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Why so few drug targets: a mathematical explanation?
Kyaw Tun1, Marta Menghini, Lina D'Andrea
1MetaSystems Research Team, RIKEN Advanced Science Institute, Yokohama, Japan.
Current Computer-Aided Drug Design
|May 24, 2011
Summary
Biological pathways are often redundant, limiting drug effectiveness. Mathematical models show that only linear pathways allow drugs to impact the entire system, affecting drug development strategies.
Area of Science:
- Systems biology
- Pharmacology
- Computational biology
Background:
- Post-genomic sciences have identified numerous drug targets, yet drug development has not proportionally increased.
- This discrepancy suggests underlying complexities in biological systems and drug action.
Purpose of the Study:
- To investigate the principle of biological pathway redundancy.
- To mathematically model how network architecture affects drug efficacy and signal propagation.
Main Methods:
- Simplified mathematical approaches were used to analyze biological regulation models.
- The 'degree of autonomy' of network architectures was simulated.
- The capacity for external stimuli (drugs) to be sensed and amplified within the network was assessed.
Main Results:
- Network architectures exhibit limited 'degree of autonomy,' restricting drug impact.
- Only strictly linear pathways allow external stimuli to be sensed and amplified across the entire network.
- Non-linearities and complex network structures dampen or block drug signals.
Conclusions:
- Pathway redundancy significantly limits the effectiveness of targeting single nodes.
- Drug development strategies must account for network properties and signal propagation.
- Computational approaches and poly-pharmacology may offer solutions to overcome these limitations.
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