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Found 4 papers, 1 papers with code
Deep Lead Optimization: Leveraging Generative AI for Structural Modification
Through this lens, de novo design can incorporate strategies from lead optimization to address the challenge of generating hard-to-synthesize molecules; inversely, lead optimization can benefit from the innovations in de novo design by approaching it as a task of generating molecules conditioned on certain substructures.
PPFlow: Target-aware Peptide Design with Torsional Flow Matching
Therapeutic peptides have proven to have great pharmaceutical value and potential in recent decades.
Infinite Physical Monkey: Do Deep Learning Methods Really Perform Better in Conformation Generation?
Recently, with the development of geometric neural networks, the data-driven schemes have been successfully applied in this field, both for molecular conformation generation (in vacuum) and binding pose generation (in protein pocket).
An adaptive graph learning method for automated molecular interactions and properties predictions
In fact, the pursuit of high prediction performance on a limited number of datasets has crystallized their architectures and hyperparameters, making them lose advantage in repurposing to new data generated in drug discovery.
Ranked #1 on
Drug Discovery
on ToxCast (Toxicity Forecaster)
