CHAI-1 — это революционная мультимодальная ИИ-модель, созданная для глубокого анализа биологических структур и разработки новых лекарств. Нейросеть с высокой точностью предсказывает фолдинг белков и взаимодействия молекул, позволяя интегрировать данные из реальных лабораторий для усиления результата.
We introduce Chai-1, a multi-modal foundation model for molecular structure prediction that performs at the state-of-the-art across a variety of tasks relevant to drug discovery. Chai-1 can optionally be prompted with experimental restraints (e.g. derived from wet-lab data) which boostsperformance by double-digit percentage points. Chai-1 can also be run in single-sequence mode without MSAs while preserving most of its performance. We release Chai-1 model weights and inference code as a Python package for non-commercial use and via a web interface where it can be used for free including for commercial drug discovery purposes.