Chemical Signatures for the Discovery of Protein Function

用于发现蛋白质功能的化学特征

• 批准号: 1305655
• 负责人: Mary Jo Ondrechen
• 金额: $ 31.3万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-01 至 2018-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1305655&HistoricalAwards=false
• 关键词: Chemical; Signatures; Discovery; Protein; Function

With this award the Chemistry of Life Processes Program in the Chemistry Division supports Drs. Mary Jo Ondrechen and Penny J. Beuning from Northeastern University to develop, implement, and verify a novel method for predicting the biochemical function of proteins. This project utilizes computational chemistry tools in an innovative chemical-properties-based method to discover the biochemical function of protein structures. It begins with the premise that local structural features at the active site constitute better predictors of biochemical function than does the overall fold. First it is shown that sets of structurally similar proteins may be sorted into subgroups according to biochemical function, using the active site residues predicted from computed chemical properties, structurally aligning them, and scoring them according to chemical similarity. Thus for each functional subgroup, a characteristic chemical signature are defined. Next, structural genomics proteins are analyzed and annotated, using their calculated chemical signatures and seeking matches with the chemical signatures of the previously characterized proteins, and misannotated structural genomics proteins are identified. For selected cases of structural genomics proteins that have been determined to be misannotated, or for which biochemical function is newly predicted, the predicted functions are verified experimentally by kinetics assays and binding studies. Genome sequencing and structural genomics efforts over the past 15 years have provided a wealth of new information about thousands of proteins. While genome research holds tremendous promise for major future benefits to society, a key step toward the realization of this potential is the ability to determine the function of the thousands of protein structures whose biochemical functions are currently unknown or uncertain; this project addresses that current challenge. Greater understanding of protein function has many potential benefits in fields outside of chemistry, including agriculture, biotechnology, medicine, biofuels, and "green" industrial processes. A better understanding of the local structural, electrostatic, and chemical patterns that govern how proteins work so selectively and efficiently will open the door to novel commercial applications. Such basic knowledge to drive novel high-tech commercial application is important to the future growth of our regional and national economies. This project also will develop a knowledge base and tools that will enable other discoveries and applications. In this project a racially diverse group of both undergraduate and doctoral students are trained in methods of computational chemistry, computational biology, and biochemistry. Experience in these areas is a vital ingredient for United States competitiveness in the global economy. Individuals with such knowledge and training are in high demand in both academia and industry.

有了这个奖项，化学部的生命过程化学项目支持东北大学的玛丽乔·昂德雷琴博士和彭妮·J·博宁博士开发、实施和验证一种预测蛋白质生化功能的新方法。 该项目利用计算化学工具，以创新的化学性质为基础的方法来发现蛋白质结构的生化功能。 它始于这样的前提，即活性位点的局部结构特征比整体折叠更能预测生物化学功能。 首先，它示出了结构相似的蛋白质组可以根据生化功能分类成亚组，使用从计算的化学性质预测的活性位点残基，结构上对齐它们，并根据化学相似性对它们进行评分。 因此，对于每个功能亚组，定义了特征化学签名。 接下来，使用其计算的化学特征并寻求与先前表征的蛋白质的化学特征的匹配来分析和注释结构基因组学蛋白质，并且鉴定错误注释的结构基因组学蛋白质。 对于选定的情况下，结构基因组蛋白质已被确定为被错误注释，或生化功能是新的预测，预测的功能进行验证实验动力学分析和结合研究。基因组测序和结构基因组学在过去15年的努力提供了丰富的新信息，数以千计的蛋白质。 虽然基因组研究对未来社会的重大利益有着巨大的希望，但实现这一潜力的关键一步是能够确定数千种蛋白质结构的功能，这些蛋白质结构的生化功能目前尚不清楚或不确定;该项目解决了当前的挑战。 对蛋白质功能的更深入了解在化学以外的领域有许多潜在的好处，包括农业、生物技术、医学、生物燃料和“绿色”工业过程。 更好地了解局部结构，静电和化学模式，这些模式决定了蛋白质如何选择性和有效地工作，这将为新的商业应用打开大门。 这些基础知识，以推动新的高科技商业应用是重要的，我们的区域和国家经济的未来增长。 该项目还将开发一个知识库和工具，使其他发现和应用成为可能。 在这个项目中，一个种族多样化的本科生和博士生群体接受计算化学，计算生物学和生物化学方法的培训。 这些领域的经验是美国在全球经济中竞争力的一个重要因素。 学术界和工业界都非常需要具有这种知识和培训的个人。