title: Using models of the myocyte for functional interpretation of cardiac proteomic data.
abstract: There has been significant progress towards the development of highly integrative computational models of the cardiac myocyte over the past decade. Models now incorporate descriptions of voltage-gated ionic currents and membrane transporters, mechanisms of calcium-induced calcium release and intracellular calcium cycling, mitochondrial ATP production and its coupling to energy-requiring membrane transport processes and mechanisms of force generation. There is an extensive literature documenting both the reconstructive and predictive abilities of these models and there is no question that an interplay between quantitative modelling and experimental investigation has become a central component of modern cardiovascular research. As data regarding the cardiovascular proteome in both health and disease emerge, integrative models of the myocyte are becoming useful tools for interpreting the functional significance of changes in protein expression and post-translational modifications (PTMs). Data of particular importance include information on: (a) changes of expressed protein level, (b) changes of protein PTMs, (c) protein localization, and (d) protein-protein interactions, as it is often possible to incorporate and interpret the functional significance of such findings using computational models. We provide two examples of how models may be used in this fashion. In the first example, we show how information on altered expression of the sarcoplasmic reticulum Ca2+-ATPase, when interpreted through the use of a computational model, has provided key insights into fundamental mechanisms regulating cardiac action potential duration. In the second example, we show how information on the effects of phosphorylation of L-type Ca2+ channels, when interpreted through the use of a model, provides insights on how this post-translational modification alters the properties of excitation-contraction coupling and risk for arrhythmia.
authors.affiliation: Center for Cardiovascular Bioinformatics and Modelling, The Johns Hopkins University School of Medicine and Whiting School of Engineering, Baltimore, MD, USA. rwinslow@bme.jhu.edu
authors.forename: Raimond L
authors.initials: RL
authors.lastname: Winslow
authors.forename: Sonia
authors.initials: S
authors.lastname: Cortassa
authors.forename: Joseph L
authors.initials: JL
authors.lastname: Greenstein
mesh_terms: D000818:Animals; D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation / Q000502:physiology*; D006801:Humans; D008954:Models, Biological; D032342:Muscle Cells / Q000378:metabolism*; D009206:Myocardium / Q000378:metabolism*; D025941:Protein Interaction Mapping / Q000379:methods; D011499:Protein Processing, Post-Translational / Q000502:physiology*; D020543:Proteome / Q000032:analysis / Q000737:chemistry / Q000378:metabolism*; D040901:Proteomics / Q000379:methods*
chemical_list: D020543:Proteome