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基于药效团模型构建和片段设计筛选海洋化合物库鉴定新型脂联素2抑制剂

Identification of Novel LCN2 Inhibitors Based on Construction of Pharmacophore Models and Screening of Marine Compound Libraries by Fragment Design.

作者信息

Zheng Ningying, Li Xuan, Zhou Nan, Luo Lianxiang

机构信息

The Marine Biomedical Research Institute of Guangdong Zhanjiang, School of Ocean and Tropical Medicine, Guangdong Medical University, Zhanjiang 524023, China.

出版信息

Mar Drugs. 2025 Jan 5;23(1):24. doi: 10.3390/md23010024.

Abstract

LCN2, a member of the lipocalin family, is associated with various tumors and inflammatory conditions. Despite the availability of known inhibitors, none have been approved for clinical use. In this study, marine compounds were screened for their ability to inhibit LCN2 using pharmacophore models. Six compounds were optimized for protein binding after being docked against the positive control Compound A. Two compounds showed promising results in ADMET screening. Molecular dynamics simulations were utilized to predict binding mechanisms, with Compound 69081_50 identified as a potential LCN2 inhibitor. MM-PBSA analysis revealed key amino acid residues that are involved in interactions, suggesting that Compound 69081_50 could be a candidate for drug development.

摘要

脂质运载蛋白2(LCN2)是脂质运载蛋白家族的成员之一,与多种肿瘤和炎症性疾病相关。尽管有已知的抑制剂,但尚无一种被批准用于临床。在本研究中,利用药效团模型筛选海洋化合物抑制LCN2的能力。六种化合物在与阳性对照化合物A对接后进行了蛋白质结合优化。两种化合物在ADMET筛选中显示出有前景的结果。利用分子动力学模拟预测结合机制,确定化合物69081_50为潜在的LCN2抑制剂。MM-PBSA分析揭示了参与相互作用的关键氨基酸残基,表明化合物69081_50可能是药物开发的候选物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f70a/11767183/0f014d97811c/marinedrugs-23-00024-g001.jpg

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