Olivier Elemento: Blurring the Line Between Druggable and Undruggable with AI Tools
Olivier Elemento, Director, Englander Institute for Precision Medicine at Weill Cornell Medicine, shared on LinkedIn about a paper published on Nature:
“Making “Undruggable” Proteins Druggable with AI
The line between “druggable” and “undruggable” cancer targets is blurring, as recent advances in AI begin to challenge the long-held paradigm. In our new Nature Biotechnology comment, stemming from a Cancer Moonshot workshop, we argue that a new conceptual framework is required to systematically address this space. This involves moving past the simple ‘undruggable’ label to a functional classification that guides the application of specific AI tools—from modeling protein complexes to identifying transient druggable pockets or designing molecules to modulate biomolecular condensates.
Realizing this potential will require a community effort to build robust benchmarking datasets, including negative results, and to pioneer new strategies for clinical validation. The convergence of AI and novel therapeutic modalities offers a path toward unlocking the proteome, a reward that could fundamentally expand our ability to target human disease.”
Title: Redefining druggable targets with artificial intelligence
Authors: Karen Akinsanya, Mohammed AlQuraishi, Ann Boija, John Chodera, Anna Cichońska, Marzyeh Ghassemi, Martha Head, Wengong Jin, Warren A. Kibbe, Nevan Krogan, Michael V. LeVine, John Moult, Lynda Stuart, Georgia Tourassi, James Zou, Regina Barzilay and Olivier Elemento
Read the full article.
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