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How a dynamical model can help to predict phenotype from genotype?

Santiago Schnell ( Department of Molecular and Integrative Physiology, University of Michigan Medical School )

Understanding how the phenotype of a disease arises from individual molecules and their interactions is a primary challenge in biology that mathematical approaches are poised to tackle.  Protein folding diseases are an ideal system to investigate the relationship between genotype and phenotype.  A protein folding disease can occurs when a specific protein fails to fold into its correct functional state as a result of a mutation in the protein.  In this seminar, I present a mathematical model of the protein expression and processing which we have used to investigate how the protein folding disease phenotype can be manifested. Using a continuous flow reactor model for protein processing, we found that the onset and rescue from a protein folding disease can be controlled by some combination of the transition time of proteins in the reactor, the ratio of wild-type and mutant proteins inflow rates in the reactor and a chemical interaction parameter between wild-type and mutant proteins.  Our analysis reveals potential therapeutic strategies targeting the modulation of protein folding diseases, which have been tested in cellular and animal models of Mutant INS-gene Induced Diabetes of Youth and Congenital Hypothyroidism with deficient thyroglobulin.

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