Claude Team for scientists
Claude access for 10000 research groups from leading scientific institutions, to accelerate scientific research. Includes Claude Science tailored for life science research.
Claude access for 10000 research groups from leading scientific institutions, to accelerate scientific research. Includes Claude Science tailored for life science research.
Peptide therapeutics are a fast-growing modality that remains hard to design, because activity depends jointly on sequence, local chemistry, folding, and developability constraints such as toxicity, selectivity, and synthesizability. Existing methods sit at two extremes that each fall short, so this project proposes a unified, folding-aware framework that couples sequence optimization over natural amino acids with residue-level optimization over a curated library of synthesizable modifications. It uses folding predictions, conformer-derived descriptors, and function scoring as active signals in a hierarchical discrete generative search, building on prior results showing that efficient representations can rival heavier architectures.
Modern crop protection faces resistance, a shortage of new modes of action, and climate-driven shifts in pest pressure, all while demand rises to cut chemical load and off-target toxicity. The AI/ML progress seen in pharmaceutical discovery has not reached agrochemistry, largely because few models are tested on pesticide-relevant chemical space and scattered, conflicting data make it hard to judge whether advanced methods beat classical baselines. This project delivers a task-oriented benchmark for crop-protection chemistry, analogous to MoleculeNet and TDC, with transparent baselines and a public leaderboard.