COMO

COMO integrates multi-omics data into constraint-based metabolic models to identify metabolic vulnerabilities and candidate drug targets.

Key Features:

• Multi-Omics Data Integration: Integrates bulk and single-cell RNA-sequencing (RNA-seq), microarrays, and proteomics outputs for context-specific analysis.
• Context-Specific Metabolic Model Construction: Constructs context-specific metabolic models by leveraging public databases and open-source solutions.
• Constraint-Based Optimization: Applies constraint-based modeling techniques to simulate cellular metabolism and optimize metabolic objectives.
• Drug Repurposing Prediction: Incorporates drug databases and disease data to predict repurposable drugs and candidate targets.
• Case Study Application: Demonstrated application to B cells with target predictions relevant to rheumatoid arthritis and systemic lupus erythematosus.

Scientific Applications:

• Metabolic Target Identification: Identification of metabolic enzymes and pathways as candidate drug targets in disease contexts.
• Drug Repurposing: Prioritization of repurposable drugs using integrated drug and disease data within metabolic models.
• Cell- and Tissue-Specific Modeling: Generation of context-specific models for any cell or tissue type using multi-omics inputs.
• Disease Mechanism Exploration: Analysis of altered metabolic states in human diseases where metabolic processes are implicated.

Methodology:

Combines multi-omics data processing with context-specific metabolic model development, utilizes constraint-based modeling techniques to simulate cellular metabolism, leverages public databases and open-source solutions, and integrates disease-specific and drug database information to predict repurposable drugs.