Department of Bioengineering, University of California, San Diego, San Diego,California, USA.
The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark.
Nat Biotechnol. 2018 Mar;36(3):272-281. doi: 10.1038/nbt.4072. Epub 2018 Feb 19.
Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein structure data and enables integrated analyses of metabolic functions in humans. We use Recon3D to functionally characterize mutations associated with disease, and identify metabolic response signatures that are caused by exposure to certain drugs. Recon3D represents the most comprehensive human metabolic network model to date, accounting for 3,288 open reading frames (representing 17% of functionally annotated human genes), 13,543 metabolic reactions involving 4,140 unique metabolites, and 12,890 protein structures. These data provide a unique resource for investigating molecular mechanisms of human metabolism. Recon3D is available at http://vmh.life.
基因组规模的网络重建有助于揭示代谢的分子基础。在这里，我们介绍了 Recon3D，这是一个计算资源，包括三维（3D）代谢物和蛋白质结构数据，并能够对人类的代谢功能进行综合分析。我们使用 Recon3D 对与疾病相关的突变进行功能特征分析，并确定由某些药物暴露引起的代谢反应特征。Recon3D 代表了迄今为止最全面的人类代谢网络模型，包括 3288 个开放阅读框（代表 17%的功能注释人类基因）、涉及 4140 个独特代谢物的 13543 个代谢反应，以及 12890 个蛋白质结构。这些数据为研究人类代谢的分子机制提供了独特的资源。Recon3D 可在 http://vmh.life 上获取。
