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将富集方法与蛋白质组学相结合以了解和治疗疾病。

Coupling enrichment methods with proteomics for understanding and treating disease.

作者信息

Kumar Amit, Baycin-Hizal Deniz, Shiloach Joseph, Bowen Michael A, Betenbaugh Michael J

机构信息

Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA; Antibody Discovery and Protein Engineering, MedImmune LLC, One MedImmune Way, Gaithersburg, MD, USA; Biotechnology Core Laboratory, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA.

出版信息

Proteomics Clin Appl. 2015 Feb;9(1-2):33-47. doi: 10.1002/prca.201400097. Epub 2015 Jan 19.

Abstract

Owing to recent advances in proteomics analytical methods and bioinformatics capabilities there is a growing trend toward using these capabilities for the development of drugs to treat human disease, including target and drug evaluation, understanding mechanisms of drug action, and biomarker discovery. Currently, the genetic sequences of many major organisms are available, which have helped greatly in characterizing proteomes in model animal systems and humans. Through proteomics, global profiles of different disease states can be characterized (e.g. changes in types and relative levels as well as changes in PTMs such as glycosylation or phosphorylation). Although intracellular proteomics can provide a broad overview of physiology of cells and tissues, it has been difficult to quantify the low abundance proteins which can be important for understanding the diseased states and treatment progression. For this reason, there is increasing interest in coupling comparative proteomics methods with subcellular fractionation and enrichment techniques for membranes, nucleus, phosphoproteome, glycoproteome as well as low abundance serum proteins. In this review, we will provide examples of where the utilization of different proteomics-coupled enrichment techniques has aided target and biomarker discovery, understanding the drug targeting mechanism, and mAb discovery. Taken together, these improvements will help to provide a better understanding of the pathophysiology of various diseases including cancer, autoimmunity, inflammation, cardiovascular disease, and neurological conditions, and in the design and development of better medicines for treating these afflictions.

摘要

由于蛋白质组学分析方法和生物信息学能力的最新进展,利用这些能力开发治疗人类疾病的药物的趋势日益增长,包括靶点和药物评估、理解药物作用机制以及生物标志物发现。目前,许多主要生物体的基因序列已经可得,这在表征模式动物系统和人类的蛋白质组方面有很大帮助。通过蛋白质组学,可以表征不同疾病状态的全局概况(例如类型和相对水平的变化以及糖基化或磷酸化等翻译后修饰的变化)。尽管细胞内蛋白质组学可以提供细胞和组织生理学的广泛概述,但量化对理解疾病状态和治疗进展可能很重要的低丰度蛋白质一直很困难。因此,将比较蛋白质组学方法与亚细胞分级分离和富集技术相结合,用于膜、细胞核、磷酸蛋白质组、糖蛋白质组以及低丰度血清蛋白质的研究兴趣日益增加。在本综述中,我们将举例说明不同蛋白质组学耦合富集技术的应用如何有助于靶点和生物标志物发现、理解药物靶向机制以及单克隆抗体发现。总之,这些改进将有助于更好地理解包括癌症、自身免疫、炎症、心血管疾病和神经疾病在内的各种疾病的病理生理学,并有助于设计和开发治疗这些疾病的更好药物。

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