SUPERFAMILY

超级家庭

• 批准号: BB/N019431/1
• 负责人: Julian Gough
• 金额: $ 65.2万
• 依托单位: University of Bristol
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FN019431%2F1
• 关键词: SUPERFAMILY

SUPERFAMILY is a popular resource that detects and classifies protein domains of known structure in genome sequences.Small proteins are a single unit but larger proteins can be made up of multiple subunits we call domains. Domains are modular evolutionary blocks which form components of whole proteins via duplication and recombination of existing units. X-ray crystallography and NMR experiments provide the 3D atomic resolution structure of proteins allowing the domains to be grouped into related families which often share a common or related function. The SUPERFAMILY database contains a library of profiles of these domain families in the form of hidden Markov models. These models are a computational tool which can detect the presence of domains in the sequences of proteins.Some years ago the complete human genome was experimentally characterised, giving us a list of all the sequences of the proteins. The genomes of many other organisms have also been sequenced and at this time we have the complete sequences for the proteins of thousands of organisms. The SUPERFAMILY model library is run against all the genomes to identify the domains in the proteins. The data produced by the SUPERFAMILY analysis can be used for example by biologists working on specific proteins in the laboratory, larger projects working on a whole genome, or to improve our understanding of molecular evolution across all genomes and all kingdoms of life.The SUPERFAMILY website enables users to enter sequences to search against the model library. The results of the domain assignments to all the genomes are stored in a database and can also be viewed on the website. There are many tools and ways of browsing the data which allow the comparison of different organisms, proteins and domains to allow researchers to answer biological questions. The data, software and model library are available for people to download wholesale to carry out their own analysis. The information contained in SUPERFAMILY feeds into several other websites and resources, e.g. the ENSEMBL human genome website, which bring together different specialist sources of data to display alongside each other.

SUPERFAMILY是一个流行的资源，它检测和分类基因组序列中已知结构的蛋白质结构域。小蛋白质是一个单一的单位，但较大的蛋白质可以由多个亚基组成，我们称之为结构域。结构域是模块化的进化块，通过现有单元的复制和重组形成整个蛋白质的组分。X射线晶体学和NMR实验提供了蛋白质的3D原子分辨率结构，允许将结构域分组为通常具有共同或相关功能的相关家族。SUPERFAMILY数据库包含了一个以隐马尔可夫模型形式的这些域族的配置文件库。这些模型是一种计算工具，可以检测蛋白质序列中结构域的存在。几年前，完整的人类基因组被实验表征，给了我们所有蛋白质序列的列表。许多其他生物体的基因组也已被测序，目前我们已拥有数千种生物体蛋白质的完整序列。SUPERFAMILY模型库针对所有基因组运行以识别蛋白质中的结构域。SUPERFAMILY分析产生的数据可以用于例如在实验室中研究特定蛋白质的生物学家，研究整个基因组的大型项目，或者提高我们对所有基因组和所有生命王国的分子进化的理解。SUPERFAMILY网站允许用户输入序列以搜索模型库。所有基因组的域分配结果存储在数据库中，也可以在网站上查看。有许多浏览数据的工具和方法，可以比较不同的生物体，蛋白质和结构域，让研究人员回答生物学问题。数据、软件和模型库可供人们批量下载，以进行自己的分析。SUPERFAMILY中包含的信息可以输入到其他几个网站和资源中，例如ENSEMBL人类基因组网站，该网站汇集了不同的专业数据来源，相互显示。

项目成果

InterPro in 2017-beyond protein family and domain annotations.

• DOI: 10.1093/nar/gkw1107
• 发表时间: 2017-01-04
• 期刊: Nucleic acids research
• 影响因子: 14.9
• 作者: Finn RD;Attwood TK;Babbitt PC;Bateman A;Bork P;Bridge AJ;Chang HY;Dosztányi Z;El-Gebali S;Fraser M;Gough J;Haft D;Holliday GL;Huang H;Huang X;Letunic I;Lopez R;Lu S;Marchler-Bauer A;Mi H;Mistry J;Natale DA;Necci M;Nuka G;Orengo CA;Park Y;Pesseat S;Piovesan D;Potter SC;Rawlings ND;Redaschi N;Richardson L;Rivoire C;Sangrador-Vegas A;Sigrist C;Sillitoe I;Smithers B;Squizzato S;Sutton G;Thanki N;Thomas PD;Tosatto SC;Wu CH;Xenarios I;Yeh LS;Young SY;Mitchell AL
• 通讯作者: Mitchell AL

Evolution of the Calcium-Based Intracellular Signaling System.

• DOI: 10.1093/gbe/evw139
• 发表时间: 2016-07-14
• 期刊: Genome biology and evolution
• 影响因子: 3.3
• 作者: Marchadier E;Oates ME;Fang H;Donoghue PC;Hetherington AM;Gough J
• 通讯作者: Gough J

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

CAFA 挑战报告通过实验筛选改进了蛋白质功能预测和数百个基因的新功能注释

• DOI: 10.1101/653105
• 发表时间: 2019
• 作者: Zhou N

Hypothesis-free phenotype prediction within a genetics-first framework.

• DOI: 10.1038/s41467-023-36634-6
• 发表时间: 2023-02-17
• 期刊: NATURE COMMUNICATIONS
• 影响因子: 16.6
• 作者: Lu, Chang;Zaucha, Jan;Gam, Rihab;Fang, Hai;Smithers, Ben E.;Oates, Matt;Bernabe-Rubio, Miguel;Williams, James;Zelenka, Natalie;Pandurangan, Arun Prasad;Tandon, Himani;Shihab, Hashem;Kalaivani, Raju;Sung, Minkyung J.;Sardar, Adam;Tzovoras, Bastian Greshake;Danovi, Davide;Gough, Julian
• 通讯作者: Gough, Julian

MOESM2 of The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

CAFA 挑战赛的 MOESM2 报告通过实验筛选改进了蛋白质功能预测和数百个基因的新功能注释

• DOI: 10.6084/m9.figshare.10458518
• 发表时间: 2019
• 作者: Zhou N