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生物片段:一种利用生物相关片段预测蛋白质功能的方法及其在结核分枝杆菌CYP126中的应用

Biofragments: an approach towards predicting protein function using biologically related fragments and its application to Mycobacterium tuberculosis CYP126.

作者信息

Hudson Sean A, Mashalidis Ellene H, Bender Andreas, McLean Kirsty J, Munro Andrew W, Abell Chris

出版信息

Chembiochem. 2014 Mar 3;15(4):549-55. doi: 10.1002/cbic.201300697.

Abstract

We present a novel fragment-based approach that tackles some of the challenges for chemical biology of predicting protein function. The general approach, which we have termed biofragments, comprises two key stages. First, a biologically relevant fragment library (biofragment library) can be designed and constructed from known sets of substrate-like ligands for a protein class of interest. Second, the library can be screened for binding to a novel putative ligand-binding protein from the same or similar class, and the characterization of hits provides insight into the basis of ligand recognition, selectivity, and function at the substrate level. As a proof-of-concept, we applied the biofragments approach to the functionally uncharacterized Mycobacterium tuberculosis (Mtb) cytochrome P450 isoform, CYP126. This led to the development of a tailored CYP biofragment library with notable 3D characteristics and a significantly higher screening hit rate (14%) than standard drug-like fragment libraries screened previously against Mtb CYP121 and 125 (4% and 1%, respectively). Biofragment hits were identified that make both substrate-like type-I and inhibitor-like type-II interactions with CYP126. A chemical-fingerprint-based substrate model was built from the hits and used to search a virtual TB metabolome, which led to the discovery that CYP126 has a strong preference for the recognition of aromatics and substrate-like type-I binding of chlorophenol moieties within the active site near the heme. Future catalytic analyses will be focused on assessing CYP126 for potential substrate oxidative dehalogenation.

摘要

我们提出了一种基于片段的新方法,该方法解决了化学生物学中预测蛋白质功能的一些挑战。我们将这种通用方法称为生物片段,它包括两个关键阶段。首先,可以根据感兴趣的蛋白质类别的已知底物样配体集设计并构建一个生物学相关的片段库(生物片段库)。其次,可以筛选该库与来自相同或相似类别的新型推定配体结合蛋白的结合情况,对命中结果的表征为底物水平上的配体识别、选择性和功能基础提供了深入了解。作为概念验证,我们将生物片段方法应用于功能未表征的结核分枝杆菌(Mtb)细胞色素P450同工酶CYP126。这导致开发了一个具有显著三维特征的定制CYP生物片段库,其筛选命中率(14%)明显高于先前针对Mtb CYP121和125筛选的标准类药物片段库(分别为4%和1%)。已鉴定出与CYP126发生底物样I型和抑制剂样II型相互作用的生物片段命中结果。基于化学指纹的底物模型由命中结果构建而成,并用于搜索虚拟结核代谢组,结果发现CYP126对血红素附近活性位点内的芳烃识别以及氯酚部分的底物样I型结合具有强烈偏好。未来的催化分析将集中于评估CYP126的潜在底物氧化脱卤作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd0f/4159592/fef9f01f5972/cbic0015-0549-f1.jpg

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