Token-Mol 1.0: Tokenized drug design with large language model

Understand

Significant interests have recently risen in leveraging sequence-based large language models (LLMs) for drug design.

• However, most current applications of LLMs in drug discovery lack the ability to comprehend three-dimensional (3D) structures, thereby limiting their effectiveness in tasks that explicitly involve molecular conformations.
• In this study, we introduced Token-Mol, a token-only 3D drug design model.
• This model encodes all molecular information, including 2D and 3D structures, as well as molecular property data, into tokens, which transforms classification and regression tasks in drug discovery into probabilistic prediction problems, thereby enabling learning through a unified paradigm.