BBSRC-NSF/BIO - Expanding fold library in the twilight zone to facilitate structure determination of macromolecular machines

BBSRC-NSF/BIO - 扩展暮光区的折叠库以促进大分子机器的结构测定

• 批准号: BB/S017135/1
• 负责人: Sameer Velankar
• 金额: $ 43万
• 依托单位: European Bioinformatics Institute
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FS017135%2F1
• 关键词: BBSRC; NSF; BIO; Expanding; fold

The Protein Data Bank (PDB) is the single global archive of three-dimensional (3D) structures of large biological molecules. PDBe (pdbe.org) is the European partner in the global consortium managing the PDB. PDB is one of the oldest biological archives, with 144,000+ entries and nearly 2 million downloads daily by users worldwide in academic or industry settings, working on topics ranging from food security, human health through to design of more efficient enzymes in various aspects of biotechnology. Despite a steady increase in its holdings (13,000+ entries added in 2017), 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. This resource combines data from a number of UK and overseas groups who apply complementary methods for protein structure prediction. These approaches largely model proteins that are closely related to a protein of known structure (ie the protein relatives share more than 30% identical residues in their sequences). 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 (below 30%). We will integrate Rosetta models into Genome3D to expand the coverage of structural data for important organisms for health (e.g. human) and food security (e.g. wheat).This project 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 focussing 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 visualisation 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 endeavour, where possible, to improve the assembly of individual protein structures into macromolecular complexes which can be analysed to determine their biological role. We anticipate that scientists in both academia and industrial sectors (e.g. pharmaceutical companies) 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 "resolution revolution" 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.

蛋白质数据库（PDB）是大生物分子的三维（3D）结构的单个全局档案。 PDBE（pdbe.org）是管理PDB的全球财团的欧洲合作伙伴。 PDB是最古老的生物档案馆之一，全球在学术或行业环境中每天有144,000多个条目，每天下载近200万，从事粮食安全，人类健康到设计更有效的酶的主题，在生物技术的各个方面。尽管其持有量稳定增长（2017年添加了13,000多个条目），但PDB的增长远远超过了可用蛋白质序列数据的增长。由BBSRC资助的Genome3D（Genome3D.EU）之类的资源旨在填补蛋白质序列空间的结构覆盖范围，并具有可靠的结构预测。该资源结合了来自许多英国和海外群体的数据，这些数据将互补方法用于蛋白质结构预测。这些方法在很大程度上模拟了与已知结构蛋白密切相关的蛋白质（即蛋白亲属在其序列中共有30％以上相同的残基）。 Rosetta预测蛋白质结构的方法是美国贝克实验室在美国开发的世界领先的方法，它通过蛋白质序列数据的进化分析得出的信息得到了增强，即使对于模型与可用实验结构之间的序列身份的情况也很低（低于30％），也可以产生可靠的模型。我们将将Rosetta模型集成到Genome3D中，以扩大重要生物（例如人类）和粮食安全（例如小麦）（例如小麦）的结构数据的覆盖范围。该项目还将丰富具有实验确定的和计算预测的结构，并具有有价值的功能注释，例如与表面界面有关的信息与其他型组成型相互作用，并且与其他相互作用的构成相互作用。通过关注蛋白质与具有已知结构的蛋白质不同，该门户将有助于填补蛋白质序列空间的结构覆盖范围的空白，并使结构数据更容易获得和访问。最后，将开发整合预测和实验确定结构的呈现的新型可视化工具，并在预测和实验确定的内容之间保持明显的区别。从该项目中得出的扩展的3D模型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（例如低温电子显微镜（EM））获得的蛋白质结构的实验确定。该项目还将在可能的情况下努力改善单个蛋白质结构的组装到大分子复合物中，可以分析这些蛋白质结构以确定其生物学作用。我们预计，学术界和工业部门的科学家（例如制药公司）都将受益于进入这种综合门户网站，从而帮助他们设计新药物，了解疾病的机制或设计具有新型特性的蛋白质。电子显微镜中最近的“分辨率革命”允许几乎常规地确定大型分子机器的结构，并且需要大量的“构件”曲目来解释实验结果，这一需求将由新的门户网站及其提供的扩展领域结构库的提供。该门户网站还将有办法以编程方式访问组装的数据，使Power用户受益：软件开发人员和其他资源的维护者。

项目成果

Characterizing and explaining impact of disease-associated mutations in proteins without known structures or structural homologues

• DOI: 10.1101/2021.11.17.468998
• 发表时间: 2021-11
• 期刊: bioRxiv
• 作者: Neeladri Sen;I. Anishchenko;N. Bordin;I. Sillitoe;S. Velankar;D. Baker;C. Orengo

PDBe and PDBe-KB: Providing high-quality, up-to-date and integrated resources of macromolecular structures to support basic and applied research and education.

• DOI: 10.1002/pro.4439
• 发表时间: 2022-10
• 期刊: PROTEIN SCIENCE
• 影响因子: 8
• 作者: Varadi, Mihaly;Anyango, Stephen;Appasamy, Sri Devan;Armstrong, David;Bage, Marcus;Berrisford, John;Choudhary, Preeti;Bertoni, Damian;Deshpande, Mandar;Leines, Grisell Diaz;Ellaway, Joseph;Evans, Genevieve;Gaborova, Romana;Gupta, Deepti;Gutmanas, Aleksandras;Harrus, Deborah;Kleywegt, Gerard J.;Bueno, Weslley Morellato;Nadzirin, Nurul;Nair, Sreenath;Pravda, Lukas;Afonso, Marcelo Querino Lima;Sehnal, David;Tanweer, Ahsan;Tolchard, James;Abrams, Charlotte;Dunlop, Roisin;Velankar, Sameer
• 通讯作者: Velankar, Sameer