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Pathophysiology, Etiology, Epidemiology of Type 1 Diabetes and Computational Approaches for Immune Targets and Therapy

机译:病理生理学,病因,1型糖尿病的流行病学和免疫靶和治疗的计算方法

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摘要

Autoimmune diseases occur when the body's natural defense system fails to differentiate its own cells from the foreign cells and mistakenly attacks the healthy cells. Among the autoimmune diseases, the most common serious disease is the type 1 diabetes (T1D). Biomarkers like c-peptide, autoantibodies, and glycated molecules are now widely used for the early diagnosis of diabetes. However, the diverse nature of biomarkers and the available autoantibodies as biomarkers are not enough to differentiate the heterogeneity inherent in T1D. Novel biomarkers have allowed the introduction of bioinformatics for assimilating the new data into clinical tools. Computer-aided drug design contributes to the discovery of novel autoantibodies, and molecular docking promises to enhance it. Moreover, the study of the pathophysiology of diabetes via molecular simulation has been proposed. In this review article, we focus on the characterization of the etiology, epidemiological factors, and mechanisms of hyperglycemia that induce cellular damage due to oxidative stress and proinflammatory responses. We also decribe novel biomarkers used for the detection of beta-cell destruction and diagnosis at early stages. Bioinformatics tools including molecular docking, sequence alignment, and homology modeling are also presented. This report supports researchers in drug design, in disease detection at an early phase, and in therapy development for T1D-associated complications.
机译:当身体的自然防御系统未能将其自身细胞与外部细胞分化并错误地攻击健康细胞时,发生自身免疫疾病。在自身免疫疾病中,最常见的严重疾病是1型糖尿病(T1D)。现在广泛用于糖尿病,自身抗体和糖化分子等生物标志物现在广泛用于糖尿病的早期诊断。然而,生物标志物的多样性性质和可用的自身抗体作为生物标志物不足以区分T1D中固有的异质性。新型生物标志物允许引入生物信息学,将新数据与临床工具同化。计算机辅助药物设计有助于发现新型自身抗体,以及分子对接的承诺增强它。此外,提出了通过分子模拟的糖尿病病理生理学的研究。在本综述文章中,我们专注于表征病因,流行病学因素和高血糖血症的机制,诱导由于氧化应激和促炎反应引起的细胞损伤。我们还减少用于检测早期阶段的β细胞破坏和诊断的新型生物标志物。还提出了包括分子对接,序列对准和同源性建模的生物信息学工具。本报告支持药物设计的研究人员,在早期阶段进行疾病检测,以及治疗的T1D相关并发症的治疗。

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