Physics

Human disease

Biology

Gene

Metabolic network

Genome

Human genome

Variation (astronomy)

Astrophysics

Metabolism

Computational biology

Cell metabolism

Genetics

Biochemistry

Nature Biotechnology

Large-scale integration of metabolite and protein structural data with existing networks of human metabolism provides insights into gene function and how drugs affect metabolic response. 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                              .

Recon3D enables a three-dimensional view of gene variation in human metabolism