Scholarlink

<p>Human glutaminyl cyclase (hQC), as a potential drug target, has attracted considerable attention due to its strong association with the pathology of Alzheimer’s disease (AD). In this study, stepwise molecular docking integrated with molecular dynamics (MD) simulation was employed to identify potential novel hQC inhibitors. Through structure-based virtual screening, six hit compounds with desirable drug-like properties were screened out from the ChEMBL database. The evaluation of adsorption, distribution, metabolism, excretion, and toxicity (ADMET) showed that hit compounds exhibited pharmacokinetic properties within acceptable ranges. Further investigations using Density Functional Theory (DFT) revealed distinct physicochemical properties and binding mechanisms of the hit compounds, with hydrogen bonding and van der Waals interactions playing pivotal roles in ligand binding. Structural stability and binding dynamics were further explored using MD simulations, where structural evaluations (RMSD, Rg, SASA, and RMSF), principal component analysis (PCA), and free energy landscapes (FEL) demonstrated that hit compounds maintained stable binding to the hQC active site while the protein remained in a stable folded state throughout the binding process. Finally, the binding free energy calculation showed that the binding affinity of hit compounds was higher than that of the reference compound PBD150. These findings suggested that the identified hit compounds showed significant potential for further biological activity studies to evaluate their inhibitory effects on hQC.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Identification of human glutaminyl cyclase inhibitors for Alzheimer’s disease: integrating virtual screening, DFT calculations, and molecular dynamics simulation

  • 期刊论文

  • 发表日期：

    2025年12月8日

查看全文
  • Jingjing Li,
  • Chaochun Wei,
  • Xiaokun Zhang,
  • Qidi Zhong,
  • Hong Yan,
  • Juan Wang

摘要

Human glutaminyl cyclase (hQC), as a potential drug target, has attracted considerable attention due to its strong association with the pathology of Alzheimer’s disease (AD). In this study, stepwise molecular docking integrated with molecular dynamics (MD) simulation was employed to identify potential novel hQC inhibitors. Through structure-based virtual screening, six hit compounds with desirable drug-like properties were screened out from the ChEMBL database. The evaluation of adsorption, distribution, metabolism, excretion, and toxicity (ADMET) showed that hit compounds exhibited pharmacokinetic properties within acceptable ranges. Further investigations using Density Functional Theory (DFT) revealed distinct physicochemical properties and binding mechanisms of the hit compounds, with hydrogen bonding and van der Waals interactions playing pivotal roles in ligand binding. Structural stability and binding dynamics were further explored using MD simulations, where structural evaluations (RMSD, Rg, SASA, and RMSF), principal component analysis (PCA), and free energy landscapes (FEL) demonstrated that hit compounds maintained stable binding to the hQC active site while the protein remained in a stable folded state throughout the binding process. Finally, the binding free energy calculation showed that the binding affinity of hit compounds was higher than that of the reference compound PBD150. These findings suggested that the identified hit compounds showed significant potential for further biological activity studies to evaluate their inhibitory effects on hQC.