基于结构的HNF4α激动剂鉴定:迷迭香酸作为NAFLD治疗的有希望的候选者。

IF 4.1 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY Computational and structural biotechnology journal Pub Date : 2025-01-01 Epub Date: 2024-12-27 DOI:10.1016/j.csbj.2024.12.014
Xi Chen , Xinqi Zhu , Gang Wu , Xiaobo Wang , Yu Zhang , Nan Jiang
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引用次数: 0

摘要

预防和治疗代谢性疾病,如非酒精性脂肪性肝病(NAFLD),已成为重大的全球卫生挑战。目前的降脂药物治疗与副作用相关,包括肝毒性、横纹肌溶解和红细胞计数下降,强调迫切需要更安全的治疗方案。肝细胞核因子4α (HNF4α)已被确定为脂质代谢的关键调节因子,使其成为药物开发的一个有吸引力的靶点。在这项研究中,我们研究了四种HNF4α激动剂的结构特征和结合相互作用:Alverine, Benfluorex, n -反式咖啡乙胺(NCT)和n -反式阿魏乙胺(NFT)。我们的研究结果表明,NCT和NFT中酰胺键和芳香环形成的共轭结构增强了电子密度,可能有助于它们相对于Alverine和Benfluorex提高对HNF4α的特异性。此外,化合物的芳香族部分与HNF4α残基之间的静电相互作用在配体结合中起着至关重要的作用。利用这些见解,我们使用NCT和NFT的结合模式作为参考模板,对2131种天然化合物进行了高通量虚拟筛选。迷迭香酸是一种很有前途的HNF4α激动剂,具有较高的共识值和良好的结合亲和力。随后的生物学实验表明迷迭香酸能显著抑制HepG2细胞的增殖,这与增强细胞自噬有关。敲除HNF4α P2亚型后,HepG2对NCT和迷迭香酸的作用更加敏感。此外,NCT和迷迭香酸对仅表达HNF4α P2亚型的DLD-1细胞的增殖无明显抑制作用。综上所述,迷迭香酸是一种很有前景的HNF4α激动剂,可以更有效地激活HNF4α P1亚型,具有治疗NAFLD的潜力,为开发疗效更高、副作用更小的新型降脂药物提供了基础。数据可得性:应要求提供数据。
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Structure-based identification of HNF4α agonists: Rosmarinic acid as a promising candidate for NAFLD treatment
The prevention and treatment of metabolic disorders, such as non-alcoholic fatty liver disease (NAFLD), have emerged as critical global health challenges. Current lipid-lowering pharmacotherapies are associated with side effects, including hepatotoxicity, rhabdomyolysis, and decreased erythrocyte counts, underscoring the urgent need for safer therapeutic alternatives. Hepatocyte nuclear factor 4α (HNF4α) has been identified as a pivotal regulator of lipid metabolism, making it an attractive target for drug development. In this study, we investigated the structural characteristics and binding interactions of four HNF4α agonists: Alverine, Benfluorex, N-trans caffeoyltyramine (NCT), and N-trans feruloyltyramine (NFT). Our results indicate that the conjugated structure formed by the amide bond and the aromatic ring in NCT and NFT enhances electron density, potentially contributing to their increased specificity for HNF4α relative to Alverine and Benfluorex. Additionally, electrostatic interactions between the aromatic moieties of the compounds and HNF4α residues were found to play a crucial role in ligand binding. Leveraging these insights, we performed a high-throughput virtual screening of 2131 natural compounds, using the binding modes of NCT and NFT as reference templates. Rosmarinic acid emerged as a promising HNF4α agonist, exhibiting a high consensus score and favorable binding affinity. Subsequent biological assays demonstrated that rosmarinic acid significantly inhibited HepG2 cell proliferation which related to the enhancement of autophagy. After the knockdown of P2 isoform of HNF4α, HepG2 was more sensitive to the administration of NCT and rosmarinic acid. Furthermore, the proliferation of DLD-1 cell, which only expresses the P2 isoform of HNF4α, was not significantly inhibited by the administration of NCT and rosmarinic acid. Collectively, these findings suggest that rosmarinic acid is a promising HNF4α agonist which is more effective to activate the P1 isoform of HNF4α and holds potential as an effective treatment for NAFLD, providing a foundation for the development of novel lipid-lowering drugs with enhanced efficacy and reduced side effect.

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Data will be made available on request.
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来源期刊
Computational and structural biotechnology journal
Computational and structural biotechnology journal Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
9.30
自引率
3.30%
发文量
540
审稿时长
6 weeks
期刊介绍: Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to: Structure and function of proteins, nucleic acids and other macromolecules Structure and function of multi-component complexes Protein folding, processing and degradation Enzymology Computational and structural studies of plant systems Microbial Informatics Genomics Proteomics Metabolomics Algorithms and Hypothesis in Bioinformatics Mathematical and Theoretical Biology Computational Chemistry and Drug Discovery Microscopy and Molecular Imaging Nanotechnology Systems and Synthetic Biology
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