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\section{Personal Statement}
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\section{Contribution to Science} 
\subsection*{Calcium handling proteins}
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Heart failure is a serious health risk for millions of Americans and is commonly associated with substantial dysregulation of vital \catwo\ signaling pathways.  
Detailed insight into how cardiac proteins regulate \catwo\ signaling therefore offers exciting potential to combat heart disease through protein engineering and drug design.
\person\ research as a postdoc and assistant professor has yielded unprecedented molecular detail into \catwo-binding and sensing mechanisms of several prominent muscle proteins, including troponin, SERCA, parvalbumin and S100A1 \autocite{Lindert2015,Cheng2014,Kekenes-Huskey2012c,Kekenes-Huskey2012a,Lindert2012a,Scott2016,Kucharski2016}.  
These mechanisms provide exquisite control of \catwo\ handling and were unveiled through novel hybrid computational approaches I developed to couple all-atom molecular dynamics simulations with meso-scale Brownian dynamics and statistical mechanics models.
Recently, we have had an exciting development that casts doubt on a popular dogma that \catwo\ binding selectivity is confined to the binding site structure.
Namely, we found that protein internal strain and hydrophobic packing powerfully tune cation binding thermodynamics; this advancement opens the door for new strategies to redesign or potentially (ant)agonize \catwo\ binding proteins to treat diseases accompanied by substantial \catwo\ dysregulation. 

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\subsection*{Signaling in cardiac cells}
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Of equal importance to the integrity of calcium signaling at the single protein level is the close spatial and temporal coupling between integral calcium-handling proteins. 
Central to maintaining normal \catwo\ homeostasis, for instance, is the close apposition of key ion channels anchored in the cell membrane and sarcoplasmic reticulum; conversely, this coupling is frequently destroyed in later stages of heart disease.
To improve our understanding of the interrelationships between heart cell morphology, intracellular organization and cardiac signaling, I have developed three-dimensional finite element models of \catwo\ \autocite{Hake2012,Kekenes-Huskey2012} and nucleotide signaling \autocite{Kekenes-Huskey2013} that leverage realistic cellular anatomic models from confocal fluorescence and cryoelectron microscopy.
Among the most important discoveries are quantitative estimates of the contributions of protein distribution, 'co-localization' and 'buffering' to maintaining, or desynchronizing, cardiac \catwo\ signaling. 
Presently, we are extending these innovations by integrating advanced computer vision detection algorithms, which could ultimately have translational outcomes in the automated analysis of biopsied tissue. 

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\subsection*{Multi-scale modeling of coupled biochemical networks}
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It is well-established for coupled biochemical networks that proteins' spatial organization and effective diffusion rates of their substrates are as important as substrate binding kinetics in controlling intracellular signaling.
Despite the importance of spatial coupling and diffusion, precise characterization of these factors remains a daunting task in real biological systems, given the broad ranges of spatial and temporal scales involved in signaling.
I have advanced the computational biophysics field substantially by drawing on algorithmic approaches, including homogenization theory, to link fine-grained molecular information with micron-scale models of intracellular signaling and metabolic transport.
\autocite{Metzger2014,Eun2014,Eun2013,Kekenes-Huskey2012b,Kekenes-Huskey2014a}.
Particularly exciting are our recent findings \autocite{Kekenes-Huskey2015} that for  signaling processes that exhibit oscillations such as feedback inhibition,  signal frequency and amplitude can be controlled purely by intracellular organization and diffusion rates, without chemical modification of the proteins themselves. 
This raises an intriguing possibility that cells behave like miniature signal processing units that can filter, amplify or even frequency-shift molecular signals. 
Currently we are investigating how cells can adapt signal processing characteristics through morphological changes that reposition key proteins. 


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