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Dimensionality Reduction and Search for Analyzing Protein Structure

蛋白质结构分析的降维和搜索

基本信息

批准号：
7619644
负责人：
Lydia E. Kavraki
金额：
$ 17.81万
依托单位：
RICE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2006
资助国家：
美国
起止时间：
2006-05-11 至 2011-04-30
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): It is virtually impossible to find a physiological function that does not actively involve single proteins or protein complexes at a certain stage. There is a huge gap in our knowledge of how protein structure relates to protein function or to cooperative mechanisms in macromolecular complexes, although these issues have been challenging scientists for many years. There is also great promise that understanding how systems such as proteins and protein complexes work, will impact the rational design of drugs and enzymes, and suggest better treatments for certain diseases. The intellectual merit of this project lies in the development of a novel framework to explore the conformational space of proteins and protein complexes. Our goal is to generate geometrically-distinct low energy conformations of the above systems. We will pursue the development of dimensionality reduction methods that are tailored to complex molecular systems and can be used to represent such systems compactly. Using those representations we will aggressively explore the conformational landscape of proteins, initially, and protein complexes, at a later stage. We believe that the tight coupling of dimensionality reduction and efficient search algorithms will result in a method that can reason about large systems with some probabilistic guarantees, a presently elusive goal. A distinguishing feature of our method is that we will modify and update our low-dimensional representations as the exploration of the conformational landscape progresses in order to best represent the considered system as it evolves. The output of our work can be used to study the possible shapes of a biomacromolecule and shed light on its function. As far as applications are concerned, we will first tackle problems that relate to molecular docking and computer-assisted drug design. In the long run, our goal is to study molecular machines and macromolecular assemblies in collaboration with experimentalists. The broader impact of the project is implemented through (a) interdisciplinary collaborations with the Texas Medical Center which will affect students in applied and computational mathematics, computer science, biology, and biochemistry, (b) training, mentoring and involvement in research activities of undergraduate, graduate and postdoctoral students, (c) course development at Rice University, (d) mentoring of women undergraduate students in computer science, and (e) participation in an NSF funded program of Rice University and the Houston Independent School District whose goal is to attract high school girls to fields where they are underrepresented.

描述(申请人提供)：在某一阶段，几乎不可能找到一种不涉及单一蛋白质或蛋白质复合体的生理功能。尽管这些问题多年来一直困扰着科学家，但在我们对蛋白质结构如何与蛋白质功能或大分子复合体中的合作机制相关的知识方面存在着巨大的差距。了解蛋白质和蛋白质复合体等系统的工作原理也有很大的希望，这将影响药物和酶的合理设计，并为某些疾病提供更好的治疗方法。这个项目的智力价值在于开发了一个新的框架来探索蛋白质和蛋白质复合体的构象空间。我们的目标是产生上述体系的几何上不同的低能构象。我们将致力于为复杂的分子系统量身定做的降维方法的发展，并可用于紧凑地表示此类系统。使用这些表示法，我们将积极探索蛋白质的构象图景，最初，以及稍后阶段的蛋白质复合体。我们相信，降维和高效搜索算法的紧密耦合将导致一种方法，可以在某种概率保证下对大型系统进行推理，这是目前难以实现的目标。我们方法的一个显著特点是，随着构象景观的探索进展，我们将修改和更新我们的低维表示法，以便在所考虑的系统演化时最好地表示它。我们的工作成果可以用来研究生物大分子的可能形状，并阐明其功能。在应用方面，我们将首先解决与分子对接和计算机辅助药物设计有关的问题。从长远来看，我们的目标是与实验者合作研究分子机器和大分子组装。该项目的更广泛影响通过以下方式实现：(A)与德克萨斯医学中心开展跨学科合作，这将影响到应用数学和计算数学、计算机科学、生物学和生物化学方面的学生；(B)对本科生、研究生和博士后进行培训、辅导和参与研究活动；(C)在莱斯大学开发课程；(D)辅导计算机科学方面的女本科生；以及(E)参与国家科学基金会资助的莱斯大学和休斯顿独立学区的一项计划，其目标是吸引高中女生进入其代表性不足的领域。