Discovery of Positive Allosteric Modulators of α 7 nAChR by an Ensemble-based Virtual Screening Method, Molecular Dynamics Simulation, and in vitro Biological Activity Testing

Abstract

The [Formula: see text]7 nicotinic acetylcholine receptor (nAChR) is a neurotransmitter receptor and a promising therapeutic target for neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease. In this study, we used deep learning-based classification modeling, molecular docking, and intracellular calcium signal detection experiments to identify positive allosteric modulators (PAMs) of the [Formula: see text]7 nAChR from natural tobacco products. First, we used a classification prediction model based on the direct message-passing neural network (D-MPNN) and molecular docking to predict potential [Formula: see text]7 PAMs. Subsequently, absorption, distribution, metabolism, excretion, and toxicity (ADMET) predictions were performed to determine its pharmacological properties and minimal toxic side effects, leading to the selection of three natural compounds for in vitro activity validation. Calcium signaling assay experiments revealed that diosmetin can enhance nicotine-induced calcium ion signaling. 100 ns molecular dynamics (MD) simulations indicated that diosmetin can form a dense and stable complex with [Formula: see text]7 nAChR. This study provides valuable insights for the design of more effective and selective ligands for the [Formula: see text]7 nAChR.