Evaluation of neuroprotective agents acting via the BDNF–TrkB pathway using AI-enabled predictions of ligand–receptor interactions

Abstract

Glaucoma is the leading cause of irreversible blindness globally and is associated with retinal ganglion cell (RGC) death. Brain-derived neurotrophic factor (BDNF) is a potent neurotrophin that promotes neuronal survival via its receptor, tropomyosin receptor kinase B (TrkB) encoded by NTRK2. Our current understanding of the mechanism of action and therapeutic potential of the BDNF pathway is limited by the lack of knowledge of its interaction with TrkB at atomic resolution. We developed an artificial intelligence (AI) model to predict the three-dimensional protein structures of BDNF and TrkB, as well as their interaction. The AI model was further applied to compare small-molecule drugs that mimic BDNF–TrkB interaction, leading to the identification of 7,8-dihydroxyflavone (DHF) as an agonist of TrkB. We verified the neuroprotective effects of DHF in an in vivo acute glaucoma model in which RGC apoptosis caused by acute elevation of intraocular pressure was prevented by the intraocular application of DHF and to a lesser extent by BDNF. Our results provide AI-enabled prediction of ligand–receptor interactions between BDNF and TrkB at the atomic level and demonstrate the great potential for AI-enabled drug discovery.