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CAREER: Novel Sampling Approaches for Protein Modeling Applications

CAREER: Novel Sampling Approaches for Protein Modeling Applications
职业:蛋白质建模应用的新型采样方法
批准号:
1066471
负责人:
Yaohang Li
金额:
$37.67万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-09-01 至 2018-07-31

项目摘要

项目成果

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中文摘要
翻译
职业:蛋白质建模应用的新采样方法李耀航北卡罗莱纳AT州立大学精确建模蛋白质或蛋白质复合物结构被认为是一个重大的挑战,具有广泛的经济和科学影响。其中一个关键的障碍是缺乏一个可靠的采样方法,可以有效地探索巨大的蛋白质构象空间。这个CAREER项目研究有效的采样方法,可以导致预测高分辨率蛋白质结构的准确性和可靠性,目前在计算蛋白质建模中无法实现。其基本原理是通过多评分函数采样来整合各种基于物理和知识的评分函数,以探索复杂的蛋白质构象空间。本文的研究工作包括:1)建立了蛋白质结构建模中多评分函数采样的计算模型,并从理论和数学上进行了严格的论证; 2)设计了新的采样算法,以有效地探索大的蛋白质构象空间; 3)将采样算法应用于重要的蛋白质建模应用,包括从头计算蛋白质折叠和蛋白质-蛋白质对接; 4)开发一种资源有效的蛋白质建模编程范例,本研究开发的高效采样方法可以应用于各种重要的计算生物学应用,这将为蛋白质模型的可靠分辨率改进提供关键的垫脚石。高分辨率蛋白质建模的成功将对基因组研究、疾病研究、生物能源开发和药物设计行业产生重大影响。除了其研究影响,这个CAREER项目的教育目标是吸引优秀的学生,特别是少数民族,参与计算生物学研究和追求计算科学事业。
英文摘要
CAREER: Novel Sampling Approaches for Protein Modeling ApplicationsYaohang LiNorth Carolina A&T State UniversityAccurately modeling protein or protein complex structure is considered a significant grand challenge that has broad economic and scientific impact. One of the key obstacles is the absence of a reliable sampling method that can efficiently explore the tremendously large protein conformation space. This CAREER project investigates efficient sampling approaches that can lead to prediction of high resolution protein structures with accuracy and reliability currently not achievable in computational protein modeling. The rationale is to integrate various physics- and knowledge-based scoring functions via multi-scoring functions sampling to explore the complex protein conformation space. The research work includes 1) establishing computational models for multi-scoring functions sampling in protein structure modeling with theoretically and mathematically rigorous justification; 2) designing novel sampling algorithms to efficiently explore large protein conformation space; 3) applying the sampling algorithms to important protein modeling applications including ab initio protein folding and protein-protein docking; and 4) developing a resource-efficient protein modeling programming paradigm.The efficient sampling approaches developed in this research can be applied to a variety of important computational biology applications, which will provide a critical stepping stone toward reliable resolution improvement in protein models for practical use. Success of high resolution protein modeling will have significant impact on genomic study, disease research, bio-energy development, and the drug-design industry. In addition to its research impact, the educational goal of this CAREER project is to attract excellent students, particularly the minorities, to participate in computational biology research and pursue computational science career.
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会议论文
Workshop: 2011 NSF CAREER Proposal Writing Workshop
CAREER: Novel Sampling Approaches for Protein Modeling Applications
Collaborative Research: Enhancing Teaching of Grid Computing to Undergraduate Students by using a Workflow Editor
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