1271-AI for Rational Polypharmacology drug design
This review examines the shift from traditional single-target therapies toward rational polypharmacology through the integration of artificial intelligence and network biology. By conceptualizing diseases as failures within complex signaling webs rather than isolated malfunctions, researchers use machine learning and graph neural networks to identify multi-target intervention sites that circumvent biological redundancy and drug resistance. The text details how generative models and reinforcement learning can design novel compounds capable of modulating entire pathways, such as those involved…
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