Yuan Shuying, Chen Yanwen, Zou Lin, Lu Xinrong, Liu Ruijie, Zhang Shaoxing, Zhang Yuxin, Chen Cuiying, Cheng Dongqing, Chen Li, Sun Guiqin
School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang Province, China.
Department of Medical Microbiology and Parasitology, Key Laboratory of Medical Molecular Virology of Ministries of Education and Health, School of Basic Medical Sciences, Fudan University, Shanghai, 200032, China.
Heliyon. 2024 Apr 6;10(8):e28787. doi: 10.1016/j.heliyon.2024.e28787. eCollection 2024 Apr 30.
Genetic diseases are currently diagnosed by functional mutations. However, only some mutations are associated with disease. It is necessary to establish a quick prediction model for clinical screening. Pathogenic mutations in NGLY1 cause a rare autosomal recessive disease known as congenital disorder of deglycosylation (NGLY1-CDDG). Although NGLY1-CDDG can be diagnosed through gene sequencing, clinical relevance of a detected mutation in NGLY1 needs to be further confirmed. In this study, taken NGLY1-CDDG as an example, a comprehensive and practical predictive model for pathogenic mutations on NGLY1 through an NGLY1/Glycopeptide complex model was constructed, the binding sites of NGLY1 and glycopeptides were simulated, and an in vitro enzymatic assay system was established to facilitate quick clinical decisions for NGLY1-CDDG patients. The docking model covers 42 % of reported NGLY1-CDDG missense mutations (5/12). All reported mutations were subjected to in vitro enzymatic assay in which 18 mutations were dysfunctional (18/30). In addition, a full spectrum of functional R328 mutations was assayed and 11 mutations were dysfunctional (11/19). In this study, a model of NGLY1 and glycopeptides was built for potential functional mutations in NGLY1. In addition, the effect of potential regulatory compounds, including N-acetyl-l-cysteine and dithiothreitol, on NGLY1 was examined. The established in vitro assay may serve as a standard protocol to facilitate rapid diagnosis of all mutations in NGLY1-CDDG. This method could also be applied as a comprehensive and practical predictive model for the other rare genetic diseases.
目前，遗传疾病是通过功能性突变来诊断的。然而，只有一些突变与疾病相关。有必要建立一个用于临床筛查的快速预测模型。NGLY1基因中的致病突变会导致一种罕见的常染色体隐性疾病，即先天性糖基化障碍（NGLY1-CDDG）。虽然可以通过基因测序来诊断NGLY1-CDDG，但检测到的NGLY1突变的临床相关性仍需进一步确认。在本研究中，以NGLY1-CDDG为例，通过NGLY1/糖肽复合物模型构建了一个全面且实用的NGLY1致病突变预测模型，模拟了NGLY1与糖肽的结合位点，并建立了体外酶分析系统，以促进对NGLY1-CDDG患者的快速临床决策。对接模型涵盖了42%已报道的NGLY1-CDDG错义突变（5/12）。所有已报道的突变都进行了体外酶分析，其中18个突变功能异常（18/30）。此外，对R328位点的所有功能性突变进行了分析，其中11个突变功能异常（11/19）。在本研究中，构建了NGLY1与糖肽的模型，用于预测NGLY1的潜在功能突变。此外，还研究了包括N-乙酰-L-半胱氨酸和二硫苏糖醇在内的潜在调节化合物对NGLY1的影响。所建立的体外分析方法可作为一个标准方案，以促进对NGLY1-CDDG所有突变的快速诊断。该方法也可作为其他罕见遗传疾病的全面且实用的预测模型。
