CAREER: Analysis of the Coiled-coil Interactome

该项目的研究目标是使用计算方法将蛋白质-蛋白质相互作用的分子特性与其在基因组中更广泛的生物学作用联系起来。该项目旨在证明对蛋白质相互作用基序的结构理解可以有助于解释蛋白质-蛋白质相互作用的高通量研究，并可以导致关于蛋白质关联和功能的特定和可测试的假设。该作品以一个常见且重要的交互主题——螺旋线圈为例，测试了这一想法。具体的研究目标是：(1)建立包含大量基因组中螺旋盘状序列的数据库，并包含螺旋盘状序列的性质、蛋白质的功能和其他注释；(2)将这些数据与结构考虑相结合，以验证高通量蛋白质-蛋白质相互作用研究，并预测卷曲线圈介导的相互作用；(3)通过实验验证线圈介导的相互作用预测具有重要的生物学作用。更广泛的影响：基廷博士在麻省理工学院的研究和教学是在计算和系统生物学的新兴领域进行的。这些领域将在未来几十年对科学和社会产生巨大的影响。人类基因组的测序，以及重要病原体、作物和科学模式生物的测序，为结合生物学、计算机科学、数学、工程学和其他定量领域的全新研究提供了机会。这种跨学科的方法有望加深对生物学的理解，并在生物技术和分子治疗方面取得突破。开发这类科学的基础方法，并为想要在这一领域工作的本科生和研究生提供适当的培训是至关重要的。上述研究，加上基廷博士在CSBi（麻省理工学院计算和系统生物学的教育、研究和推广计划）中的积极作用，将使我们更接近这些目标。

The research objective of this project is to use computational methods to link the molecular properties of protein-protein interactions to their broader biological roles in the genome. The project aims to demonstrate that a structural understanding of protein interaction motifs can contribute to the interpretation of high-throughput studies of protein-protein interactions, and can lead to specific and testable hypotheses about protein associations and function. The work tests this idea using the alpha-helical coiled coil, a common and important interaction motif, as an example. The specific research objectives are: (1) To build a database containing the coiled-coil sequences from numerous genomes, along with the properties of the coiled coils, the functions of the proteins, and other annotation; (2) To combine these data with structural considerations to validate high-throughput protein-protein interaction studies and to predict coiled coil-mediated interactions; and (3) To experimentally verify putative coiled coil mediated interactions predicted to have important biological roles.Broader Impacts: Dr. Keating's research and teaching at MIT are carried out in the emerging areas of computational and systems biology. These fields will have a tremendous impact on science and society in the next several decades. The sequencing of the human genome, as well as that of important pathogens, crops and scientific model organisms, has provided an opportunity for fundamentally new kinds of research combining biology, computer science, math, engineering and other quantitative fields. This interdisciplinary approach promises a deeper understanding of biology, as well as breakthroughs in biotechnology and molecular therapeutics. It is critically important to develop foundational methods for this kind of science and to provide appropriate training for undergraduate and graduate students who want to work in this area. The research described above, coupled with Dr. Keating's active role in CSBi, MIT's educational, research and outreach initiative in Computational and Systems Biology, will bring us closer to these goals.