Cholinesterases (ChEs) are pivotal in the pathophysiology of various neuromuscular diseases, including Parkinson’s disease, Alzheimer’s disease, myasthenia gravis, and vascular dementia. The involvement of ChEs in open-angle glaucoma establishes them as promising drug targets. This study employed hierarchical virtual screening (HVS) to identify lead compounds against cholinesterase drug targets. A four-step, knowledge-based, and time-efficient HVS protocol was implemented, resulting in the identification of 41 novel scaffolds capable of evolving into diverse functional ChE inhibitors. This includes inhibitors with selectivity for acetylcholinesterase (AChE) or butyrylcholinesterase (BChE), dual-target, and dual-binding-site inhibitors. The proposed HVS scheme integrates structure-based pharmacophores, docking methodologies, and physicochemical-descriptor-based filters. Among the identified scaffolds, 13 potential ChE inhibitors were selected based on their non-covalent interactions with key binding site residues of both AChE and BChE. Furthermore, an assessment of the physicochemical and pharmacokinetic profiles of these compounds was conducted. The selected potential inhibitors are recommended for further evaluation through in vitro and in vivo assay studies. This comprehensive approach enhances the prospects of identifying effective therapeutic agents targeting cholinesterases in neuromuscular diseases.

胆碱酯酶 (ChE) 在各种神经肌肉疾病的病理生理学中发挥着关键作用，包括帕金森病、阿尔茨海默病、重症肌无力和血管性痴呆。 ChE 在开角型青光眼中的参与使它们成为有希望的药物靶点。本研究采用分层虚拟筛选 (HVS) 来识别针对胆碱酯酶药物靶点的先导化合物。实施了四步、基于知识且高效的 HVS 方案，最终鉴定出 41 种能够演变成多种功能性 ChE 抑制剂的新型支架。这包括对乙酰胆碱酯酶 (AChE) 或丁酰胆碱酯酶 (BChE) 具有选择性的抑制剂、双靶点和双结合位点抑制剂。所提出的 HVS 方案集成了基于结构的药效团、对接方法和基于物理化学描述符的过滤器。在已鉴定的支架中，根据其与 AChE 和 BChE 关键结合位点残基的非共价相互作用，选择了 13 种潜在的 ChE 抑制剂。此外，还对这些化合物的理化和药代动力学特征进行了评估。建议通过体外和体内测定研究对所选的潜在抑制剂进行进一步评估。这种综合方法增强了确定针对神经肌肉疾病的胆碱酯酶的有效治疗药物的前景。