CIBR: Collaborative Research: CIBR Expanding structure coverage of genomes to facilitate macromolecular assembly determination.

CIBR:协作研究:CIBR 扩大基因组的结构覆盖范围,以促进大分子组装测定。

基本信息

  • 批准号:
    1937533
  • 负责人:
  • 金额:
    $ 47.36万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-08-01 至 2022-07-31
  • 项目状态:
    已结题

项目摘要

The Protein Data Bank (PDB) is the single global archive of three-dimensional (3D) structures of large biological molecules. Despite a steady increase in its holdings, the growth of the PDB is far outstripped by the growth in the available protein sequence data. Resources like Genome3D (genome3d.eu), funded by the BBSRC, aim to fill the gap in structure coverage of the protein sequence space with reliable predictions of structures. These approaches largely model proteins that are closely related to a protein of known structure. The Rosetta method for predicting protein structures, a world-leading approach developed by the Baker lab in the USA, was recently enhanced with information derived from evolutionary analyses of protein sequence data, yielding reliable models even for cases where sequence identity between the model and the available experimental structures is very low. This project will integrate Rosetta models into Genome3D to expand the coverage of structural data for important organisms for health and food security. It will also enrich both the experimentally determined and computationally predicted structures with valuable functional annotations, such as information pertaining to surface interfaces, a key ingredient in understanding how proteins interact with each other and with other biological molecules. By focusing on proteins dissimilar to those with known structures, this portal will help fill the gaps in structure coverage of the protein sequence space and will make structure data much more readily available and accessible. Finally, novel visualization tools integrating the presentation of the predicted and experimentally determined structures will be developed, maintaining a clear distinction between what is predicted and what is experimentally determined. The expanded set of 3D models derived from this project will in turn help to expand the coverage of sequence space even further, since these models can be used to guide the experimental determination of protein structures being obtained by powerful new structural biology techniques like cryo-Electron Microscopy (EM). This project will also endeavor, where possible, to improve the assembly of individual protein structures into macromolecular complexes which can be analyzed to determine their biological role. Scientists in both academia and industrial sectors will benefit from access to such an integrated portal, assisting them in designing new medicines, understanding the mechanism of disease, or in designing proteins with novel properties. Recent advances in Electron Microscopy allows near routine determination of structures of large molecular machines and is in need of a large repertoire of "building blocks" in interpreting the experimental results, a need which will be partially addressed by the new portal and its provision of expanded domain structure libraries. The portal will also have ways to access the assembled data programmatically, benefiting power users: software developers and maintainers of other resources.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
蛋白质数据库(PDB)是大型生物分子三维(3D)结构的单一全球档案。尽管其持有量稳步增长,但PDB的增长远远超过了可用蛋白质序列数据的增长。资源如Genome3D (Genome3D。eu),由BBSRC资助,旨在通过可靠的结构预测来填补蛋白质序列空间结构覆盖的空白。这些方法主要模拟与已知结构的蛋白质密切相关的蛋白质。预测蛋白质结构的Rosetta方法是由美国Baker实验室开发的一种世界领先的方法,最近通过蛋白质序列数据的进化分析获得的信息得到了增强,即使在模型和可用实验结构之间的序列一致性非常低的情况下,也能产生可靠的模型。该项目将把Rosetta模型整合到Genome3D中,以扩大对健康和粮食安全重要生物体结构数据的覆盖范围。它还将通过有价值的功能注释丰富实验确定和计算预测的结构,例如有关表面界面的信息,这是理解蛋白质如何相互作用以及与其他生物分子相互作用的关键成分。通过关注与已知结构不同的蛋白质,该门户将有助于填补蛋白质序列空间结构覆盖的空白,并使结构数据更容易获得和访问。最后,将开发新的可视化工具,整合预测和实验确定的结构的呈现,保持预测和实验确定之间的明确区分。从该项目衍生的扩展的3D模型集反过来将有助于进一步扩大序列空间的覆盖范围,因为这些模型可用于指导通过强大的新结构生物学技术(如冷冻电子显微镜(EM))获得的蛋白质结构的实验测定。在可能的情况下,该项目还将努力改进将单个蛋白质结构组装成大分子复合物的方法,从而可以对其进行分析以确定其生物学作用。学术界和工业部门的科学家都将受益于获得这样一个综合门户,帮助他们设计新药、了解疾病的机制或设计具有新特性的蛋白质。电子显微镜的最新进展允许对大分子机器的结构进行接近常规的确定,并且需要大量的“构建块”来解释实验结果,这一需求将通过新的门户及其提供的扩展域结构库部分解决。门户还将具有以编程方式访问组装数据的方法,从而使高级用户(软件开发人员和其他资源的维护人员)受益。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(5)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Computed structures of core eukaryotic protein complexes.
  • DOI:
    10.1126/science.abm4805
  • 发表时间:
    2021-12-10
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Humphreys IR;Pei J;Baek M;Krishnakumar A;Anishchenko I;Ovchinnikov S;Zhang J;Ness TJ;Banjade S;Bagde SR;Stancheva VG;Li XH;Liu K;Zheng Z;Barrero DJ;Roy U;Kuper J;Fernández IS;Szakal B;Branzei D;Rizo J;Kisker C;Greene EC;Biggins S;Keeney S;Miller EA;Fromme JC;Hendrickson TL;Cong Q;Baker D
  • 通讯作者:
    Baker D
{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

