Our end-to-end computational platform leverages on deep understanding of physical principles and artificial intelligence, and opens up new possibilities for structure and dynamics-based drug discovery. Equipped with the Uni-Fold algorithm for protein folding and the RiD (Reinforced Dynamics) method for enhanced sampling, our platform enables both high-resolution refinement of static structures of proteins and accurate capture of intermediate states. Our approach allows novel pockets to be identified and can be applied to study many other emerging classes of therapeutics. Our team has been working relentlessly on a few of them:

Powered by the Differentiable Molecular Force Field, we aim to improve the accuracy of FEP calculation, especially on complex systems like GPCR, to a new level. Aligned with our Uni-Dock and AI based molecular recommendation algorithm, we are providing a full package of pre-clinical discovery services including but not limited to:

Combining Uni-Fold structure prediction methods, state-of-the-art natural language processing techniques, reinforcement learning framework and next-generation molecular dynamics simulations, our multidisciplinary team are devoted to creating a whole new paradigm for biologics drug discovery, including but not limited to: