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This work presents AutoSDT, an automatic pipeline that collects high-quality coding tasks in real-world data-driven discovery workflows and is the only automatically collected and the largest open dataset for data-driven scientific discovery.
RIDE, a Reference-anchored Inference-time Diffusion Editing framework for scaffold hopping, is introduced and demonstrates its ability to generate distinct scaffolds with different structures and properties, and its ability to introduce substantial 2D variation while maintaining very high 3D similarity.
Drug discovery and development is time-consuming and resource-intensive, motivating computational approaches such as diffusion models for de novo drug design. Many such models follow the structure-based drug design (SBDD) paradigm, generating molecules to fit a target binding pocket. However, existing diffusion-based S...
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