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.

中文翻译：

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酶机理分析的优化模型比较

药物开发中酶抑制的表征通常仅限于使用经典抑制模型进行的基本分析或仅使用IC50值进行。但是，对酶生理学和调控的更好理解被认为是阐明和治疗与顽固性疾病目标（例如阿尔茨海默氏病）相关的过程的关键。最近已经显示，可以使用结合曲线的总和来模拟通过底物，抑制剂或活化剂相互作用进行的酶调节。在这里，我们研究了可通过结合曲线求和产生的模块化方程置换的使用，以拟合和评估松香酸与11型蛋白质酪氨酸磷酸酶非受体的相互作用。