SUPERFAMILY

超级家庭

• 批准号: BB/N019431/2
• 负责人: Julian Gough
• 金额: $ 62.15万
• 依托单位: MRC Laboratory of Molecular Biology
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FN019431%2F2
• 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.

超家族是一种对基因组序列中已知结构的蛋白质结构域进行检测和分类的常用资源，小的蛋白质是一个单一的单位，但较大的蛋白质可以由多个亚单位组成，我们称之为结构域。结构域是模块化的进化块，通过复制和重组现有的单位形成整个蛋白质的组成部分。X射线结晶学和核磁共振实验提供了蛋白质的3D原子分辨率结构，允许将结构域划分为相关的家族，这些家族通常具有共同或相关的功能。超家族数据库以隐马尔可夫模型的形式包含这些领域家族的简档库。这些模型是一种计算工具，可以检测蛋白质序列中是否存在结构域。几年前，我们对整个人类基因组进行了实验表征，给出了所有蛋白质序列的清单。许多其他生物的基因组也已经被测序，目前我们已经有了数千个生物的蛋白质的完整序列。超家族模型库与所有基因组进行比对，以确定蛋白质中的结构域。例如，超家族分析产生的数据可用于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。超家族网站使用户能够输入序列，以根据模型库进行搜索。所有基因组的结构域分配结果都存储在数据库中，也可以在网站上查看。有许多工具和方法可以浏览数据，这些工具和方法允许比较不同的生物体、蛋白质和结构域，从而使研究人员能够回答生物学问题。数据、软件和模型库可供人们批量下载进行自己的分析。超级家族中包含的信息被提供给其他几个网站和资源，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，相互并排显示。

项目成果

Performance of in silico tools for the evaluation of p16INK4a (CDKN2A) variants in CAGI.

• DOI: 10.1002/humu.23235
• 发表时间: 2017-09
• 期刊: Human mutation
• 影响因子: 3.9
• 作者: Carraro M;Minervini G;Giollo M;Bromberg Y;Capriotti E;Casadio R;Dunbrack R;Elefanti L;Fariselli P;Ferrari C;Gough J;Katsonis P;Leonardi E;Lichtarge O;Menin C;Martelli PL;Niroula A;Pal LR;Repo S;Scaini MC;Vihinen M;Wei Q;Xu Q;Yang Y;Yin Y;Zaucha J;Zhao H;Zhou Y;Brenner SE;Moult J;Tosatto SCE
• 通讯作者: Tosatto SCE

The InterPro protein families and domains database: 20 years on.

• DOI: 10.1093/nar/gkaa977
• 发表时间: 2021-01-08
• 期刊: Nucleic acids research
• 影响因子: 14.9
• 作者: Blum M;Chang HY;Chuguransky S;Grego T;Kandasaamy S;Mitchell A;Nuka G;Paysan-Lafosse T;Qureshi M;Raj S;Richardson L;Salazar GA;Williams L;Bork P;Bridge A;Gough J;Haft DH;Letunic I;Marchler-Bauer A;Mi H;Natale DA;Necci M;Orengo CA;Pandurangan AP;Rivoire C;Sigrist CJA;Sillitoe I;Thanki N;Thomas PD;Tosatto SCE;Wu CH;Bateman A;Finn RD
• 通讯作者: Finn RD

InterPro in 2019: improving coverage, classification and access to protein sequence annotations.

• DOI: 10.1093/nar/gky1100
• 发表时间: 2019-01-08
• 期刊: Nucleic acids research
• 影响因子: 14.9
• 作者: Mitchell AL;Attwood TK;Babbitt PC;Blum M;Bork P;Bridge A;Brown SD;Chang HY;El-Gebali S;Fraser MI;Gough J;Haft DR;Huang H;Letunic I;Lopez R;Luciani A;Madeira F;Marchler-Bauer A;Mi H;Natale DA;Necci M;Nuka G;Orengo C;Pandurangan AP;Paysan-Lafosse T;Pesseat S;Potter SC;Qureshi MA;Rawlings ND;Redaschi N;Richardson LJ;Rivoire C;Salazar GA;Sangrador-Vegas A;Sigrist CJA;Sillitoe I;Sutton GG;Thanki N;Thomas PD;Tosatto SCE;Yong SY;Finn RD
• 通讯作者: Finn RD