Jung Jihoon, Kim Nam Doo, Kim Su Yeon, Choi Inhee, Cho Kwang-Hwi, Oh Won Seok, Kim Doo Nam, No Kyoung Tai
Department of Biotechnology, Yonsei University, 120-749, Seoul, Korea.
J Chem Inf Model. 2008 May;48(5):1074-80. doi: 10.1021/ci800001m. Epub 2008 Apr 16.
A kinetic, reactivity-binding model has been proposed to predict the regioselectivity of substrates meditated by the CYP1A2 enzyme, which is responsible for the metabolism of planar-conjugated compounds such as caffeine. This model consists of a docking simulation for binding energy and a semiempirical molecular orbital calculation for activation energy. Possible binding modes of CYP1A2 substrates were first examined using automated docking based on the crystal structure of CYP1A2, and binding energy was calculated. Then, activation energies for CYP1A2-mediated metabolism reactions were calculated using the semiempirical molecular orbital calculation, AM1. Finally, the metabolic probability obtained from two energy terms, binding and activation energies, was used for predicting the most probable metabolic site. This model predicted 8 out of 12 substrates accurately as the primary preferred site among all possible metabolic sites, and the other four substrates were predicted into the secondary preferred site. This method can be applied for qualitative prediction of drug metabolism mediated by CYP1A2 and other CYP450 family enzymes, helping to develop drugs efficiently.
已提出一种动力学反应性结合模型来预测由CYP1A2酶介导的底物的区域选择性,该酶负责咖啡因等平面共轭化合物的代谢。该模型包括用于结合能的对接模拟和用于活化能的半经验分子轨道计算。首先基于CYP1A2的晶体结构使用自动对接检查CYP1A2底物的可能结合模式,并计算结合能。然后,使用半经验分子轨道计算AM1计算CYP1A2介导的代谢反应的活化能。最后,从结合能和活化能这两个能量项获得的代谢概率用于预测最可能的代谢位点。该模型准确地预测了12种底物中的8种是所有可能代谢位点中的主要首选位点,另外4种底物被预测为次要首选位点。该方法可用于定性预测由CYP1A2和其他CYP450家族酶介导的药物代谢,有助于高效开发药物。