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dockYard--一个协助蛋白质-蛋白质对接建模的存储库。

dockYard--a repository to assist modeling of protein-protein docking.

机构信息

Bioinformatics Centre, Supercomputer Education Research Centre, Indian Institute of Science, Bangalore, 560 012, India.

出版信息

J Mol Model. 2011 Mar;17(3):599-606. doi: 10.1007/s00894-010-0758-9. Epub 2010 Jun 4.

DOI:10.1007/s00894-010-0758-9
PMID:20524020
Abstract

In the absence of interlogs, building docking models is a time intensive task, involving generation of a large pool of docking decoys followed by refinement and screening to identify near native docking solutions. This limits the researcher interested in building docking methods with the choice of benchmarking only a limited number of protein complexes. We have created a repository called dockYard ( http://pallab.serc.iisc.ernet.in/dockYard ), that allows modelers interested in protein-protein interaction to access large volume of information on protein dimers and their interlogs, and also download decoys for their work if they are interested in building modeling methods. dockYard currently offers four categories of docking decoys derived from: Bound (native dimer co-crystallized), Unbound (individual subunits are crystallized, as well as the target dimer), Variants (match the previous two categories in at least one subunit with 100% sequence identity), and Interlogs (match the previous categories in at least one subunit with ≥ 90% or ≥ 50% sequence identity). The web service offers options for full or selective download based on search parameters. Our portal also serves as a repository to modelers who may want to share their decoy sets with the community.

摘要

在没有相互作用日志的情况下,构建对接模型是一项耗时的任务,需要生成大量对接诱饵,然后进行细化和筛选,以确定接近天然的对接解决方案。这限制了有兴趣构建对接方法的研究人员只能选择有限数量的蛋白质复合物进行基准测试。我们创建了一个名为 dockYard(http://pallab.serc.iisc.ernet.in/dockYard)的存储库,它允许对蛋白质-蛋白质相互作用感兴趣的建模人员访问大量关于蛋白质二聚体及其相互作用日志的信息,如果他们有兴趣构建建模方法,还可以下载诱饵。dockYard 目前提供四类对接诱饵,来源于:结合(天然二聚体共结晶)、未结合(单个亚基结晶,以及目标二聚体)、变体(在至少一个亚基中与前两类匹配,具有 100%序列同一性)和相互作用日志(在至少一个亚基中与前两类匹配,具有≥90%或≥50%序列同一性)。该网络服务根据搜索参数提供全部或选择性下载选项。我们的门户还充当建模人员的存储库,他们可能希望与社区共享他们的诱饵集。

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Inference of macromolecular assemblies from crystalline state.从晶体状态推断大分子组装体
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