Suppr超能文献

基于系统生物学的靶点鉴定和药物发现的最新进展。

Recent Advances in the System Biology-based Target Identification and Drug Discovery.

机构信息

Department of Bioengineering, The University of Information Science and Technology (UIST) St. Paul the Apostle, Macedonia, the Former Yugoslav Republic of.

Department of Molecular and Cellular Engineering, Sam Higginbottom University of Agriculture, Technology and Sciences Naini, Allahabad, India.

出版信息

Curr Top Med Chem. 2018;18(20):1737-1744. doi: 10.2174/1568026618666181025112344.

Abstract

The enormous quantity of publicly available active chemical ligand and biological receptor data knowledge allows scientists to retreat several open questions by the analysis and systematic integration of these complex unique data. Systems biology plays a crucial role through the constructive alignment of bio-physiochemical monitoring of gene, protein along with metabolites from the complex data. Further, it integrates information within the data and responses (metabolic and signaling pathway) which lead to the formulation of computational models for the elucidation of structure and function of the molecular determinant. The system biology methods utilize big complex high throughput data for the identification of the whole drug target and for the mechanism of action to lead compound characterization. Nowadays, the system biology is one of the most popular approaches to characterize proteinligand interaction on a large scale and is vital to address a complex mode of the drug action to clinical indications. The network of protein-ligand interactions also reveals the correlation between molecular functions of the cell with their physiological processes which help to design safe and effective ligands for drug development. Here, we review recent attempts to apply system biology-based approaches with large-scale network analyses to predict novel interactions of ligand and targets. We also deliver an essential step involved in the discovery and development of such multi-target drugs by identifying the group of proteins targeted by a particular ligand, leading to innovation in therapeutic research.

摘要

大量公开可用的活性化学配体和生物受体数据知识使科学家能够通过分析和系统整合这些复杂独特的数据来解决几个悬而未决的问题。系统生物学通过对基因、蛋白质以及代谢物的生物物理化学监测的建设性调整,发挥着至关重要的作用,这些监测来自复杂的数据。此外,它还整合了数据和响应(代谢和信号通路)中的信息,从而为阐明分子决定因素的结构和功能构建计算模型。系统生物学方法利用大量复杂的高通量数据来识别整个药物靶标和作用机制,从而对先导化合物进行特征描述。如今,系统生物学是大规模表征蛋白质-配体相互作用的最流行方法之一,对于解决药物作用的复杂模式与临床适应症至关重要。蛋白质-配体相互作用网络还揭示了细胞的分子功能与其生理过程之间的相关性,这有助于设计安全有效的药物开发配体。在这里,我们回顾了最近应用基于系统生物学的方法和大规模网络分析来预测配体和靶标新相互作用的尝试。我们还通过确定特定配体靶向的蛋白质组,来识别此类多靶标药物的发现和开发过程中的关键步骤,从而推动治疗研究的创新。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验