Pharmacophore and quantitative structure activity relationship modelling of UDP-glucuronosyltransferase 1A1 (UGT1A1) substrates
Pharmacophore and quantitative structure activity relationship modelling of UDP-glucuronosyltransferase 1A1 (UGT1A1) substrates
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DOI：
10.1097/00008571-200211000-00008
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发表时间：
2002-11-01
期刊：
影响因子：
--
通讯作者：
Miners, JO
中科院分区：
文献类型：
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作者：
Sorich, MJ;Smith, PA;Miners, JO
UDP-葡萄糖醛酸基转移酶1AL(UGT1A1)是一种多态酶，负责结构不同的药物、非药物外源化合物和内源性化合物(如胆红素)的葡萄糖醛酸化反应。因此，UGT1A1底物和抑制剂选择性和结合亲和力的定义对于鉴定其消除可能在不同基因型的受试者中受到损害的化合物，以及预测涉及外源物质的潜在抑制相互作用以及由UGT1A1代谢的内源化合物具有重要意义。我们报道了23种具有不同结构和结合亲和力的已知UGT1A1底物的二维和三维(2D和3D)定量结构活性关系(QSAR)和药效团模型的生成。首先，开发了一种简单的方法来确定这些化合物的表观抑制常数(K-I，K-APP)。18个底物随后用于构建模型，其余5个用于验证模型的预测能力。构建了三种不同的模型：(I)能够根据底物与3D特征的排列相适应的程度来预测K-I，K-APP的三特征药效团模型(r(2)=0.87，在对数单元内预测的所有五个测试底物的K-I，K-APP)；(Ii)使用‘共同特征’药效团来对齐底物的3D-QSAR(r(2)=0.71，K-I，K-APP)；(3)由6个化学描述符构成的2D-QSAR(r(2)=0.92，在一个对数单元内预测所有5个测试底物的K-I、K-APP)。药效团的共同特征证明了两个疏水结构域的重要性，这两个疏水结构域分别与葡萄糖醛酸化作用部位隔开4埃和7埃。这些模型代表了UGT亚型的第一个广义预测模型，它们相辅相成，是迈向基于计算机(电子计算机)的UGT1A1模型用于高通量新陈代谢预测的重要第一步。
UDP-glucuronosyltransferase 1Al (UGT1A1) is a polymorphic enzyme responsible for the glucuronidation of structurally diverse drugs, non-drug xenobiotics and endogenous compounds (e.g. billrubin). Thus, definition of UGT1A1 substrate and inhibitor selectivities and binding affinities assumes importance for the identification of compounds whose elimination may be impaired in subjects with variant genotypes, and for the prediction of potentially inhibitory interactions involving xenobiotics; and endogenous compounds metabolized by UGT1A1. We report the generation of two- and three-dimensional (2D and 3D) quantitative structure activity relationships (QSAR) and pharmacophore models for 23 known UGT1A1 substrates with diverse structure and binding affinity. Initially, a simple procedure was developed to determine apparent inhibition constants (K-i,K-app) for these compounds. Eighteen substrates were subsequently used to construct models and the remaining five to validate the predictive ability of the models. Three different models were constructed: (i) three feature pharmacophore model able to predict the K-i,K-app on the basis of the degree to which a substrate can fit to the arrangement of 3D features (r(2) = 0.87, K-i,K-app for all five test substrates predicted within log unit); (ii) 3D-QSAR using a 'common features' pharmacophore to align the substrates (r(2) = 0.71, K-i,K-app for four out of five test substrates predicted within one log unit); (iii) 2D-QSAR constructed with six chemical descriptors (r(2) = 0.92, K-i,K-app of all five test substrates predicted within one log unit). The common features pharmacophore demonstrated the importance of two hydrophobic domains separated from the glucuronidation site by 4 Angstrom and 7 Angstrom, respectively. These models, which represent the first generalized predictive models for a UGT isoform, complement each other and are an important first step towards computer based (in silico) models of UGT1A1 for high throughput prediction of metabolism.