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Learning Objectives
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Now · 1. Network Pharmacology
Learning Objectives
- Apply network methods to drug discovery
- Understand drug repurposing
1. Network Pharmacology
Traditional: one drug-one target. Network: multi-target, multi-disease.
Polypharmacology: Most drugs interact with 5-15 targets. Network explains both efficacy and side effects.
2. Drug-Target Prediction
Chemical similarity (Tanimoto): similar compounds bind similar targets. Network propagation: drug target effects propagate through PPI. Machine learning: predict from chemical + sequence features.
3. Drug Repurposing
Find new uses for existing drugs. Faster, cheaper, safer.
Methods: Gene expression matching (Connectivity Map - drugs reversing disease signature), side effect similarity, target proximity to disease module.
Q1: What is polypharmacology?Drugs interact with multiple targets. Explains efficacy (hitting disease module in multiple ways) and side effects (hitting unintended modules). Q2: How does network proximity predict repurposing?If drug targets are close to disease module in PPI network, drug may be effective. Distance between drug targets and disease genes predicts therapeutic effect. Q3: What is the Connectivity Map (CMap)?Database of gene expression signatures from drug-treated cells. Query disease signature: find drugs that reverse it (therapeutics) or mimic it (side effects). Q4: Why is repurposing faster than de novo discovery?Existing safety data, manufacturing, dosing. 3-5 years vs 10-15. Cost 300Mvs2B+. Higher success rate. Join Discord PreviousSignaling & Neural NetworksNextNetwork Medicine & Systems Approaches