EAGER: A novel approach to improve template-based multi-domain protein structure prediction
EAGER:一种改进基于模板的多域蛋白质结构预测的新方法
基本信息
- 批准号:1647884
- 负责人:
- 金额:$ 15万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-09-01 至 2018-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The National Science Foundation uses the Early-concept Grants for Exploratory Research (EAGER) funding mechanism to support exploratory work in its early stages on untested, but potentially transformative, research ideas or approaches. This EAGER project was awarded as a result of the invitation in the Dear Colleague Letter NSF 16-080 to proposers from Historically Black Colleges and Universities to submit proposals that would strengthen research capacity of faculty at the institution. The project at North Carolina A&T State University (NC A&T) aims to obtain preliminary data to support cutting-edge research to design novel computational tools to model multi-domain protein structure. The spatial arrangement of domains is essential in understanding the functional mechanisms of a multi-domain protein. This project will also help broaden the participation in protein modeling research of students at NC A&T with a growing research enterprise.This study aims to obtain preliminary data to design novel computational tools to enhance capabilities of template-based approaches for prediction of multi-domain proteins. Essentially, the availability of full-domain solved template structures for modeling multi-domain proteins in current PDB (Protein Data Bank) will be systematically analyzed. This systematic study to assess the availability of templates for multi-domain proteins in PDB will shed light on the extent of availability of templates for multi-domain proteins. These multi-domain proteins are generally not suitable for structure determination based on biochemical experimental techniques, and these proteins can also exhibit inter-domain flexibility, which can complicate or prevent crystallization. As a consequence, experimental determination of the structure of multi-domain proteins is often more difficult than for single domain proteins. Based on the systematic study, efforts will also be made to develop a novel strategy to identify distant or non-homologous template structures. This will be performed using complex matching based strategy. The results of the finding will significantly increase our ability to model multi-domain protein structure and will help to increase our understanding of protein complexes.This EAGER project is funded by the Biology Directorate.
美国国家科学基金会(National Science Foundation)使用早期概念赠款进行探索性研究(急切)资金机制,以在未经测试但可能具有变革性的研究思想或方法的早期阶段支持探索性工作。这项渴望的项目是由于尊敬的同事信函NSF 16-080向历史悠久的黑人学院和大学提出的提议提出的提议提出的提议,以提高该机构的研究能力。北卡罗来纳州A&T州立大学(NC A&T)的项目旨在获取初步数据,以支持尖端研究,以设计新颖的计算工具,以模拟多域蛋白质结构。域的空间排列对于理解多域蛋白的功能机理至关重要。该项目还将有助于扩大NC A&T学生在不断增长的研究企业中对蛋白质建模研究的参与。本研究旨在获取初步数据以设计新型计算工具,以增强基于模板的方法预测多域蛋白质的能力。本质上,将系统地分析全域解决的模板结构,用于建模当前PDB中多域蛋白(蛋白质数据库)中的多域蛋白。这项用于评估PDB中多域蛋白模板可用性的系统研究将阐明多域蛋白的模板的可用性。这些多域蛋白通常不适用于基于生化实验技术的结构测定,并且这些蛋白质也可以表现出域间的柔韧性,这可能会使或防止结晶复杂化。结果,多域蛋白质结构的实验确定通常比单域蛋白更难。基于系统的研究,还将努力制定一种新的策略来识别遥远或非同源模板结构。这将使用基于复杂的匹配策略进行。该发现的结果将显着提高我们对多域蛋白质结构进行建模的能力,并有助于增加我们对蛋白质复合物的理解。这一急切的项目由生物学局资助。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Dukka KC其他文献
Dukka KC的其他文献
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{{ truncateString('Dukka KC', 18)}}的其他基金
MRI: Acquisition of a GPU-accelerated cluster for research, training and outreach
MRI:获取 GPU 加速集群用于研究、培训和推广
- 批准号:
2215734 - 财政年份:2022
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
III: Medium: Collaborative Research: Multi-level computational approaches to protein function prediction
III:媒介:协作研究:蛋白质功能预测的多级计算方法
- 批准号:
2210356 - 财政年份:2021
- 资助金额:
$ 15万 - 项目类别:
Continuing Grant
Collaborative Research: ABI Development: Integrated platforms for protein structure and function predictions
合作研究:ABI开发:蛋白质结构和功能预测的集成平台
- 批准号:
2021734 - 财政年份:2020
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
III: Medium: Collaborative Research: Multi-level computational approaches to protein function prediction
III:媒介:协作研究:蛋白质功能预测的多级计算方法
- 批准号:
1901086 - 财政年份:2019
- 资助金额:
$ 15万 - 项目类别:
Continuing Grant
III: Medium: Collaborative Research: Multi-level computational approaches to protein function prediction
III:媒介:协作研究:蛋白质功能预测的多级计算方法
- 批准号:
2003019 - 财政年份:2019
- 资助金额:
$ 15万 - 项目类别:
Continuing Grant
Collaborative Research: ABI Development: Integrated platforms for protein structure and function predictions
合作研究:ABI开发:蛋白质结构和功能预测的集成平台
- 批准号:
1564606 - 财政年份:2016
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
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