Predicting blood-brain barrier permeability of molecules with a large language model and machine learning.

ABSTRACT: Predicting the blood-brain barrier (BBB) permeability of small-molecule compounds using a novel artificial intelligence platform is necessary for drug discovery. Machine learning and a large language model on artificial intelligence (AI) tools improve the accuracy and shorten the time for new drug development. The primary goal of this research is to develop artificial intelligence (AI) computing models and novel deep learning architectures capable of predicting whether molecules can permeate the human blood-brain barrier (BBB). The in silico (computational) and in vitro (experimental) results were validated by the Natural Products Research Laboratories (NPRL) at China Medical University Hospital (CMUH). The transformer-based MegaMolBART was used as the simplified molecular input line entry

SUBMITTER: Huang ETC 

PROVIDER: S-EPMC11233737 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature