CAREER: A Database for Modeling Protein Spatial Geometry -Discovering Protein Functions

职业：蛋白质空间几何建模数据库 - 发现蛋白质功能

• 批准号: 0133856
• 负责人: Jie Liang
• 金额: $ 65.18万
• 依托单位: University of Illinois at Chicago
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-01 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0133856&HistoricalAwards=false
• 关键词: CAREER; Database; Modeling; Protein; Spatial

Many genes in bacteria, plants, fungi, worm, fruit fly, and human have no sequence matches, their three-dimensional structures are unsolved, and their functional roles are unknown. Three-dimensional spatial surface motifs of key residues can provide critical links connecting gene sequence, protein structure, and protein functions. Surface motifs with complicated geometry are difficult to compute, and the key residues are often from distant parts of the primary sequences. The proposed project aims to develop tools using computational geometry for discovery of similar protein surface patterns, as well as server databases of libraries of similar protein surfaces for biological querying and understanding. The search tools will be developed using a comprehensive informatics approach for discovery of statistically significant similarity relationship of protein surfaces, combining sequence, physicochemical, and shape information. The database of libraries of spatial surface motifs will provide organized information enriched with functional annotation.By providing quantitative, organized, and understandable information of protein surface motifs, the tools and database proposed will help to uncover new patterns of key residues in surface motifs important for understanding protein functions. It will facilitate the understanding of the cellular roles of newly sequenced genes from genomic sequencing and newly solved structures from structural genomics. It will also help to establish previously unrecognized functional and evolutionary relationship of protein spatial surfaces, and uncover deep evolutionary origins of functionally constrained structural elements before the emergence of protein domains and folds. Knowledge and insight gained from protein surface motifs will also help to design and engineer novel proteins for new biological functions and for novel industrial applications.The educational component of this proposal will be centered on (1) course and curriculum development, (2) student mentoring, and (3) outreach. In addition to curriculum development for the newly approved MS/PHD programs in bioinformatics, a new course named "Geometric Computing for Bioinformatics" will be developed, which will be tightly linked to the research through classroom teaching and class projects designed based on the research activities. The involvement of graduate and undergraduate students, as well as postdoctoral researchers provide mentoring opportunities, with the goal to pass the knowledge, the computational skill, and the ability of critical and creative thinking to the students. It will also allow the students to present their research in national and international conferences. The outreach activities to Chicago high school and junior colleges will be focused on high school summer camp activities of bioinformatics research, local visits, hosting interns in the PI's lab, school teacher preparation, and developing career as well as educational material on bioinformatics (CD-ROM and website) to attract students not traditionally represented in this field.

细菌、植物、真菌、蠕虫、果蝇和人类中的许多基因没有序列匹配，它们的三维结构尚未解决，它们的功能作用也未知。 关键残基的三维空间表面模体可以提供连接基因序列、蛋白质结构和蛋白质功能的关键环节。 具有复杂几何形状的表面模体很难计算，并且关键残基通常来自一级序列的遥远部分。 拟议的项目旨在开发工具，使用计算几何发现相似的蛋白质表面模式，以及服务器数据库的图书馆相似的蛋白质表面的生物查询和理解。搜索工具将使用综合信息学方法开发，用于发现蛋白质表面的统计学显著相似性关系，结合序列，物理化学和形状信息。 空间表面基序库将提供丰富的功能注释信息，通过提供定量的、有组织的和可理解的蛋白质表面基序信息，所提出的工具和数据库将有助于揭示对理解蛋白质功能重要的表面基序中的关键残基的新模式。它将促进对来自基因组测序的新测序基因和来自结构基因组学的新解决的结构的细胞作用的理解。 这也将有助于建立以前未被认识的蛋白质空间表面的功能和进化关系，并揭示蛋白质结构域和折叠出现之前功能受限的结构元件的深层进化起源。 从蛋白质表面基序中获得的知识和见解也将有助于设计和工程化新的蛋白质，以实现新的生物功能和新的工业应用。本提案的教育部分将集中在（1）课程和课程开发，（2）学生指导和（3）推广。 除了新批准的生物信息学硕士/博士课程的课程开发外，还将开发一门名为“生物信息学的几何计算”的新课程，该课程将通过课堂教学和基于研究活动设计的课堂项目与研究紧密联系。 研究生和本科生以及博士后研究人员的参与提供了指导机会，其目标是将知识，计算技能以及批判性和创造性思维的能力传递给学生。 它还将允许学生在国家和国际会议上展示他们的研究。 对芝加哥高中和大专院校的推广活动将侧重于生物信息学研究的高中夏令营活动、当地访问、在PI实验室接待实习生、学校教师准备、发展职业以及生物信息学教育材料（光盘和网站），以吸引传统上不在该领域的学生。