US EditionAI Automatically Designs Optimal Drug Candidates for Cancer-Targeting Mutations
SOUTH KOREA, AUG 11 – The AI model BInD designs drug candidates by optimizing multiple criteria from protein structures alone, improving drug discovery without prior molecular data, KAIST researchers said.
Summary by Phys.org
2 Articles
2 Articles
AI automatically designs optimal drug candidates for cancer-targeting mutations
Traditional drug development methods involve identifying a target protein (e.g., a cancer cell receptor) that causes disease, and then searching through countless molecular candidates (potential drugs) that could bind to that protein and block its function. This process is costly, time-consuming, and has a low success rate.
·United Kingdom
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AI model can design optimal drug candidates without any prior molecular data
Traditional drug development methods involve identifying a target protein (e.g., a cancer cell receptor) that causes disease, and then searching through countless molecular candidates (potential drugs) that could bind to that protein and block its function.
·United States
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