Classification of domains in predicted structures of the human proteome.
Classification of domains in predicted structures of the human proteome.
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DOI：
10.1073/pnas.2214069120
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发表时间：
2023-03-21
影响因子：
11.1
通讯作者：
V. Grishin, Nick
中科院分区：
文献类型：
--
作者：
Schaeffer, R. Dustin;Zhang, Jing;Kinch, Lisa N.;Pei, Jimin;Cong, Qian;V. Grishin, Nick
最近发表的整个人类蛋白质组的预测结构是一个里程碑式的成就。结合自动流水线和手动策展，我们从人类蛋白质组的预测结构中识别出47，576个球状结构域，并确定了它们与已知结构域的进化关系。这些领域中有四分之一在这些预测发布之前缺乏结构数据。对这些结构域和其中数千个致病的单个氨基酸变异的研究有望揭示蛋白质功能和疾病机制的见解，如本文讨论的示例所示。最后，与来自多个模式生物的自动分类域的比较揭示了与人类独特生理学相关的差异，例如细胞因子的扩增和气味传感域的耗尽。蛋白质结构预测的最新进展已经产生了以前未表征的人类蛋白质的准确结构。识别这些预测结构中的结构域并将其分类到进化层次中可以揭示生物学见解。在这里，我们描述了从人类蛋白质组域的检测和分类。我们的分类表明，只有62%的残基位于球状域。我们进一步对这些球状结构域进行分类，并观察到大多数（65%）可以通过序列在已知折叠中进行分类，较小部分（33%）需要结构数据来细化结构域边界和/或支持其同源性。相对较少的域名（966个域名）无法使用我们的自动管道进行可靠的分配，因此需要人工检查。我们对47,576个结构域进行了分类，其中只有23%的结构域被纳入了实验结构。这些分类的球状结构域的一部分（6.3%）缺乏InterPro中基于序列的注释。四分之一（23%）的基因没有通过同源性进行结构建模，它们包含2,540个已知的致病单氨基酸变异，其发病机制现在可以使用AF模型来推断。从一系列模式生物的分类域的比较显示，在人类中的几个免疫反应相关的域的扩展和嗅觉受体的消耗。最后，我们使用这种分类来扩展具有生物学意义的已知蛋白质家族。这些分类载于经合组织发展司网站（http：//prodata.swmed.edu/ecod/index_human.php）。
The recent publication of predicted structures of the entire human proteome was a landmark achievement. Combining automatic pipelines and manual curation, we identified 47,576 globular domains from predicted structures of the human proteome and determined their evolutionary relationships to known domains. A quarter of these domains lacked structural data before the release of these predictions. Investigation into these domains and the thousands of disease-causing single amino acid variations within them is expected to reveal insights into protein function and disease mechanisms, as illustrated by examples discussed here. Finally, comparison with automatically classified domains from multiple model organisms revealed differences associated with the unique physiology of humans, such as expansion in cytokines and depletion of odor-sensing domains. Recent advances in protein structure prediction have generated accurate structures of previously uncharacterized human proteins. Identifying domains in these predicted structures and classifying them into an evolutionary hierarchy can reveal biological insights. Here, we describe the detection and classification of domains from the human proteome. Our classification indicates that only 62% of residues are located in globular domains. We further classify these globular domains and observe that the majority (65%) can be classified among known folds by sequence, with a smaller fraction (33%) requiring structural data to refine the domain boundaries and/or to support their homology. A relatively small number (966 domains) cannot be confidently assigned using our automatic pipelines, thus demanding manual inspection. We classify 47,576 domains, of which only 23% have been included in experimental structures. A portion (6.3%) of these classified globular domains lack sequence-based annotation in InterPro. A quarter (23%) have not been structurally modeled by homology, and they contain 2,540 known disease-causing single amino acid variations whose pathogenesis can now be inferred using AF models. A comparison of classified domains from a series of model organisms revealed expansions of several immune response-related domains in humans and a depletion of olfactory receptors. Finally, we use this classification to expand well-known protein families of biological significance. These classifications are presented on the ECOD website (http://prodata.swmed.edu/ecod/index_human.php).
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影响因子：
14.9
作者：
Kooistra AJ;Mordalski S;Pándy-Szekeres G;Esguerra M;Mamyrbekov A;Munk C;Keserű GM;Gloriam DE
通讯作者：
Gloriam DE
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
影响因子：
64.8
作者：
Jumper J;Evans R;Pritzel A;Green T;Figurnov M;Ronneberger O;Tunyasuvunakool K;Bates R;Žídek A;Potapenko A;Bridgland A;Meyer C;Kohl SAA;Ballard AJ;Cowie A;Romera-Paredes B;Nikolov S;Jain R;Adler J;Back T;Petersen S;Reiman D;Clancy E;Zielinski M;Steinegger M;Pacholska M;Berghammer T;Bodenstein S;Silver D;Vinyals O;Senior AW;Kavukcuoglu K;Kohli P;Hassabis D
通讯作者：
Hassabis D
Pfam：氏族、网络工具和服务。
影响因子：
14.9
作者：
Finn, Robert D.;Mistry, Jaina;Schuster-Bockler, Benjamin;Griffiths-Jones, Sam;Hollich, Volker;Lassmann, Timo;Moxon, Simon;Marshall, Mhairi;Khanna, Ajay;Durbin, Richard;Eddy, Sean R.;Sonnhammer, Erik L. L.;Bateman, Alex
通讯作者：
Bateman, Alex
影响因子：
11.8
作者：
Leikina E;Gamage DG;Prasad V;Goykhberg J;Crowe M;Diao J;Kozlov MM;Chernomordik LV;Millay DP
通讯作者：
Millay DP