Genome-Scale Model Driven Characterization of the Effect of Single Nucleotide Polymorphisms on Erythrocyte Metabolism

The recent expansion of genome-scale models of metabolism (GEMs) to explicitly include the three-dimensional structure of proteins has opened up novel pharmacological applications of these models. The knowledge gained from decades of studies on protein structure, function, and activity presents an emerging opportunity to integrate this information with GEMs and constraint-based modeling. Previous work has utilized protein structures to add an additional layer of constraints to the models of T. maritima [1] and E. coli [2, 3]. We have built and improved upon this integrated structural systems biology framework, streamlining previous methods to add experimentally determined and computationally modeled structures of proteins, while integrating a molecular-level analysis of the impact of single nucleotide polymorphisms (SNPs) on drug response in the context of the erythrocyte. We explore the use of a variety of molecular modeling tools and their ability to be utilized at the genome-scale, including homology modeling, computational docking, molecular dynamics, and free-energy calculations. Case studies of three metabolic enzymes from the human erythrocyte are presented in which a clinically significant association was found when drugs were administered to populations with a SNP and to those without. This study also represents the first creation of a genome-scale model with protein structures (GEM-PRO) for a eukaryotic model, accounting for the unique isozymes present in the erythrocyte as well as known protein complexes. The resulting pipeline provides an extensible framework for structural systems pharmacology applications to any genome-scale model.  

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2. Chang RL, Andrews K, Kim D, Li Z, Godzik A, Palsson BO. Structural systems biology evaluation of metabolic thermotolerance in Escherichia coli. Science. American Association for the Advancement of Science; 2013;340: 1220–1223.

3. Chang RL, Xie L, Bourne PE, Palsson BO. Antibacterial mechanisms identified through structural systems pharmacology. BMC Syst Biol. BioMed Central Ltd; 2013;7: 102.