基于生物信息学方法的副猪嗜血杆菌靶标及先导发现

Haemophilus parasuis (H.parasuis) infections have become worldwide and produce big losses in swine populations. Because of a lack of effective prevention and treatments at present, there is a strong incentive to develop new bactericides against H.parasuis. The project will screen new potential targets by reconstructing metabolic network of H.parasuis SH0165 strains. Approximately one to two candidate targets are expected to be identified by the further assessment of target drugability. Simultaneously, a "self-built bactericides database" will be built by SVM. Virtual screening based on the candidate targets will also be carried out by using the "self-built bactericide databases". Subsequently, the bactericidal activities of the hits will be detected. Consequently, our research is expected to develop two to tree new bactericides, helping the control of H.parasuis infections. The successful implementation of the project will simulate the development of bactericides with independent intellectual property rights, which is of major significance and potential applications.

副猪嗜血杆菌（Heamophilus parasuis, HPS）病是全球范围内影响养猪业的一种严重细菌性疾病，给养猪业带来严重经济损失。在目前尚缺乏有效的预防和治疗方法的现状下，本项目拟以全基因组测序的副猪嗜血杆菌SH0165株为研究对象，通过构建副猪嗜血杆菌的代谢网络草图，利用网络拓扑结构和流量平衡分析筛选潜在靶标；进一步开展基于代谢物浓度和基于抑菌实验的靶标成药性评价，确定1-2种候选靶标；采用SVM方法建立杀菌剂分类预测模型，构建"类杀菌剂"被筛化合物数据库。然后针对候选靶标，对"类杀菌剂"库进行虚拟筛选。最后对筛选到的化合物开展杀菌活性评价。本研究的顺利实施，有望获得2-3种具有进一步开发价值的新型杀菌剂，为有效控制副猪嗜血杆菌病害，开发具有自主知识产权的新型作用机制的杀菌剂奠定基础。因此，本研究具有较为重要的研究意义和潜在的应用价值。

本项目通过代谢网络的构建，寻找H.parasuis SH0165 中潜在的作用靶标；同时采用课题前期建立的预测细菌代谢物浓度的支持向量回归（SVR）模型，对潜在靶标的底物浓度进行预测，确定H.parasuis SH0165菌株的细胞内催化酶GlmU（N-Acetylglucosamine-1-phosphate uridyltransferase）（EC 2.3.1.157）是一个很有发展潜力的杀菌剂靶标，可用于新型杀菌剂的筛选研究。采用SVM 方法建立杀菌剂分类预测模型，构建"类杀菌剂"被筛化合物数据库，接着对潜在靶标的三维结构进行同源模建，并针对靶标对"类杀菌剂"库进行虚拟筛选，选出16个化合物进行购买用于下一步的活性测试研究。发现三个化合物有较好的抑菌活性，这将对于发现新型杀菌剂具有较好的指导作用。