Comparative genomics of protein structure and function

蛋白质结构和功能的比较基因组学

• 批准号: 8331586
• 负责人: OLIVIER LICHTARGE
• 金额: $ 39.09万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-04-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8331586
• 关键词: Algorithms; Amino Acids; Bacteria; Bacterial Drug Resistance; Belief; Benchmarking; Binding; Biological; Biological Assay; Biological Process; Biology; Catalysis; Chloroquine resistance; Computing Methodologies; Data; Development; Diffuse; Diffusion; Disease; Drug Design; Drug resistance; Drug resistance pathway; Escherichia coli; Escherichia coli Proteins; Future; Genes; Genomics; Goals; Graph; Internet; Learning; Link; Malaria; Measures; Mediating; Medical; Methods; Molecular; Molecular Conformation; Mutation; Network-based; Pathologic Processes; Pharmaceutical Preparations; Plasmodium falciparum; Protein Engineering; Protein Structure Initiative; Proteins; Proteome; Protocols documentation; Reagent; Relative (related person); SOS Response; Scheme; Sensitivity and Specificity; Sequence Analysis; Sequence Homology; Site; Solutions; Son of Sevenless Proteins; Source; Specificity; Staging; Structure; Testing; Therapeutic; Three-dimensional analysis; Variant; Work; base; comparative; comparative genomics; computer based statistical methods; cost; design; engineering design; falls; improved; interest; novel; pathogen; protein function; protein structure; protein structure function; research study; structural genomics; theories; tool

DESCRIPTION (provided by applicant): This work aims to identify protein functional determinants and to compare them across the proteome to predict protein function. The approach is predicated on a phylogenomic algorithm, the Evolutionary Trace (ET), that identifies key functional residues in proteins; and on ET Annotation (ETA) algorithms, which extract from ET analysis 3D templates, describing the composition and conformation of key residues involved in binding or in catalysis, and then search in other structures for geometric matches to these 3D templates that suggest a common function. Preliminary data have extensively validated ET, both computationally and through experiments, and ETA has become a useful tool to annotate function on structural genomics proteins. Both methods, however, can still gain in sensitivity, specificity and scalability. To do so we propose in Aim 1, first, to improve the ET identification of key functional residues, by optimizing the selection of the input sequences and by a new measure of residue functional importance, and, second, to refine the selection of 3D templates. In Aim 2, we propose a new network-based annotation diffusion method to compare all 3D template matches at once and to add in functional information from other sources, such as from proteins without known structure. Aim 3 is experimental and it will test our predictions through mutations and assays on proteins of direct medical interest including one that controls drug resistance in bacteria and another that is a marker of drug resistance in malaria. In the long term, these results should help to focus protein engineering and drug design to the most functionally and therapeutically relevant parts of a protein, and, most broadly, link the massive and exponentially growing amounts of raw sequence and structure data to biological function and its molecular basis.

描述（由申请人提供）：这项工作的目的是确定蛋白质功能决定因素，并在蛋白质组中比较它们，以预测蛋白质功能。该方法是基于一种可识别蛋白质中关键功能残基的进化轨迹（ET）基因组算法;以及ET注释（ETA）算法，该算法从ET分析3D模板中提取，描述参与结合或催化的关键残基的组成和构象，然后在其他结构中搜索与这些3D模板的几何匹配，这些模板表明共同的功能。初步的数据已经在计算和实验上广泛验证了ET，并且ETA已经成为注释结构基因组蛋白质功能的有用工具。然而，这两种方法仍然可以获得灵敏度，特异性和可扩展性。为此，我们在目标1中提出，首先，通过优化输入序列的选择和残基功能重要性的新度量来改进关键功能残基的ET鉴定，其次，改进3D模板的选择。在目标2中，我们提出了一种新的基于网络的注释扩散方法，可以一次比较所有3D模板匹配，并添加来自其他来源的功能信息，例如来自未知结构的蛋白质。目标3是实验性的，它将通过对直接医学感兴趣的蛋白质的突变和测定来测试我们的预测，其中包括控制细菌耐药性的蛋白质和疟疾耐药性标志物。从长远来看，这些结果应该有助于将蛋白质工程和药物设计集中在蛋白质的功能和治疗相关部分，并且最广泛地将大量和指数增长的原始序列和结构数据与生物功能及其分子基础联系起来。