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Found 3 papers, 3 papers with code
Modeling PROTAC Degradation Activity with Machine Learning
PROTACs are a promising therapeutic modality that harnesses the cell's built-in degradation machinery to degrade specific proteins.
De novo PROTAC design using graph-based deep generative models
After fine-tuning, predicted activity against a challenging POI increases from 50% to >80% with near-perfect chemical validity for sampled compounds, suggesting this is a promising approach for the optimization of large, PROTAC-like molecules for targeted protein degradation.
Amortized Tree Generation for Bottom-up Synthesis Planning and Synthesizable Molecular Design
Molecular design and synthesis planning are two critical steps in the process of molecular discovery that we propose to formulate as a single shared task of conditional synthetic pathway generation.
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