Discovery of Bavachin as a Dual Trk-A/Trk-B Agonist via Integrated Computational Screening and Experimental Validation
Neurotrophins regulate neuronal survival, differentiation, and synaptic plasticity through activation of tropomyosin receptor kinase (Trk) receptors, and their dysregulation is strongly implicated in neurodegenerative disorders, including Alzheimer's disease. However, the therapeutic application of recombinant neurotrophins remains limited by poor bioavailability, rapid degradation, and…
Neurotrophins play a crucial role in neuronal survival, differentiation, and synaptic plasticity by activating tropomyosin receptor kinase (Trk) receptors. Dysregulation of these proteins is linked to neurodegenerative disorders like Alzheimer's disease. However, using recombinant neurotrophins for therapy is hindered by poor bioavailability, rapid degradation, and limited blood brain barrier permeability.
Researchers have now discovered Bavachin, a dual Trk-A/Trk-B neurotrophin mimetic, through an integrated computational screening and experimental validation method. By conducting structure-based virtual screening of a bioactive natural product library from Traditional Chinese Medicine, along with a novel consensus-ranking strategy, the scientists identified flavonoid scaffolds that target neurotrophin-binding sites on Trk receptors.
Bavachin was found to robustly and dose-dependently activate both Trk-A and Trk-B receptors, while not affecting Trk-C, demonstrating receptor selectivity. Induced-fit docking and molecular dynamics simulations revealed that Bavachin forms stable bindings within both conserved and receptor-specific ligand-binding pockets, confirming its dual agonist activity.
Overall, this study reveals Bavachin as a promising small-molecule neurotrophin mimetic and outlines an integrated computational and experimental approach for discovering dual Trk-A/Trk-B agonists to combat neurodegenerative diseases.
Written by urgent.news from bioRxiv's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.