David Baker其他文献

Designed repeat protein in complex with Fz7
设计与 Fz7 复合的重复蛋白
  • DOI:
    10.2210/pdb6ne2/pdb
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    16.8
  • 作者:
    Luke T. Dang;Y. Miao;A. Ha;Kanako Yuki;K. Park;C. Y. Janda;K. Jude;K. Mohan;N. Ha;Mario Vallon;Jenny Yuan;J. Vilches;C. Kuo;K. Garcia;David Baker
  • 通讯作者:
    David Baker
Trypanosoma cruzi adenylyl cyclase is encoded by a complex multigene family.
克氏锥虫腺苷酸环化酶由复杂的多基因家族编码。
VaxCelerate II: Rapid development of a self-assembling vaccine VaxCelerate II: Rapid development of a self-assembling vaccine for Lassa fever for Lassa fever
VaxCelerate II:快速开发拉沙热自组装疫苗 VaxCelerate II:快速开发拉沙热自组装疫苗
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Pierre Leblanc;L. Moise;Cybelle Luza;Kanawat Chantaralawan;Lynchy Lezeau;Jianping Yuan;M. Field;Daniel Richer;C. Boyle;William D Martin;Jordan B Fishman;Eric A Berg;David Baker;Brandon Zeigler;Dale E Mais;William Taylor;Russell Coleman;Shaw Warren;Jeffrey A. Gelfand;A. S. D. Groot;Timothy Brauns;M. Poznansky
  • 通讯作者:
    M. Poznansky
Big History’s Big Potential
大历史的大潜力
  • DOI:
  • 发表时间:
    2014
  • 期刊:
  • 影响因子:
    0
  • 作者:
    L. Grinin;David Baker;E. Quaedackers;Andrey Korotayev
  • 通讯作者:
    Andrey Korotayev
Engaging a community to focus on upper limb function in people with multiple sclerosis: the ThinkHand campaign case study
让社区关注多发性硬化症患者的上肢功能:ThinkHand 活动案例研究
  • DOI:
    10.1186/s40900-024-00586-y
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Alison Thomson;Rachel Horne;Christine Chapman;Trishna Bharadia;Patrick Burke;Elizabeth Colwell;Mark Harrington;Bonnie Boskovic;Andrea M Stennett;David Baker;Gavin Giovannoni;K. Schmierer
  • 通讯作者:
    K. Schmierer

David Baker的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('David Baker', 18)}}的其他基金

