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iPCD: A Comprehensive Data Resource of Regulatory Proteins in Programmed Cell Death

Programmed cell death (PCD) is an essential biological process involved in many human pathologies. According to the continuous discovery of new PCD forms, a large number of proteins have been found to regulate PCD. Notably, post-translational modifications play critical roles in PCD process and the...

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Autores principales: Tang, Dachao, Han, Cheng, Lin, Shaofeng, Tan, Xiaodan, Zhang, Weizhi, Peng, Di, Wang, Chenwei, Xue, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9265749/
https://www.ncbi.nlm.nih.gov/pubmed/35805101
http://dx.doi.org/10.3390/cells11132018
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author Tang, Dachao
Han, Cheng
Lin, Shaofeng
Tan, Xiaodan
Zhang, Weizhi
Peng, Di
Wang, Chenwei
Xue, Yu
author_facet Tang, Dachao
Han, Cheng
Lin, Shaofeng
Tan, Xiaodan
Zhang, Weizhi
Peng, Di
Wang, Chenwei
Xue, Yu
author_sort Tang, Dachao
collection PubMed
description Programmed cell death (PCD) is an essential biological process involved in many human pathologies. According to the continuous discovery of new PCD forms, a large number of proteins have been found to regulate PCD. Notably, post-translational modifications play critical roles in PCD process and the rapid advances in proteomics have facilitated the discovery of new PCD proteins. However, an integrative resource has yet to be established for maintaining these regulatory proteins. Here, we briefly summarize the mainstream PCD forms, as well as the current progress in the development of public databases to collect, curate and annotate PCD proteins. Further, we developed a comprehensive database, with integrated annotations for programmed cell death (iPCD), which contained 1,091,014 regulatory proteins involved in 30 PCD forms across 562 eukaryotic species. From the scientific literature, we manually collected 6493 experimentally identified PCD proteins, and an orthologous search was then conducted to computationally identify more potential PCD proteins. Additionally, we provided an in-depth annotation of PCD proteins in eight model organisms, by integrating the knowledge from 102 additional resources that covered 16 aspects, including post-translational modification, protein expression/proteomics, genetic variation and mutation, functional annotation, structural annotation, physicochemical property, functional domain, disease-associated information, protein–protein interaction, drug–target relation, orthologous information, biological pathway, transcriptional regulator, mRNA expression, subcellular localization and DNA and RNA element. With a data volume of 125 GB, we anticipate that iPCD can serve as a highly useful resource for further analysis of PCD in eukaryotes.
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spelling pubmed-92657492022-07-09 iPCD: A Comprehensive Data Resource of Regulatory Proteins in Programmed Cell Death Tang, Dachao Han, Cheng Lin, Shaofeng Tan, Xiaodan Zhang, Weizhi Peng, Di Wang, Chenwei Xue, Yu Cells Article Programmed cell death (PCD) is an essential biological process involved in many human pathologies. According to the continuous discovery of new PCD forms, a large number of proteins have been found to regulate PCD. Notably, post-translational modifications play critical roles in PCD process and the rapid advances in proteomics have facilitated the discovery of new PCD proteins. However, an integrative resource has yet to be established for maintaining these regulatory proteins. Here, we briefly summarize the mainstream PCD forms, as well as the current progress in the development of public databases to collect, curate and annotate PCD proteins. Further, we developed a comprehensive database, with integrated annotations for programmed cell death (iPCD), which contained 1,091,014 regulatory proteins involved in 30 PCD forms across 562 eukaryotic species. From the scientific literature, we manually collected 6493 experimentally identified PCD proteins, and an orthologous search was then conducted to computationally identify more potential PCD proteins. Additionally, we provided an in-depth annotation of PCD proteins in eight model organisms, by integrating the knowledge from 102 additional resources that covered 16 aspects, including post-translational modification, protein expression/proteomics, genetic variation and mutation, functional annotation, structural annotation, physicochemical property, functional domain, disease-associated information, protein–protein interaction, drug–target relation, orthologous information, biological pathway, transcriptional regulator, mRNA expression, subcellular localization and DNA and RNA element. With a data volume of 125 GB, we anticipate that iPCD can serve as a highly useful resource for further analysis of PCD in eukaryotes. MDPI 2022-06-24 /pmc/articles/PMC9265749/ /pubmed/35805101 http://dx.doi.org/10.3390/cells11132018 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Tang, Dachao
Han, Cheng
Lin, Shaofeng
Tan, Xiaodan
Zhang, Weizhi
Peng, Di
Wang, Chenwei
Xue, Yu
iPCD: A Comprehensive Data Resource of Regulatory Proteins in Programmed Cell Death
title iPCD: A Comprehensive Data Resource of Regulatory Proteins in Programmed Cell Death
title_full iPCD: A Comprehensive Data Resource of Regulatory Proteins in Programmed Cell Death
title_fullStr iPCD: A Comprehensive Data Resource of Regulatory Proteins in Programmed Cell Death
title_full_unstemmed iPCD: A Comprehensive Data Resource of Regulatory Proteins in Programmed Cell Death
title_short iPCD: A Comprehensive Data Resource of Regulatory Proteins in Programmed Cell Death
title_sort ipcd: a comprehensive data resource of regulatory proteins in programmed cell death
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9265749/
https://www.ncbi.nlm.nih.gov/pubmed/35805101
http://dx.doi.org/10.3390/cells11132018
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