Developing Computational Methods to Aid Infectious Disease Therapeutics Through Analysis of Protein Function Evolution

最近由人类基因组计划发起的高通量DNA测序革命，导致了关于各种生物体的大量数据收集。这特别包括引起传染病的寄生虫、细菌和病毒病原体，以及负责疾病传播的有机体。这些数据的出现为理解这些致病因子和开发新的治疗方法提供了新的令人兴奋的机会。一个突出的和具有挑战性的问题是理解这些基因组编码的蛋白质的功能。时间和资源限制了可以通过实验确定其功能的数量；因此，预测功能的方法至关重要。此外，由于宿主和致病因子之间的复杂关系，在应用于传染病时需要新的方法。这些关联对评估哪些药物适合用于治疗传染病和开发新的治疗方法也有影响。了解复杂的生化关系将有助于确定传染病的新药物靶标，需要汇集一系列不同的生物学信息。实现这一目标的最好方法是使用结合生物学、化学和计算机科学技术的多学科方法。与伦敦卫生和热带医学院、欧洲生物信息学研究所和伦敦大学学院的同事合作，我将开发一种独特的计算资源，专门用于处理与传染病相关的基因组：-将蛋白质序列及其分子结构之间的关系聚集在一起，将它们置于进化背景中，并建立这些蛋白质功能之间的相似性度量。-使用捕获的数据来开发一种新的方法，通过对相关蛋白质之间发生功能变化的情况进行系统分析并确定这种变化的特征来定义规则来预测蛋白质的功能。从项目开始，开发的方法将应用于传染病研究中的具体问题，并与实验小组合作验证预测。我将首先讨论查加斯病新药治疗中涉及的关键酶，查加斯病是美洲最重要的寄生虫感染，目的是更好地了解耐药性机制。将对锥虫和利什曼原虫基因组进行预测和功能注释，它们分别是昏睡病/恰加斯病和利什曼病的病原体，以测试这些方法，并深入了解它们如何能够很好地促进这些基因组的注释。从应用和验证过程中获得的见解将被用来进一步加强所开发的方法，最终使它们能够用于任何传染病病原体。开发的资源和方法还将用于确定新的药物靶点，以及药物与可能导致患者副作用的其他蛋白质之间可能发生的意外相互作用。立即应用将寻求增加针对血吸虫的高通量药物筛查结果的价值。这种吸虫引起世界第二大社会经济破坏性寄生虫病(由世界卫生组织强调)。其目的将是确定药物(S)可能针对的是哪种蛋白质(S)，并确定在人类宿主中是否存在潜在的不利相互作用。这项研究最终将在临床环境中使用，真正有可能帮助抗击数百万人遭受的各种传染病。

The recent revolution in high throughput DNA sequencing, started by the Human Genome Project, has led to large collections of data on a diverse set of organisms. This notably includes the parasitic, bacterial and viral agents that cause infectious diseases, as well as the organisms that are responsible for disease transmission. The emergence of this data offers new and exciting opportunities to understand these disease-causing agents and to develop novel therapeutics.An outstanding and challenging problem is to understand the functions of the proteins encoded by these genomes. Time and resources limit the number whose function can be experimentally determined; therefore methods for predicting function are of paramount importance. Moreover, new methods are required when applied to infectious diseases due to the complex relationships between the host organism and the disease causing agent. These associations also have implications for assessing which drugs are suitable for use against infectious diseases and for the development of new therapeutics.An understanding of the complex biochemical relationships that will facilitate the identifying of new drug targets for infectious diseases requires bringing together a range of diverse biological information. The best method for achieving this is using a multidisciplinary approach interfacing biology, chemistry and computer science techniques. In collaboration with colleagues at the London School of Hygiene and Tropical Medicine, the European Bioinformatics Institute and University College London, I will develop a unique computational resource specifically to handle genomes associated with infectious diseases that:- brings together relationships between protein sequences and their molecular structures, putting them into an evolutionary context as well as establishing measures of similarity between the functions of these proteins.- uses the data captured to develop a new method to predict the function of proteins by defining rules bases on the systematic analysis of cases where changes in function occur between related proteins and determining the features of that change.From the outset of the project, the methods developed will be applied to specific problems in infectious disease research, combined with validating predictions in collaboration with experimental groups. I will start by addressing the key enzymes involved in new drug treatments for Chagas disease, the most important parasitic infection in the Americas, with the aim of providing a better understanding of drug-resistance mechanisms. Predictions and functional annotations of the Trypanosoma and Leishmania genomes, the causative agents of sleeping sickness/Chagas disease and Leishmaniasis respectively, will be made to test the methods and to gain insight into how well they can contribute to enhancing the annotations of these genomes. Insights gained from the application and validation process will be used to further enhance the methods developed, ultimately enabling them to be used on any infectious disease agent. The resource and methods developed will also be used to identify new drug targets and possible unintended interactions between the drug and other proteins that may result in side effects in patients. An immediate application will seek to add value to the results of high-throughput drug screens against schistosomes. This trematode worm causes the world's second most socio-economically devastating parasitic disease (highlighted by he World Health Organization). The aim will be to identify which protein(s) the drug(s) might be targeting, and to determine if there is potential for adverse interaction in the human host. The research will eventually be of use in a clinical setting, with the real possibility of helping fight the huge variety of infectious diseases suffered by millions.