Integrating –Omics Information with Biosimulations to Assist Diagnosis and Treatment of Diabetes Mellitus in Silico

Abstract

Genomic test results were used to predict protein structure for the mitochondrial pyruvate carrier (MPC) that is a novel target for an FDA approved anit-diabetic drug, pioglitazone. Transcriptomic test results were used along with in silico drug-protein binding results to determine parameters for oral glucose tolerance and metabolic biosimulation models used to diagnose diabetes mellitus and determine the best dose for treatment, respectively. The metabolomic and fluxomic biosimulation results were used to determine the proper dose of pioglitazone. This –omic and in silico information can be integrated into comprehensive health information to assist clinicians in medical decision making.