Centre for Synthesis and Chemical Biology, School of Biomolecular and Biomedical Science, UCD Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland.
Nucleic Acids Res. 2010 Nov;38(20):e186. doi: 10.1093/nar/gkq726. Epub 2010 Aug 19.
Large amounts of data are being generated annually on the connection between the sequence, structure and function of proteins using site-directed mutagenesis, protein design and directed evolution techniques. These data provide the fundamental building blocks for our understanding of protein function, molecular biology and living organisms in general. However, much experimental data are never deposited in databases and is thus 'lost' in journal publications or in PhD theses. At the same time theoretical scientists are in need of large amounts of experimental data for benchmarking and calibrating novel predictive algorithms, and theoretical progress is therefore often hampered by the lack of suitable data to validate or disprove a theoretical assumption. We present PEAT (Protein Engineering Analysis Tool), an application that integrates data deposition, storage and analysis for researchers carrying out protein engineering projects or biophysical characterization of proteins. PEAT contains modules for DNA sequence manipulation, primer design, fitting of biophysical characterization data (enzyme kinetics, circular dichroism spectroscopy, NMR titration data, etc.), and facilitates sharing of experimental data and analyses for a typical university-based research group. PEAT is freely available to academic researchers at http://enzyme.ucd.ie/PEAT.
大量数据正在通过定点诱变、蛋白质设计和定向进化技术生成,这些数据记录了蛋白质序列、结构和功能之间的联系。这些数据为我们理解蛋白质功能、分子生物学和一般的生命有机体提供了基本的构建块。然而,许多实验数据从未被存入数据库,因此在期刊出版物或博士论文中“丢失”。与此同时,理论科学家需要大量的实验数据来对新的预测算法进行基准测试和校准,因此理论进展常常受到缺乏合适的数据来验证或反驳理论假设的阻碍。我们介绍了 PEAT(蛋白质工程分析工具),这是一个应用程序,用于整合进行蛋白质工程项目或蛋白质生物物理特性分析的研究人员的数据存储和分析。PEAT 包含用于 DNA 序列操作、引物设计、拟合生物物理特性数据(酶动力学、圆二色光谱学、NMR 滴定数据等)的模块,并为典型的基于大学的研究小组共享实验数据和分析提供便利。PEAT 可在 http://enzyme.ucd.ie/PEAT 免费供学术研究人员使用。