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3D-Beacons:通过蛋白质结构数据资源的联邦网络缩小蛋白质序列和结构之间的差距。

3D-Beacons: decreasing the gap between protein sequences and structures through a federated network of protein structure data resources.

机构信息

European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton CB10 1SA, UK.

Department of Structural and Molecular Biology, UCL, London WC1E 6BT, UK.

出版信息

Gigascience. 2022 Nov 30;11. doi: 10.1093/gigascience/giac118.

Abstract

While scientists can often infer the biological function of proteins from their 3-dimensional quaternary structures, the gap between the number of known protein sequences and their experimentally determined structures keeps increasing. A potential solution to this problem is presented by ever more sophisticated computational protein modeling approaches. While often powerful on their own, most methods have strengths and weaknesses. Therefore, it benefits researchers to examine models from various model providers and perform comparative analysis to identify what models can best address their specific use cases. To make data from a large array of model providers more easily accessible to the broader scientific community, we established 3D-Beacons, a collaborative initiative to create a federated network with unified data access mechanisms. The 3D-Beacons Network allows researchers to collate coordinate files and metadata for experimentally determined and theoretical protein models from state-of-the-art and specialist model providers and also from the Protein Data Bank.

摘要

虽然科学家们通常可以从蛋白质的三维四级结构推断其生物学功能,但已知蛋白质序列的数量与其实验确定的结构之间的差距仍在不断扩大。解决这个问题的一种潜在方法是采用越来越复杂的计算蛋白质建模方法。虽然这些方法本身通常很强大,但大多数方法都有其优缺点。因此,研究人员检查来自不同模型提供者的模型并进行比较分析以确定哪些模型最适合他们的特定用例是有益的。为了使来自大量模型提供者的数据更容易被更广泛的科学界访问,我们建立了 3D-Beacons,这是一个创建具有统一数据访问机制的联邦网络的合作计划。3D-Beacons 网络允许研究人员从最先进的和专业的模型提供者以及蛋白质数据库中整理坐标文件和实验确定的和理论蛋白质模型的元数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2046/9709962/09eb08db7ee3/giac118fig1.jpg

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