Drug Target Deconvolution in Wolbachia: a Chemical Proteomic Route to Discovering Novel Antibacterial Targets

淋巴丝虫病和盘尾丝虫病是热带寄生虫传染病，是全球残疾的主要原因。由于缺乏安全有效的药物，这些疾病的控制和消除受到阻碍。针对蠕虫（Wolbachia）的基本细菌共生体导致成虫死亡-这是目前使用的治疗方法的重要进步。工业和学术界的抗沃尔巴克氏体（AWOL）联盟已经开发出一种I期候选分子（泰乐菌素A（TylAMAc TM））和一种独立的临床前候选分子（AWZ 1066），它们在沃尔巴克氏体中表现出杀灭活性。AWOL还发现，夫西地酸，这是一种已经用于治疗皮肤感染的抗生素，也表现出抗沃尔巴克氏体的活性。然而，这些化合物在细菌中的具体靶点尚不清楚。靶向去卷积对于确定药物的作用机制是必要的，这可以用于进一步优化，并提供研究潜在不良反应和耐药途径的工具。在基于表型的药物发现中，可以使用各种不同的技术来鉴定蛋白质靶标。亲和层析纯化是目前研究中应用最广泛的目标去卷积技术，是化学蛋白质组学的一种。在这种方法中，化合物被连接到固体支持物上，较小的“点击化学”产生亲和标签或与光反应性基团组合的标签（图1）。光反应性基团的掺入是有益的，因为它诱导配体和靶蛋白之间的结合。这可以通过用小的光反应性基团和报告基团修饰命中来实现，这是分离所需的，或者通过使用包含两种组分的“一体化”官能团来实现。在去卷积过程中，载药亲和基质用于分离靶蛋白，通过洗涤除去非结合剂，并使用过量的活性配体洗脱命中-靶复合物，所述活性配体替代固定化分子。然后可以通过质谱法分析蛋白质-配体复合物，从而鉴定靶标。该项目将利用化学生物学技术鉴定AWZ 1066、TylAMAC TM和夫西地酸的蛋白质靶标，旨在验证这种方法用于发现新的细菌靶标和监测耐药性的工具。将设计光亲和探针分子，并通过对现有化合物（>200）数据集进行建模来优先合成，以确保使用已为这些化学型建立的路线具有良好的生物活性。一旦完成探针的优化和其对沃尔巴克氏体的活性的确认，将在与裂解物孵育后进行亲和纯化方法，以评估特异性和非特异性结合，从而确定感兴趣的蛋白质。这些富集的蛋白质将通过生物信息学补充的全自动LC-MS/MS方案进行鉴定和半定量，首次验证了Wolbachia中的这种目标鉴定方法。TylAMacTM的初始建模将针对更广泛的大环内酯类的已知细菌核糖体靶点进行，以期在靶点鉴定后使用沃尔巴克氏体模型进行基于同源性的研究。

Lymphatic filariasis and onchocerciasis are tropical parasitic worm infectious diseases that are leading causes of global disability. The control and elimination of these diseases is hampered by the lack of safe and effective drugs. Targeting an essential bacterial symbiont of the worm (Wolbachia) leads to death of the adult worms - an important advance over currently used treatments. The industrial and academic Anti-Wolbachia (AWOL) consortium has developed a Phase I candidate molecule (Tylosin A (TylAMacTM)) and an independent pre-clinical candidate (AWZ1066) that demonstrate cidal activity in Wolbachia. AWOL also discovered that fusidic acid, which is an antibiotic already used against skin infections, also demonstrates anti-Wolbachia activity. However, the specific targets of these compounds within the bacteria are unknown. Target deconvolution is necessary for determining the drug's mechanism of action, which could be utilised in further optimisation and provide tools to study potential adverse effects and resistance pathways. In phenotype-based drug discovery, a variety of different techniques can be used to identify protein targets. Affinity chromatography purification, which is a type of chemical proteomics, is known to be the most widely employed target deconvolution technique in current research. In this approach, compounds are attached to solid support, smaller 'click chemistry' generated affinity tags or tags in combination with photoreactive groups (Fig. 1). The incorporation of photoreactive groups is beneficial as it induces the binding between the ligand and target protein. This can be achieved either by modifying the hit with a small photoreactive group and a reporter group, which is required for isolation, or by using 'all-in-one' functional groups that contain both components. During the deconvolution process, drug-loaded affinity matrices are used to isolate target proteins, non-binders are removed by washing and the hit-target complex is eluted using an excess of the active ligand which replaces the immobilised molecules. The protein-ligand complex can then be analysed by mass spectroscopy allowing identification of the target. This project will utilise chemical biology techniques to identify the protein targets of AWZ1066, TylAMacTM and fusidic acid with the intention of validating this approach for the discovery of novel bacterial targets and tools to monitor resistance. Photoaffinity probe molecules will be designed and prioritised for synthesis through modelling of existing compound (>200) data sets to ensure good biological activity, using routes already established for these chemotypes. Once optimisation of the probes and confirmation of their activity against Wolbachia are completed, an affinity purification approach, following incubation with lysates will be performed in order to assess specific and non-specific binding and thus determine the proteins of interest. These enriched proteins will be identified and semi-quantified by a fully automated LC-MS/MS protocol complemented by bioinformatics, validating for the first time this target identification approach in Wolbachia. Initial modelling of TylAMacTM will be performed against the known bacterial ribosomal targets of the broader macrolide class with a view to homology based studies using a Wolbachia model post target identification.