OCSANA

OCSANA identifies minimal combinations of interventions in biological networks to disrupt pathways between specified source nodes (e.g., proteins or genes) and target nodes, enabling prioritization of multi-target therapeutic strategies while minimizing off-target effects.

Key Features:

• Minimal intervention identification: Identifies minimal and effective intervention combinations that disrupt pathways between specified source and target nodes.
• Combinatorial complexity management: Addresses the combinatorial complexity inherent in targeting multiple proteins within signaling networks.
• Exact solution: Provides an exact computational solution for identifying optimal intervention combinations.
• Selective enumeration strategy: Implements a novel selective enumeration strategy tailored to handle large-scale networks efficiently.
• Off-target consideration: Allows specification of off-target nodes to minimize unintended impacts and side effects of interventions.

Scientific Applications:

• Targeted therapies (cancer): Prioritizes multi-target therapeutic strategies in the context of diseases such as cancer.
• Signaling network intervention design: Designs and ranks intervention combinations in signaling networks involving proteins and genes.
• Side-effect minimization: Enables analysis that accounts for off-target nodes to reduce adverse effects of proposed interventions.

Methodology:

Uses an exact solution to identify optimal intervention combinations and a selective enumeration strategy for large-scale networks, focusing on disruption of paths between specified source and target nodes and incorporating user-defined off-target node constraints.