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 model’s 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.