Computational methods for structural-functional studies of proteins

蛋白质结构功能研究的计算方法

• 批准号: 8098699
• 负责人: Nick V. Grishin
• 金额: $ 30.6万
• 依托单位: UT SOUTHWESTERN MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2014-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8098699
• 关键词: Achievement; Address; Algorithms; Amino Acid Sequence; Amino Acids; Attention; Bioinformatics; Biological Process; Biomedical Research; CASP8 gene; Collaborations; Communities; Computational Biology; Computer software; Computing Methodologies; Data; Databases; Detection; Disease; Drops; Effectiveness; Employment; Enzymes; Experimental Designs; Family; Foundations; Homologous Gene; Homologous Protein; Homology Modeling; Human; Internet; Joints; Knowledge; Malignant Neoplasms; Medical; Methods; Modeling; Pattern; Peptide Sequence Determination; Phosphotransferases; Phylogenetic Analysis; Positioning Attribute; Protein Family; Proteins; PubMed; Relative (related person); Research; Research Personnel; Sequence Alignment; Sequence Analysis; Sequence Homologs; Signal Transduction; Site; Source; Structure; Surveys; Work; base; design; improved; insight; interest; novel strategies; programs; public health relevance; research study; software development; statistics; success; tool

DESCRIPTION (provided by applicant): Accurate multiple sequence alignment (MSA) is the major unsolved problem in protein bioinformatics. Alignments and similarity searches are essential first steps in experimental design for all studies involving proteins, and the accuracy of these methods is crucial for the success in biomedical research. In the course of this project, we plan to significantly improve the accuracy of alignments and the precision of sequence similarity detection between protein families. During the last few years, our group proposed 4 methods for MSA construction and 2 methods for remote homology inference. Presently, our latest program PROMALS3D is judged to be the most accurate aligner for weakly similar sequences. We also performed a comprehensive survey of kinase sequences and structures that revealed 25 homologous groups (superfamilies) in 10 structural folds. Building on these results, we propose to: 1) Improve sensitivity of sequence profile similarity search, mainly by using known relationships between database sequences. 2) Develop software for accurate MSA of sequences with low similarity. The emphasis is being made on employment of structural features and predictions to improve MSA quality. 3) Design an easy to use web server for exploration of protein families. The server could be queried with a single sequence to find, align and analyze its homologs, or with a set of sequences. The central component of the server is MSA using the software developed in this project. 4) Assemble a database of high quality MSAs for kinases and their relatives, and make testable structure-functional predictions for groups without experimental annotations. Since kinases attract considerable attention due to their medical relevance (e.g. cancer studies), this database should be a valuable asset to researchers. PUBLIC HEALTH RELEVANCE: Accurate multiple sequence alignment is the major unsolved problem in protein bioinformatics. Alignments and sequence similarity searches are essential first steps in experimental design for all studies involving proteins, and the accuracy of these methods is crucial for the success of biomedical research. We will improve alignment accuracy and using the new method will analyze kinases, which are a medically important group of enzymes attracting high interest because of their relevance to many diseases, cancer in particular.

描述（由申请人提供）：准确的多序列比对（MSA）是蛋白质生物信息学中的主要未解决问题。对于所有涉及蛋白质的研究的实验设计的一致性和相似性搜索是必不可少的第一步，这些方法的准确性对于生物医学研究的成功至关重要。在该项目的过程中，我们计划显着提高比对的准确性和蛋白质家族之间序列相似性检测的精确性。在过去的几年中，我们的小组提出了4种用于MSA构建的方法和2种远程同源性推断的方法。目前，我们的最新程序Promals3D被认为是微弱相似序列的最准确的对准器。我们还对激酶序列和结构进行了全面的调查，该调查揭示了10个结构折叠中的25个同源组（超家族）。在这些结果的基础上，我们建议：1）主要通过使用数据库序列之间的已知关系来提高序列曲线相似性搜索的灵敏度。 2）开发软件，以使其准确的MSA具有低相似性的序列。重点是使用结构特征和预测以提高MSA质量。 3）设计易于使用的Web服务器，以探索蛋白质家族。可以使用单个序列查询服务器，以查找，对齐和分析其同源物或一组序列。服务器的中心组件是使用此项目中开发的软件MSA。 4）组装一个用于激酶及其亲戚的高质量MSA数据库，并对没有实验注释的组进行可测试的结构功能预测。由于激酶由于其医学相关性引起了极大的关注（例如癌症研究），因此该数据库应该是研究人员的宝贵资产。 公共卫生相关性：准确的多个序列比对是蛋白质生物信息学中的主要未解决问题。对所有涉及蛋白质的研究的实验设计的一致性相似性搜索是必不可少的第一步，这些方法的准确性对于生物医学研究的成功至关重要。我们将提高对齐的准确性，使用新方法将分析激酶，因为它们与许多疾病有关，特别是癌症，这是一种具有医学上重要的酶，引起了人们的兴趣。