Expanding Metabolic Models to Three Dimensions

With the increasing coverage of genomic, proteomic and metabolomic data, we are witnessing the birth of a new era in biology- one which will change the face of medical research and clinical practice in unprecedented ways. A significant challenge that impedes further advancement of genomic medicine is understanding how to effectively integrate and translate big biological data into transformative health practices that impact patients lives. Recently, we have integrated protein structural information with the human metabolic network which provides a compelling new angle and scale for studying disease (Brunk et al. Nature Biotechnology 2018). Expanding reconstructions in this way provides new avenues for understanding how biochemical processes relate to mechanisms at the atomic scale. In this talk, I will discuss several recent applications that exemplify a new scientific frontier which has been termed "structural systems biology". For the first time, relationships between human metabolic genes, their encoded proteins, and reactions they catalyze can be described in the context of specific 3D configurations, interactions, and properties. Such capabilities open the door to exploring the spatial relationships of cancer mutations, the influence of SNPs on drug or metabolic responses, as well as the mechanistic underpinnings of basic biological processes like protein translation.