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计算蛋白质组学平台解析蛋白质-蛋白质相互作用的能力。

The power of computational proteomics platforms to decipher protein-protein interactions.

机构信息

Center for Bioinformatics, Simulation and Modeling (CBSM), Faculty of Engineering, Universidad de Talca, Talca, Chile; Millennium Nucleus of Ion Channel-Associated Diseases (MiNICAD), Santiago, Chile.

Millennium Nucleus of Ion Channel-Associated Diseases (MiNICAD), Santiago, Chile; Program of Cellular and Molecular Biology, Institute of Biomedical Sciences (ICBM), Faculty of Medicine, Universidad de Chile, Santiago, Chile.

出版信息

Curr Opin Struct Biol. 2024 Oct;88:102882. doi: 10.1016/j.sbi.2024.102882. Epub 2024 Jul 13.

Abstract

Adopting computational tools for analyzing extensive biological datasets has profoundly transformed our understanding and interpretation of biological phenomena. Innovative platforms have emerged, providing automated analysis to unravel essential insights about proteins and the complexities of their interactions. These computational advancements align with traditional studies, which employ experimental techniques to discern and quantify physical and functional protein-protein interactions (PPIs). Among these techniques, tandem mass spectrometry is notably recognized for its precision and sensitivity in identifying PPIs. These approaches might serve as important information enabling the identification of PPIs with potential pharmacological significance. This review aims to convey our experience using computational tools for detecting PPI networks and offer an analysis of platforms that facilitate predictions derived from experimental data.

摘要

采用计算工具分析广泛的生物数据集,极大地改变了我们对生物现象的理解和解释。创新的平台已经出现,提供自动化分析,以揭示关于蛋白质及其相互作用复杂性的重要见解。这些计算进展与传统研究一致,传统研究采用实验技术来识别和量化蛋白质-蛋白质相互作用(PPIs)的物理和功能。在这些技术中,串联质谱法以其在识别 PPI 方面的精确性和敏感性而受到特别认可。这些方法可能是识别具有潜在药理学意义的 PPI 的重要信息来源。本综述旨在介绍我们使用计算工具检测 PPI 网络的经验,并对促进从实验数据得出预测的平台进行分析。

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