Abstract

CYP27B1, a cytochrome P450-containing hydroxylase enzyme, converts vitamin D precursor calcidiol (25-hydroxycholecalciferol) to its active form calcitriol (1α,25(OH)₂D₃). Tyrosine kinase inhibitor such as imatinib is reported to interfere with the activation of vitamin D₃ by inhibiting CYP27B1 enzyme. Consequently, there is a decrease in the serum levels of active vitamin D that in turn may increase the relapse risk among the cancer patients treated with imatinib. Within this framework, the current study focuses on identifying other possible kinase inhibitors that may affect the calcitriol level in the body by inhibiting CYP27B1. To achieve this, we explored multiple machine learning approaches including support vector machine (SVM), random forest (RF), and artificial neural network (ANN) to identify possible CYP27B1 inhibitors from a pool of kinase inhibitors database. The most reliable classification model was obtained from the SVM approach with Matthews correlation coefficient of 0.82 for the external test set. This model was further employed for the virtual screening of kinase inhibitors from the binding database (DB), which tend to interfere with the CYP27B1-mediated activation of vitamin D. This screening yielded around 4646 kinase inhibitors that were further subjected to structure-based analyses using the homology model of CYP27B1, as the 3D structure of CYP27B1 complexed with heme was not available. Overall, five kinase inhibitors including two well-known drugs, i.e., AT7867 (Compound-2) and amitriptyline N-oxide (Compound-3), were found to interact with CYP27B1 in such a way that may preclude the conversion of vitamin D to its active form and hence testify the impairment of vitamin D activation pathway.

Graphic abstract

中文翻译：

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确定排除 CYP27B1 介导的维生素 D 激活的激酶抑制剂：一种集成的机器学习和基于结构的药物设计方法

摘要

CYP27B1 是一种含有细胞色素 P450 的羟化酶，可将维生素 D 前体骨化二醇（25-羟基胆钙化醇）转化为其活性形式的骨化三醇（1α,25(OH) ₂ D ₃）。据报道，酪氨酸激酶抑制剂如伊马替尼会干扰维生素 D ₃的激活通过抑制CYP27B1酶。因此，活性维生素 D 的血清水平降低，反过来可能会增加接受伊马替尼治疗的癌症患者的复发风险。在这个框架内，目前的研究重点是确定其他可能通过抑制 CYP27B1 影响体内骨化三醇水平的激酶抑制剂。为了实现这一目标，我们探索了多种机器学习方法，包括支持向量机 (SVM)、随机森林 (RF) 和人工神经网络 (ANN)，以从激酶抑制剂数据库池中识别可能的 CYP27B1 抑制剂。最可靠的分类模型是从 SVM 方法获得的，外部测试集的 Matthews 相关系数为 0.82。该模型进一步用于从结合数据库 (DB) 中虚拟筛选激酶抑制剂，这些抑制剂往往会干扰 CYP27B1 介导的维生素 D 激活。该筛选产生了大约 4646 种激酶抑制剂，这些抑制剂进一步进行了基于结构的分析使用 CYP27B1 的同源模型，因为 CYP27B1 与血红素复合的 3D 结构不可用。总体而言，五种激酶抑制剂包括两种众所周知的药物，即 AT7867（发现化合物 2 ) 和阿米替林 N-氧化物 (化合物 3 ) 与 CYP27B1 相互作用的方式可能会阻止维生素 D 转化为其活性形式，从而证明维生素 D 激活途径受损。

图形摘要