Structure-based functional annotation of microbial genomes

摘要 鉴于最近测序的基因组数量的爆炸性增长以及功能信息的相对缺乏 在它们的内容上，注释不同基因组中所有蛋白质的生物学功能代表了一个主要的 对现代分子和计算生物学的挑战。基因组注释的问题尤其是 对细菌来说是急性的；广泛的共生和致病细菌物种影响人类健康，并且只有 计算方法，当适当地与仔细定位的生化实验相结合时，可以 提供了解其生理所需的可靠、高通量注释。海流 计算功能预测的方法主要是基于从已知的相似蛋白质转移 然而，当同源性水平较低时，该序列变得越来越不可靠。最近，意义重大 全社会范围的盲法测试证明，蛋白质三维结构预测已取得进展 实验和目前最先进的方法可以为大多数基因组构建正确的蛋白质折叠 不使用紧密同源模板的序列。建立在生物功能更多的假设之上 这项提议直接与3D结构相关，而不是序列，旨在启动从蛋白质到蛋白质的范式转变 基于结构的函数注释的结构预测。结合计算生物学的专业知识， 微生物学和结构生物学，PI将系统地检查潜力和范围如何 来自尖端建模方法的计算结构模型可以帮助提供可靠的高吞吐量 细菌基因组的注释，特别关注那些不能通过 现有的基于序列同源性的方法。 该项目旨在开发和测试几种用于蛋白质功能预测的尖端方法 来自结构预测的低分辨率(但正确折叠)模型。具体目标包括 发展新的基于结构的方法来模拟蛋白质-配体结合位点，以及酶和 基因本体论。建模方法和结果将通过一系列精心设计的实验进行检验， 包括高通量化学筛选和详细的基于结构生物学的表征。完全没有 阶段，将在实验和改进之间建立迭代的预测-实验-改进循环 用计算注解来指导功能建模方法的发展和进步。的研究 这个项目将集中在大肠杆菌K12菌株上，对于这种菌株，10%的基因组仍然没有注释，尽管 作为模式生物的使用历史悠久；但长期目标是建立一个新的和强大的框架 它可以作为其他各种微生物基因组可靠的功能注释的资源。相比较 在目前基于序列的方法下，基于结构的管道的成功可能会将 当前基因组数据库中近1000万(或30%)的非同源或远端同源靶点进入 可靠的函数注释机制。

Abstract Given the recent explosion in the number of sequenced genomes and the relative lack of functional information on their contents, annotating the biological functions of all proteins across different genomes represents a major challenge to modern molecular and computational biology. The problem of genome annotation is particularly acute for bacteria; a vast range of commensal and pathogenic bacterial species impact human health, and only computational approaches, when appropriately combined with carefully targeted biochemical experiments, can provide the reliable, high-throughput annotations necessary to understand their physiology. The current approach to computational function prediction is mainly based on transfer from known proteins of similar sequence, which however becomes increasingly unreliable when the homology level is low. Recently, significant progress has been achieved in protein 3D structure prediction as witnessed by the community-wide blind testing experiments, and current state of the art methods can construct correct protein folds for the majority of genome sequences without using close homologous templates. Building on the hypothesis that biological function is more directly associated with 3D structure than sequence, this proposal aims to initiate a paradigm shift from protein structure prediction to structure-based function annotations. Combining expertise from computational biology, microbiology, and structural biology, the PIs will systemically examine the potential and scope of how computational structure models from cutting-edge modeling methods can help provide reliable high-throughput annotations of bacterial genomes, with a particular focus on the difficult targets that cannot be addressed by the existing sequence homology-based approaches. This project is designed to develop and test several cutting-edge approaches for protein function prediction using low-resolution (but correctly folded) models from the structure predictions. The specific aims include the development of novel structure-based methods for modeling of the protein-ligand binding sites, and enzyme and gene ontologies. The modeling methods and results will be tested by a set of carefully designed experiments, including high-throughput chemical screening and detailed structural-biology based characterizations. At all stages, iterative prediction-to-experiment-to-refinement loops will be established between the experiments and computational annotations to guide the functional modeling method development and advances. The studies of this project will be focused on E. coli K12 strain, for which >10% of the genome remains un-annotated despite a long history of use as a model organism; but the long-term goal is to build up a novel and robust framework which can be used as a resource for reliable function annotations for various other microbial genomes. Compared with current sequence-based approaches, the success of the structure-based pipelines could potentially convert nearly 10 million (or 30%) of the non- or distant-homologous targets in the current genome database into the reliable function annotation regime.