Organic and Bioorganic Chemistry, Department of Chemistry, Bielefeld University, Universitätsstrasse 25, 33501, Bielefeld, Germany.
Leibniz Institute for Plant Biochemistry (IPB), Weinberg 3, 06120, Halle, Germany.
Chembiochem. 2020 Nov 16;21(22):3282-3288. doi: 10.1002/cbic.202000444. Epub 2020 Aug 4.
The recently described flavin-dependent halogenase BrvH is able to catalyse both the bromination and chlorination of indole, but shows significantly higher bromination activity. BrvH was annotated as a tryptophan halogenase, but does not accept tryptophan as a substrate. Its native substrate remains unknown. A predictive model with the data available for BrvH was analysed. A training set of compounds tested in vitro was docked into the active site of a complete protein model based on the X-ray structure of BrvH. The atoms not resolved experimentally were modelled by using molecular mechanics force fields to obtain this protein model. Furthermore, docking poses for the substrates and known non-substrates have been calculated. Parameters like distance, partial charge and hybridization state were analysed to derive rules for predicting activity. With this model for activity of the BrvH, a virtual screening suggested several structures for potential substrates. Some of the compounds preselected in this way were tested in vitro, and several could be verified as convertible substrates. Based on information on halogenated natural products, a new dataset was created to specifically search for natural products as substrates/products, and virtual screening in this database yielded further hits.
最近描述的黄素依赖型卤化酶 BrvH 能够催化吲哚的溴化和氯化，但溴化活性显著更高。BrvH 被注释为色氨酸卤化酶，但不接受色氨酸作为底物。其天然底物仍不清楚。分析了具有 BrvH 可用数据的预测模型。基于 BrvH 的 X 射线结构，将在体外测试的化合物的训练集对接到完整蛋白质模型的活性位点中。通过使用分子力学力场对实验中未解析的原子进行建模，以获得该蛋白质模型。此外，还计算了底物和已知非底物的对接构象。分析了距离、部分电荷和杂化状态等参数，以得出预测活性的规则。利用该 BrvH 活性模型，虚拟筛选建议了几种潜在底物的结构。以这种方式预选的一些化合物在体外进行了测试，其中一些可被验证为可转化的底物。基于卤化天然产物的信息，创建了一个新的数据集，专门搜索作为底物/产物的天然产物，并在该数据库中进行虚拟筛选得到了进一步的命中结果。
