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靶向人类精氨酰转移酶和翻译后蛋白质精氨酰化:一种基于药效团的多层筛选和分子动力学方法,用于发现具有治疗前景的新型抑制剂。

Targeting human arginyltransferase and post-translational protein arginylation: a pharmacophore-based multilayer screening and molecular dynamics approach to discover novel inhibitors with therapeutic promise.

作者信息

Naga R, Poddar S, Jana A, Maity S, Kar P, Banerjee D R, Saha S

机构信息

Department of Biotechnology, National Institute of Technology, Durgapur, India.

Department of Biosciences and Biomedical Engineering, IIT Indore, Indore, India.

出版信息

SAR QSAR Environ Res. 2025 Jan;36(1):1-28. doi: 10.1080/1062936X.2025.2452001. Epub 2025 Jan 23.

Abstract

Protein arginylation mediated by arginyltransferase 1 is a crucial regulator of cellular processes in eukaryotes by affecting protein stability, function, and interaction with other macromolecules. This enzyme and its targets are of immense interest for modulating cellular processes in diseased states like obesity and cancer. Despite being an important target molecule, no highly potent drug against this enzyme exists. Therefore, this study focuses on discovering potential inhibitors of human arginyltransferase 1 by computational approaches where screening of over 300,000 compounds from natural and synthetic databases was done using a pharmacophore model based on common features among known inhibitors. The drug-like properties and potential toxicity of the compounds were also assessed in the study to ensure safety and effectiveness. Advanced methods, including molecular simulations and binding free energy calculations, were performed to evaluate the stability and binding efficacy of the most promising candidates. Ultimately, three compounds were identified as potent inhibitors, offering new avenues for developing therapies targeting arginyltransferase 1.

摘要

由精氨酰转移酶1介导的蛋白质精氨酰化作用,通过影响蛋白质的稳定性、功能以及与其他大分子的相互作用,成为真核生物细胞过程的关键调节因子。该酶及其作用靶点对于调控肥胖和癌症等疾病状态下的细胞过程具有重大意义。尽管它是一个重要的靶标分子,但目前尚无针对该酶的高效药物。因此,本研究聚焦于通过计算方法发现人精氨酰转移酶1的潜在抑制剂,即利用基于已知抑制剂共同特征的药效团模型,对来自天然和合成数据库的30多万种化合物进行筛选。研究中还评估了这些化合物的类药性质和潜在毒性,以确保其安全性和有效性。运用包括分子模拟和结合自由能计算在内的先进方法,对最具潜力的候选物的稳定性和结合效力进行评估。最终,确定了三种化合物为强效抑制剂,为开发靶向精氨酰转移酶1的疗法提供了新途径。

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