논문 리뷰/Protein

[Archive] Condensates and phase separation

Cho et al. 2023. 4. 10.
새롭게 읽어보는 분야인 Protein Condensates, Liquid Phase separation 에 대한 논문들.

먼저 1차적으로 저번 주에 Nature method 에 나온 Condensate DB 논문의 Reference 부터 시작.

CD-CODE: crowdsourcing condensate database and encyclopedia

 

  • 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).
  • Alberti, S. & Dormann, D. Liquid-liquid phase separation in disease. Annu. Rev. Genet. 53, 171–194 (2019).
  • 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).
  • Conti, B. A. & Oppikofer, M. Biomolecular condensates: new opportunities for drug discovery and RNA therapeutics. Trends Pharmacol. Sci. 43, 820–837 (2022).
  • Ning, W. et al. DrLLPS: a data resource of liquid-liquid phase separation in eukaryotes. Nucleic Acids Res. 48, D288–D295 (2020).
  • Mészáros, B. et al. PhaSePro: the database of proteins driving liquid-liquid phase separation. Nucleic Acids Res. 48, D360–D367 (2020).
  • Li, Q. et al. LLPSDB: a database of proteins undergoing liquid-liquid phase separation in vitro. Nucleic Acids Res. 48, D320–D327 (2020).
  • You, K. et al. PhaSepDB: a database of liquid-liquid phase separation related proteins. Nucleic Acids Res. 48, D354–D359 (2020).
  • UniProt Consortium. UniProt: the universal protein knowledgebase in 2021. Nucleic Acids Res. 49, D480–D489 (2021).
  • Cunningham, F. et al. Ensembl 2022. Nucleic Acids Res. 50, D988–D995 (2022).
  • Thul, P. J. et al. A subcellular map of the human proteome. Science 356, eaal3321 (2017).
  • 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).
  • 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).
  • van Mierlo, G. et al. Predicting protein condensate formation using machine learning. Cell Rep. 34, 108705 (2021).
  • 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).
  • 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).
  • Chen, Z. et al. Screening membraneless organelle participants with machine-learning models that integrate multimodal features. Proc. Natl Acad. Sci. USA 119, e2115369119 (2022).
  • Kumar, S. et al. TimeTree 5: an expanded resource for species divergence times. Mol. Biol. Evol. 39, msac174 (2022).

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