Optimizing model comparison for enzymatic mechanism analysis

Abstract

Characterization of enzyme inhibition in drug development is usually limited to a basic analysis with the classical inhibition models or simply the use of IC50 values. However, a better understanding of enzyme physiology and regulation is seen as key to unraveling and treating the processes associated with stubborn disease targets like Alzheimer's disease. Recently it has been shown that enzyme regulation, through substrate, inhibitor or activator interactions can be modeled using the summation of binding curves. Here we examine the use of the modular equation permutations, that can be produced through binding curve summation, to fit and evaluate the interactions of abietic acid with protein tyrosine phosphatase nonreceptor type 11. This new sort of analysis will allow for improved insight into the physiological role enzymes play and the consequence their modulation may have in disease progression.