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基于药效团的神经退行性疾病靶标犬尿氨酸-3-单加氧酶新型竞争性抑制剂的虚拟筛选。

Pharmacophore-Based Virtual Screening of Novel Competitive Inhibitors of the Neurodegenerative Disease Target Kynurenine-3-Monooxygenase.

机构信息

Division of Bio-Medical Science & Technology, KIST School, Korea University of Science and Technology (UST), Seoul 02792, Korea.

Convergence Research Center for Diagnosis, Treatment and Care System of Dementia, Korea Institute of Science and Technology (KIST), Seoul 02792, Korea.

出版信息

Molecules. 2021 May 31;26(11):3314. doi: 10.3390/molecules26113314.

Abstract

The pathogenesis of several neurodegenerative diseases such as Alzheimer's or Huntington's disease has been associated with metabolic dysfunctions caused by imbalances in the brain and cerebral spinal fluid levels of neuroactive metabolites. Kynurenine monooxygenase (KMO) is considered an ideal therapeutic target for the regulation of neuroactive tryptophan metabolites. Despite significant efforts, the known KMO inhibitors lack blood-brain barrier (BBB) permeability and upon the mimicking of the substrate binding mode, are subject to produce reactive oxygen species as a side reaction. The computational drug design is further complicated by the absence of complete crystal structure information for human KMO (hKMO). In the current work, we performed virtual screening of readily available compounds using several protein-ligand complex pharmacophores. Each of the pharmacophores accounts for one of three distinct reported KMO protein-inhibitor binding conformations. As a result, six novel KMO inhibitors were discovered based on an in vitro fluorescence assay. Compounds VS1 and VS6 were predicted to be BBB permeable and avoid the hydrogen peroxide production dilemma, making them valuable, novel hit compounds for further drug property optimization and advancement in the drug design pipeline.

摘要

几种神经退行性疾病(如阿尔茨海默病或亨廷顿病)的发病机制与脑和脑脊液中神经活性代谢物失衡引起的代谢功能障碍有关。犬尿氨酸单加氧酶(KMO)被认为是调节神经活性色氨酸代谢物的理想治疗靶点。尽管进行了大量研究,但已知的 KMO 抑制剂缺乏血脑屏障(BBB)通透性,并且在模拟底物结合模式时,会产生作为副反应的活性氧。由于缺乏人源 KMO(hKMO)的完整晶体结构信息,计算药物设计进一步复杂化。在当前的工作中,我们使用几种蛋白-配体复合物药效团对现成的化合物进行虚拟筛选。每个药效团代表三种已报道的 KMO 蛋白-抑制剂结合构象之一。结果,基于体外荧光测定法发现了六种新型 KMO 抑制剂。化合物 VS1 和 VS6 被预测为具有 BBB 通透性,并避免了过氧化氢产生的困境,使它们成为有价值的新型命中化合物,可进一步优化药物性质并推进药物设计管道的进展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/689b/8199213/4b08ea038138/molecules-26-03314-g001.jpg

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