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Calmodulin (CaM) is a calcium-binding protein in eukaryotes that controls various calcium-regulated cellular processes. It has four calcium-binding sites that bind calcium to form the calcium-calmodulin ( Ca2+-CaM) complex. GPCR stimulation increases the calcium levels in the cells that bind to CaM and induces a conformational change.
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A control engineering model of calcium regulation.

Christopher R Christie1, Luke E K Achenie, Babatunde A Ogunnaike

  • 1Department of Chemical Engineering (C.R.C., L.E.K.A.), Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24060; and Department of Chemical Engineering (B.A.O.), University of Delaware, Newark, Delaware 19716.

The Journal of Clinical Endocrinology and Metabolism
|April 16, 2014
PubMed
Summary

A new control engineering model explains calcium (Ca) regulation and pathologies. This validated computational model accurately predicts clinical responses and aids understanding of Ca disorders.

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Area of Science:

  • Physiology
  • Biomedical Engineering
  • Systems Biology

Background:

  • A control engineering approach offers an efficient framework for detailing the mechanistic aspects of calcium (Ca) regulation.
  • This model aids in testing hypotheses regarding the origins of Ca-related pathologies.

Purpose of the Study:

  • To develop a comprehensive computational model for quantitatively understanding plasma Ca regulation in both normal and pathological states.
  • To enable a deeper mechanistic insight into Ca homeostasis.

Main Methods:

  • Calcium regulation modeled as an engineering control system, mapping physiological subprocesses to control components (sensor, controller, actuator, process).
  • Underlying mechanisms represented using differential equations.
  • Model validated against clinical data from induced hypo- and hypercalcemia in healthy subjects.

Main Results:

  • The model accurately predicts clinical responses to induced hypo- and hypercalcemia.
  • It represents Ca pathologies as defects in control system components, explaining conditions like hyperparathyroidism.
  • Facilitates hypothesis testing for Ca regulatory mechanisms.

Conclusions:

  • The control engineering framework efficiently organizes Ca regulatory subprocesses, enhancing fundamental understanding.
  • The validated model aligns with observed clinical dynamics in healthy and diseased states.
  • Enables simulation of novel clinical tests and prediction of currently unmeasurable physiological variables.