PPT-DB: the protein property prediction and testing database.
PPT-DB: the protein property prediction and testing database.
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DOI：
10.1093/nar/gkm800
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发表时间：
2008-01
影响因子：
14.9
通讯作者：
Lin G
中科院分区：
文献类型：
--
作者：
Wishart DS;Arndt D;Berjanskii M;Guo AC;Shi Y;Shrivastava S;Zhou J;Zhou Y;Lin G
蛋白质性质预测和测试数据库（PPT-DB）是一个包含近30个精心策划的数据库的数据库，每个数据库都包含通常预测的蛋白质性质信息。这些特性包括结构（即二级结构、接触顺序、二硫键配对）和动态（即顺序参数、B因子、折叠速率）特征，这些特征已从各种来源进行测量、推导或制表。PPT-DB的设计有两个目的。首先，它的目的是作为一个集中的，最新的，免费下载和易于查询的可预测的或“衍生”的蛋白质属性数据库。在这个角色中，PPT-DB可以作为开发人员的一站式，完全标准化的存储库，以获得他们可能希望创建的几乎任何类型的蛋白质特性预测程序所需的培训，测试和验证数据。PPT-DB可以发挥的第二个作用是作为基于同源性的蛋白质性质预测的工具。用户可以用感兴趣的序列查询PPT-DB，并使用序列相似性搜索对PPT-DB广泛收集的具有已知性质的蛋白质预测特定性质。PPT-DB利用了众所周知的事实，即蛋白质结构和动力学性质在同源蛋白质之间是高度保守的。从PPT-DB的相似性搜索中得出的预测通常正确率为85-95%（对于分类预测，如二级结构）或表现出>0.80的相关性（对于数值预测，如可及表面积）。这种性能比通常从标准“从头算”预测获得的性能好10-20%。PPT-DB、其预测实用程序及其所有内容均可在http://www.pptdb.ca上获取
The protein property prediction and testing database (PPT-DB) is a database housing nearly 30 carefully curated databases, each of which contains commonly predicted protein property information. These properties include both structural (i.e. secondary structure, contact order, disulfide pairing) and dynamic (i.e. order parameters, B-factors, folding rates) features that have been measured, derived or tabulated from a variety of sources. PPT-DB is designed to serve two purposes. First it is intended to serve as a centralized, up-to-date, freely downloadable and easily queried repository of predictable or ‘derived’ protein property data. In this role, PPT-DB can serve as a one-stop, fully standardized repository for developers to obtain the required training, testing and validation data needed for almost any kind of protein property prediction program they may wish to create. The second role that PPT-DB can play is as a tool for homology-based protein property prediction. Users may query PPT-DB with a sequence of interest and have a specific property predicted using a sequence similarity search against PPT-DB's extensive collection of proteins with known properties. PPT-DB exploits the well-known fact that protein structure and dynamic properties are highly conserved between homologous proteins. Predictions derived from PPT-DB's similarity searches are typically 85–95% correct (for categorical predictions, such as secondary structure) or exhibit correlations of >0.80 (for numeric predictions, such as accessible surface area). This performance is 10–20% better than what is typically obtained from standard ‘ab initio’ predictions. PPT-DB, its prediction utilities and all of its contents are available at http://www.pptdb.ca
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