathway databases.
• Candidate Prioritization and Validation: Prioritizes repurposing candidates and assesses support by recovering known FDA-approved indications and integrating epidemiological evidence.

Methodology:

Systematic consolidation of publicly available GWAS data, gene expression signatures, and pathway databases, computation of pathway signatures, and simulation of disease dysregulations to analyze disease–drug interactions at the molecular level.