BioComp: A Computational Framework for the Characterization of Biological Systems at the Molecular Level

BioComp:分子水平生物系统表征的计算框架

基本信息

  • 批准号:
    0523908
  • 负责人:
  • 金额:
    $ 30万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2005
  • 资助国家:
    美国
  • 起止时间:
    2005-07-15 至 2010-06-30
  • 项目状态:
    已结题

项目摘要

Protein modeling is becoming increasingly important for the characterization of biological systems at the molecular level. It is now widely accepted that the key to understanding biological function, and subsequently disease, is to understand the structure, flexibility, kinetics, and dynamics of the body's worker molecules, proteins. Recent successes in understanding the structure and dynamics of proteins using computational analysis underscore the importance of developing computational methodologies to explore the fundamental principles of protein flexibility. Representing a protein by a single configuration is less and less attractive, as such a representation does not represent the dynamical interplay of different conformations that can regulate protein function and does not fully characterize the protein's interaction with neighboring molecules.This proposal will develop a computational framework for the characterization of protein flexibility at equilibrium conditions through a combination of geometric/robotic and biophysics methods. The proposed work lies at the intersection of computer science and modern biophysics, and will benefit both communities. On the computational side, it will lead to new methodologies and paradigms to model physical systems with high flexibility, complex geometry, multiple constraints, and continuous motion. Successful robotics and computational geometry methods will be adapted to support the large-scale analysis required for biological applications. On the biophysical side, novel theories and methodologies will be developed and tested for modeling proteins at different resolutions. Quantitative connections between theory and experiment will be pursued. The proposed work has the potential to dramatically affect major unresolved problems on the inner workings of protein systems.
蛋白质建模对于在分子水平上表征生物系统变得越来越重要。现在人们普遍认为,理解生物功能和疾病的关键是理解身体的工作分子蛋白质的结构、灵活性、动力学和动力学。最近的成功理解蛋白质的结构和动力学,利用计算分析强调了发展计算方法的重要性,以探索蛋白质的灵活性的基本原则。用单一构型来表示蛋白质越来越没有吸引力,因为这种表示并不能代表可以调节蛋白质功能的不同构象的动态相互作用,也不能完全表征蛋白质与邻近分子的相互作用。该提案将开发一个计算框架,通过几何/机器人和生物物理学方法。拟议的工作位于计算机科学和现代生物物理学的交叉点,并将使两个社区受益。在计算方面,它将导致新的方法和范式来建模具有高度灵活性,复杂几何形状,多约束和连续运动的物理系统。成功的机器人学和计算几何学方法将被用于支持生物学应用所需的大规模分析。在生物物理方面,将开发和测试新的理论和方法,用于在不同分辨率下建模蛋白质。理论和实验之间的定量联系将被追求。这项工作有可能极大地影响蛋白质系统内部工作中尚未解决的主要问题。

项目成果

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Lydia Kavraki其他文献

Lydia Kavraki的其他文献

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{{ truncateString('Lydia Kavraki', 18)}}的其他基金

A Framework for Manipulation Planning and Execution under Uncertainty in Partially-Known Environments
部分已知环境中不确定性下的操纵规划和执行框架
  • 批准号:
    2336612
  • 财政年份:
    2024
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
Collaborative Research [FW-HTF-RM]: The Future of Nurse Training: Robotic Teaching Assistant Systems for Nursing Instructors
协作研究 [FW-HTF-RM]:护士培训的未来:护理讲师的机器人助教系统
  • 批准号:
    2326390
  • 财政年份:
    2023
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
Collaborative Research: FW-HTF-R: The Future of Robot-Assisted Nursing: Interactive AI Frameworks for Upskilling Nurses and Customizing Robot Assistance
合作研究:FW-HTF-R:机器人辅助护理的未来:用于提高护士技能和定制机器人辅助的交互式人工智能框架
  • 批准号:
    2222876
  • 财政年份:
    2022
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
IIBR:Informatics:RAPID: Structure-based identification of SARS-derived peptides with potential to induce broad protective immunity
IIBR:信息学:RAPID:基于结构的 SARS 衍生肽的鉴定,具有诱导广泛保护性免疫的潜力
  • 批准号:
    2033262
  • 财政年份:
    2020
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
RI: Small: A Novel Framework for Informed Manipulation Planning
RI:小型:知情操纵规划的新颖框架
  • 批准号:
    2008720
  • 财政年份:
    2020
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
NRI: FND: Robotic Collaboration through Scalable Reactive Synthesis
NRI:FND:通过可扩展反应合成进行机器人协作
  • 批准号:
    1830549
  • 财政年份:
    2018
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
RI: Small: Robot Motion Planning with an Experience Database
RI:小型:使用经验数据库进行机器人运动规划
  • 批准号:
    1718478
  • 财政年份:
    2017
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
SHF: Medium: Automating robot programming through constraint solving and motion planning
SHF:中:通过约束求解和运动规划实现机器人编程自动化
  • 批准号:
    1514372
  • 财政年份:
    2015
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
AF: Small: An Integrated Approach to Characterizing Conformational Changes of Large Proteins
AF:小:表征大蛋白质构象变化的综合方法
  • 批准号:
    1423304
  • 财政年份:
    2014
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
NRI: Small: Collaborative Research: Rethinking Motion Generation for Robots Operating in Human Workspaces
NRI:小型:协作研究:重新思考在人类工作空间中操作的机器人的运动生成
  • 批准号:
    1317849
  • 财政年份:
    2013
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant

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Computational Methods for Analyzing Toponome Data
  • 批准号:
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  • 批准年份:
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