3D-Beacons: Decreasing the gap between protein sequences and structures through a federated network of protein structure data resources
3D-Beacons: Decreasing the gap between protein sequences and structures through a federated network of protein structure data resources
复制标题
3D-Beacons：通过蛋白质结构数据资源的联合网络减少蛋白质序列和结构之间的差距
DOI：
10.1101/2022.08.01.501973
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Varadi M
中科院分区：
文献类型：
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作者：
Varadi M
虽然科学家们经常可以从蛋白质的三维四级结构中推断出它们的生物学功能，但已知的蛋白质序列与实验确定的结构之间的差距仍在不断扩大。这一问题的潜在解决方案是通过更复杂的计算蛋白质建模方法提出的。虽然大多数方法本身往往很强大，但它们都有优点和缺点。因此，研究人员可以检查来自不同模型提供商的模型，并执行比较分析，以确定哪些模型最能解决其特定用例。为了让更广泛的科学界更容易地访问来自大量模型提供者的数据，我们建立了3D-Beacons，这是一个合作倡议，旨在创建一个具有统一数据访问机制的联合网络。3D-Beacons Network允许研究人员整理来自最先进和专业模型提供商以及蛋白质数据库的实验确定和理论蛋白质模型的坐标文件和元数据。
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.