Analysis of the steady-state relations and control-algorithm characterisation in a mathematical model of cholesterol biosynthesis
Elevated levels of cholesterol are known to be a risk factor for cardiovascular diseases. As a result, several treatment strategies and drugs have been developed to control these elevated cholesterol levels, but they are not always successful. Statins are now the most widely used cholesterol-lowering drugs; however, not all the mechanisms of their action are understood and this can sometimes lead to adverse effects. A dynamic mathematical model of the cholesterol biosynthesis network was developed with aim to understand the key mechanisms of cholesterol biosynthesis. In this article we show that in spite of a serious lack of experimental data, the model can be used to study the concepts of possible mechanisms of cholesterol biosynthesis and drug interactions. If only steady-state data is used for the models identification, the model can predict the steady-state relations after perturbation correctly, while the dynamical properties are not necessarily related to the real system. The control mechanism for the cholesterol levels through the SREBF-2 transcription factor was identified as the PI control algorithm. The comparison of model simulations and performed biological experiments indicated that the substances LK-980 and Atorvastatin most likely trigger the same indirect mechanism of cholesterol biosynthesis control, although they interact with the network in different ways.
cholesterol biosynthesis model biological feedback mechanisms systems biology functional genomics