Estimating AChE inhibitors from MCE database by machine learning and atomistic calculations

Chúng tôi vui mừng thông báo rằng CN. Thái Quỳnh Mai và các đồng nghiệp gần đây đã xuất bản công trình của họ có tựa đề "Estimating AChE inhibitors from MCE database by machine learning and atomistic calculations" trên tạp chí Journal of Molecular Graphics and Modelling

Tóm tắt:

Acetylcholinesterase (AChE) is one of the most successful targets for the treatment of Alzheimer's disease (AD). Inhibition of AChE can result in preventing AD. In this context, the machine-learning (ML) model, molecular docking, and molecular dynamics calculations were employed to characterize the potential inhibitors for AChE from MedChemExpress (MCE) database. The trained ML model was initially employed for estimating the inhibitory of MCE compounds. Atomistic simulations including molecular docking and molecular dynamics simulations were then used to confirm ML outcomes. In particular, the physical insights into the ligand binding to AChE were clarified over the calculations. Two compounds, PubChem ID of 130467298 and 132020434, were indicated that they can inhibit AChE.