Dockground resource for protein recognition studies
Dockground resource for protein recognition studies
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DOI：
10.1002/pro.4481
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发表时间：
2022-12-01
期刊：
影响因子：
8
通讯作者：
Vakser，Ilya A.
中科院分区：
文献类型：
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作者：
Collins，Keeley W.;Copeland，Matthew M.;Vakser，Ilya A.
蛋白质相互作用的结构信息对于在分子水平上表征生命过程是必不可少的。虽然一小部分已知的蛋白质相互作用具有实验确定的结构，但蛋白质复合物的计算建模（蛋白质对接）必须填补差距。TheDockgroundresource（http：dockground.compbio.ku.edu）提供了一系列用于开发和测试蛋白质对接技术的数据集。目前，Dockground包含绑定和未绑定（实验确定和模拟）蛋白质结构，模型-模型复合物，实验确定和建模蛋白质的对接诱饵，以及比较对接的模板的数据集。Dockgroundbound蛋白质数据集是一个核心集，其他Dockgrounddatasets从该数据集生成。它被设计为一个包含实验确定的蛋白质-蛋白质复合物信息的关系型PostgreSQL数据库。这份报告介绍了数据集的现状、新的自动更新程序以及核心数据集的进一步发展。我们还提出了一个newDockgroundinteractive Web界面，它允许搜索的各种参数，如发布日期，多聚体状态，复杂的类型，结构分辨率，等等，可视化的搜索结果与一些可定制的参数，以及可下载的数据集与预定义的序列和结构冗余的水平。
Structural information of protein–protein interactions is essential for characterization of life processes at the molecular level. While a small fraction of known protein interactions has experimentally determined structures, computational modeling of protein complexes (protein docking) has to fill the gap. TheDockgroundresource (http://dockground.compbio.ku.edu) provides a collection of datasets for the development and testing of protein docking techniques. Currently,Dockgroundcontains datasets for the bound and the unbound (experimentally determined and simulated) protein structures, model–model complexes, docking decoys of experimentally determined and modeled proteins, and templates for comparative docking. TheDockgroundbound proteins dataset is a core set, from which otherDockgrounddatasets are generated. It is devised as a relational PostgreSQL database containing information on experimentally determined protein–protein complexes. This report on theDockgroundresource describes current status of the datasets, new automated update procedures and further development of the core datasets. We also present a newDockgroundinteractive web interface, which allows search by various parameters, such as release date, multimeric state, complex type, structure resolution, and so on, visualization of the search results with a number of customizable parameters, as well as downloadable datasets with predefined levels of sequence and structure redundancy.