MFB: Deep-Learning Enabled Structure Prediction and Design of Protein-DNA Assemblies
MFB:深度学习支持蛋白质-DNA 组装的结构预测和设计
  • 批准号:
    2226466
  • 财政年份:
    2022
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Standard Grant
Co-production of a software tool for field-scale species distribution modelling (fs-SDM) and mapping using local biodiversity records
共同开发用于野外规模物种分布建模 (fs-SDM) 和使用当地生物多样性记录进行绘图的软件工具
  • 批准号:
    NE/V007726/1
  • 财政年份:
    2020
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Fellowship
Generation, functionalization, and distribution of de novo designed protein nanomaterials
从头设计的蛋白质纳米材料的生成、功能化和分布
  • 批准号:
    1629214
  • 财政年份:
    2016
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Standard Grant
RAPID: Empowering the Citizen Scientist in the Fight Against Ebolaviruses
RAPID:赋予公民科学家抗击埃博拉病毒的能力
  • 批准号:
    1523362
  • 财政年份:
    2015
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Standard Grant
I-Corps: Enterprise Rosetta Protein Modelling and Design Software on the Cloud
I-Corps:云端企业 Rosetta 蛋白质建模和设计软件
  • 批准号:
    1507114
  • 财政年份:
    2014
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Standard Grant
ERASynBio: BioMolecular Origami
ERASynBio:生物分子折纸
  • 批准号:
    1445201
  • 财政年份:
    2014
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Standard Grant
DMREF Integrating theory, computation and experiment to robustly design complex protein-based nanomaterials
DMREF 整合理论、计算和实验,稳健地设计复杂的基于蛋白质的纳米材料
  • 批准号:
    1332907
  • 财政年份:
    2013
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Standard Grant
SBIR Phase II: Serious Gaming Platform for Mastering the Physician-Patient Diagnostic Interview
SBIR 第二阶段:掌握医患诊断访谈的严肃游戏平台
  • 批准号:
    1230418
  • 财政年份:
    2012
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Standard Grant
Identical Particles and Statistics in Superselection Theory
超选择理论中的相同粒子和统计
  • 批准号:
    1127260
  • 财政年份:
    2011
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Standard Grant
SBIR Phase I: Serious Gaming Platform for Mastering the Physician-Patient Diagnostic Interview
SBIR 第一阶段:掌握医患诊断访谈的严肃游戏平台
  • 批准号:
    1046589
  • 财政年份:
    2011
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Standard Grant

相似海外基金

Collaborative Research: CIBR: Leaping the Specimen Digitization Gap: Connecting Novel Tools, Machine Learning and Public Participation to Label Digitization Efforts
合作研究:CIBR:跨越标本数字化差距:将新工具、机器学习和公众参与与标签数字化工作联系起来
  • 批准号:
    2027241
  • 财政年份:
    2021
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Standard Grant
Collaborative Research: CIBR: Leaping the Specimen Digitization Gap: Connecting Novel Tools, Machine Learning and Public Participation to Label Digitization Efforts
合作研究:CIBR:跨越标本数字化差距:将新工具、机器学习和公众参与与标签数字化工作联系起来
  • 批准号:
    2027234
  • 财政年份:
    2021
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Standard Grant
Collaborative Research: CIBR: Incorporating Crystallography and Cryo-EM Tools in Foldit
合作研究:CIBR:在 Foldit 中结合晶体学和冷冻电镜工具
  • 批准号:
    2051305
  • 财政年份:
    2021
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Standard Grant
Collaborative Research: CIBR: The OpenBehavior Project
合作研究:CIBR:开放行为项目
  • 批准号:
    1948181
  • 财政年份:
    2021
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Continuing Grant
Collaborative Research: CIBR: Incorporating Crystallography and Cryo-EM tools into Foldit
合作研究:CIBR:将晶体学和冷冻电镜工具纳入 Foldit
  • 批准号:
    2051282
  • 财政年份:
    2021
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Standard Grant
Collaborative Research: CIBR: Leaping the Specimen Digitization Gap: Connecting Novel Tools, Machine Learning and Public Participation to Label Digitization Efforts
合作研究:CIBR:跨越标本数字化差距:将新工具、机器学习和公众参与与标签数字化工作联系起来
  • 批准号:
    2027228
  • 财政年份:
    2021
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Standard Grant
Collaborative Research: CIBR: Building Capacity for Data-driven Neuroscience Research
合作研究:CIBR:数据驱动神经科学研究能力建设
  • 批准号:
    1935771
  • 财政年份:
    2020
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Standard Grant
Collaborative Research: CIBR: VectorByte: A Global Informatics Platform for studying the Ecology of Vector-Borne Diseases
合作研究:CIBR:VectorByte:研究媒介传播疾病生态学的全球信息学平台
  • 批准号:
    2016282
  • 财政年份:
    2020
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Continuing Grant
Collaborative Research: CIBR: Computational resources for modeling and analysis of realistic cell membranes
合作研究:CIBR:用于真实细胞膜建模和分析的计算资源
  • 批准号:
    2011234
  • 财政年份:
    2020
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Standard Grant
Collaborative Research: CIBR: VectorByte: A Global Informatics Platform for studying the Ecology of Vector-Borne Diseases
合作研究:CIBR:VectorByte:研究媒介传播疾病生态学的全球信息学平台
  • 批准号:
    2016265
  • 财政年份:
    2020
  • 资助金额:
    $ 47.36万
  • 项目类别:
    Continuing Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了