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Classification of domains in predicted structures of the human proteome
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 c...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10041065/ https://www.ncbi.nlm.nih.gov/pubmed/36917664 http://dx.doi.org/10.1073/pnas.2214069120 |
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author | Schaeffer, R. Dustin Zhang, Jing Kinch, Lisa N. Pei, Jimin Cong, Qian Grishin, Nick V. |
author_facet | Schaeffer, R. Dustin Zhang, Jing Kinch, Lisa N. Pei, Jimin Cong, Qian Grishin, Nick V. |
author_sort | Schaeffer, R. Dustin |
collection | PubMed |
description | 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). |
format | Online Article Text |
id | pubmed-10041065 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-100410652023-09-14 Classification of domains in predicted structures of the human proteome Schaeffer, R. Dustin Zhang, Jing Kinch, Lisa N. Pei, Jimin Cong, Qian Grishin, Nick V. Proc Natl Acad Sci U S A Biological Sciences 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). National Academy of Sciences 2023-03-14 2023-03-21 /pmc/articles/PMC10041065/ /pubmed/36917664 http://dx.doi.org/10.1073/pnas.2214069120 Text en Copyright © 2023 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Biological Sciences Schaeffer, R. Dustin Zhang, Jing Kinch, Lisa N. Pei, Jimin Cong, Qian Grishin, Nick V. Classification of domains in predicted structures of the human proteome |
title | Classification of domains in predicted structures of the human proteome |
title_full | Classification of domains in predicted structures of the human proteome |
title_fullStr | Classification of domains in predicted structures of the human proteome |
title_full_unstemmed | Classification of domains in predicted structures of the human proteome |
title_short | Classification of domains in predicted structures of the human proteome |
title_sort | classification of domains in predicted structures of the human proteome |
topic | Biological Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10041065/ https://www.ncbi.nlm.nih.gov/pubmed/36917664 http://dx.doi.org/10.1073/pnas.2214069120 |
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