CD-CODE: crowdsourcing condensate database and encyclopedia.
Journal
Nature methods
ISSN: 1548-7105
Titre abrégé: Nat Methods
Pays: United States
ID NLM: 101215604
Informations de publication
Date de publication:
05 2023
05 2023
Historique:
received:
13
07
2022
accepted:
27
02
2023
medline:
12
5
2023
pubmed:
7
4
2023
entrez:
6
4
2023
Statut:
ppublish
Résumé
The discovery of biomolecular condensates transformed our understanding of intracellular compartmentalization of molecules. To integrate interdisciplinary scientific knowledge about the function and composition of biomolecular condensates, we developed the crowdsourcing condensate database and encyclopedia ( cd-code.org ). CD-CODE is a community-editable platform, which includes a database of biomolecular condensates based on the literature, an encyclopedia of relevant scientific terms and a crowdsourcing web application. Our platform will accelerate the discovery and validation of biomolecular condensates, and facilitate efforts to understand their role in disease and as therapeutic targets.
Identifiants
pubmed: 37024650
doi: 10.1038/s41592-023-01831-0
pii: 10.1038/s41592-023-01831-0
pmc: PMC10172118
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
673-676Informations de copyright
© 2023. The Author(s).
Références
Banani, S. F., Lee, H. O., Hyman, A. A. & Rosen, M. K. Biomolecular condensates: organizers of cellular biochemistry. Nat. Rev. Mol. Cell Biol. 18, 285–298 (2017).
doi: 10.1038/nrm.2017.7
pubmed: 28225081
pmcid: 7434221
Alberti, S. & Dormann, D. Liquid-liquid phase separation in disease. Annu. Rev. Genet. 53, 171–194 (2019).
doi: 10.1146/annurev-genet-112618-043527
pubmed: 31430179
Mitrea, D. M., Mittasch, M., Gomes, B. F., Klein, I. A. & Murcko, M. A. Modulating biomolecular condensates: a novel approach to drug discovery. Nat. Rev. Drug Discov. 21, 841–862 (2022).
doi: 10.1038/s41573-022-00505-4
pubmed: 35974095
pmcid: 9380678
Conti, B. A. & Oppikofer, M. Biomolecular condensates: new opportunities for drug discovery and RNA therapeutics. Trends Pharmacol. Sci. 43, 820–837 (2022).
doi: 10.1016/j.tips.2022.07.001
pubmed: 36028355
Ning, W. et al. DrLLPS: a data resource of liquid-liquid phase separation in eukaryotes. Nucleic Acids Res. 48, D288–D295 (2020).
doi: 10.1093/nar/gkz1027
pubmed: 31691822
Mészáros, B. et al. PhaSePro: the database of proteins driving liquid-liquid phase separation. Nucleic Acids Res. 48, D360–D367 (2020).
pubmed: 31612960
Li, Q. et al. LLPSDB: a database of proteins undergoing liquid-liquid phase separation in vitro. Nucleic Acids Res. 48, D320–D327 (2020).
doi: 10.1093/nar/gkz778
pubmed: 31906602
You, K. et al. PhaSepDB: a database of liquid-liquid phase separation related proteins. Nucleic Acids Res. 48, D354–D359 (2020).
doi: 10.1093/nar/gkz847
pubmed: 31584089
UniProt Consortium. UniProt: the universal protein knowledgebase in 2021. Nucleic Acids Res. 49, D480–D489 (2021).
doi: 10.1093/nar/gkaa1100
Cunningham, F. et al. Ensembl 2022. Nucleic Acids Res. 50, D988–D995 (2022).
doi: 10.1093/nar/gkab1049
pubmed: 34791404
Thul, P. J. et al. A subcellular map of the human proteome. Science 356, eaal3321 (2017).
doi: 10.1126/science.aal3321
pubmed: 28495876
Mészáros, B., Erdos, G. & Dosztányi, Z. IUPred2A: context-dependent prediction of protein disorder as a function of redox state and protein binding. Nucleic Acids Res. 46, W329–W337 (2018).
doi: 10.1093/nar/gky384
pubmed: 29860432
pmcid: 6030935
Saar, K. L. et al. Learning the molecular grammar of protein condensates from sequence determinants and embeddings. Proc. Natl Acad. Sci. USA 118, e2019053118 (2021).
doi: 10.1073/pnas.2019053118
pubmed: 33827920
pmcid: 8053968
van Mierlo, G. et al. Predicting protein condensate formation using machine learning. Cell Rep. 34, 108705 (2021).
doi: 10.1016/j.celrep.2021.108705
pubmed: 33535034
Hardenberg, M., Horvath, A., Ambrus, V., Fuxreiter, M. & Vendruscolo, M. Widespread occurrence of the droplet state of proteins in the human proteome. Proc. Natl Acad. Sci. USA 117, 33254–33262 (2021).
doi: 10.1073/pnas.2007670117
Hatos, A., Tosatto, S. C. E., Vendruscolo, M. & Fuxreiter, M. FuzDrop on AlphaFold: visualizing the sequence-dependent propensity of liquid-liquid phase separation and aggregation of proteins. Nucleic Acids Res. 50, W337–W344 (2022).
doi: 10.1093/nar/gkac386
pubmed: 35610022
pmcid: 9252777
Chen, Z. et al. Screening membraneless organelle participants with machine-learning models that integrate multimodal features. Proc. Natl Acad. Sci. USA 119, e2115369119 (2022).
doi: 10.1073/pnas.2115369119
pubmed: 35687670
pmcid: 9214545
Kumar, S. et al. TimeTree 5: an expanded resource for species divergence times. Mol. Biol. Evol. 39, msac174 (2022).
doi: 10.1093/molbev/msac174
pubmed: 35932227
pmcid: 9400175