Journal club

Journal club meetings are on Mondays at 2-3 pm through video conference.

November 11, 2022
Peptide-RNA Coacervates as a Cradle for the Evolution of Folded Domains.

Seal, M., et al. (2022) JACS 144(31), 14150–14160. https://doi.org/10.1021/jacs.2c03819

Abstract PDF | SI

presented by Gilberto

September 23, 2022
Improved predictions of phase behaviour of intrinsically disordered proteins by tuning the interaction range

Tesei, G., & Lindorff-Larsen, K. (2022). Open Research Europe2, 94. https://doi.org/10.12688/openreseurope.14967.1

Abstract PDF | SI

presented by Gilberto

August 10, 2022
RNA modulation of transport properties and stability in phase-separated condensates

Tejedor, A. R., et al (2021) Biophysical Journal120(23), 5169–5186 https://doi.org/10.1016/j.bpj.2021.11.003

Abstract PDF | SI

presented by Gilberto

June 27, 2022
Tuning Formation of Protein–DNA Coacervates by Sequence and Environment

 

Lebold, K. M., & Best, R. B. (2022). JPC B126(12), 2407–2419. https://doi.org/10.1021/acs.jpcb.2c00424

Abstract PDF | SI

presented by Gilberto

May 18, 2022
RNA chain length and stoichiometry govern surface tension and stability of protein-RNA condensates

Laghmach, R., et al. (2022). IScience25(4), 104105. https://doi.org/10.1016/j.isci.2022.104105

Abstract PDF | SI

presented by Gilberto

March 9, 2022
Learning the molecular grammar of protein condensates from sequence determinants and embeddings

Saar, K. L., et al. (2021) PNAS, 118(15). https://doi.org/10.1073/pnas.2019053118

Abstract PDF | SI

presented by Gilberto

February 23, 2022
Engineering the protein dynamics of an ancestral luciferase

Schenkmayerova, A., Pinto, G.P., Toul, M. et al. Engineering the protein dynamics of an ancestral luciferase. Nat Commun 12, 3616 (2021). https://doi-org.proxy1.cl.msu.edu/10.1038/s41467-021-23450-z

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presented by Lim

February 9, 2022
Deciphering how naturally occurring sequence features impact the phase behaviours of disordered prion-like domains

Bremer, A., et al. (2022). Nature Chemistry14(2), 196–207. https://doi.org/10.1038/s41557-021-00840-w

Abstract PDF | SI

presented by Gilberto

January 12, 2022
RNA length has a non-trivial effect in the stability of biomolecular condensates formed by RNA-binding proteins

Sanchez-burgos, I., Espinosa, J. R., & Joseph, J. A. (2021). https://www.biorxiv.org/content/10.1101/2021.10.07.463486v1

Abstract PDF

presented by Gilberto

November 3, 2021
A Data-Driven Hydrophobicity Scale for Predicting Liquid–Liquid Phase Separation of Proteins.

Dannenhoffer-Lafage, T., & Best, R. B. (2021). JPC B125(16), 4046–4056. https://doi.org/10.1021/acs.jpcb.0c11479

Abstract PDF | SI

presented by Gilberto

September 15, 2021
Geometric deep learning of RNA structure

Townshend, R. J. L.;  Eismann, S.;  Watkins, A. M.;  Rangan, R.;  Karelina, M.;  Das, R.; Dror, R. O., Geometric deep learning of RNA structure. Science 2021, 373 (6558), 1047-1051.

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presented by Lim

August 25, 2021
Comparative roles of charge, π , and hydrophobic interactions in sequence-dependent phase separation of intrinsically disordered proteins.

Das, S., Lin, Y.-H., Vernon, R. M., Forman-Kay, J. D., & Chan, H. S. (2020) PNAS117(46), 28795–28805. https://doi.org/10.1073/pnas.2008122117

Abstract PDF | SI

presented by Gilberto

July 21, 2021
Highly accurate protein structure prediction with AlphaFold

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, S. A. A.;  Ballard, A. J.;  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, A. W.;  Kavukcuoglu, K.;  Kohli, P.; Hassabis, D., Highly accurate protein structure prediction with AlphaFold. Nature 2021.

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presented by Lim

July 7, 2021
A Generative Model for Molecular Distance Geometry

Simm and Hernández-Lobato (2020) Proceedings of the 37th International Conference on Machine Learning

Abstract | PDF

Presented by Giacomo

June 23, 2021
Thermodynamics and kinetics of phase separation of protein-RNA mixtures by a minimal model

Joseph, J. A., Espinosa, J. R., Sanchez-Burgos, I., Garaizar, A., Frenkel, D., & Collepardo-Guevara, R. (2021). Biophysical Journal120(7), 1219–1230. https://doi.org/10.1016/j.bpj.2021.01.031

Abstract PDF

presented by Gilberto

June 9, 2021
Learning from Protein Structure with Geometric Vector Perceptrons

Jing et al. (2021) Ninth International Conference on Learning Representations

Abstract | PDF

Presented by Giacomo

May 19, 2021
Arginine multivalency stabilizes protein/RNA condensates

Paloni, M., Bussi, G., & Barducci, A. (2021). Protein Science, pro.4109. https://doi.org/10.1002/pro.4109

Abstract PDF

presented by Gilberto

May 12, 2021
Efficient sampling of high-dimensional free energy landscapes using adaptive reinforced dynamics

Wang D, Zhang L, Wang H, E W. arXiv. 2021.

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presented by Lim

May 5, 2021
Differentiable molecular simulation can learn all the parameters in a coarse-grained force field for proteins

Greener and Jones, (2021) bioRxiv

Abstract | PDF

Presented by Giacomo

April 28, 2021
Sequence-encoded and composition-dependent protein-RNA interactions control multiphasic condensate morphologies

Kaur, T., Raju, M., Alshareedah, I. et al. Nat Commun 12, 872 (2021). https://doi.org/10.1038/s41467-021-21089-4

Abstract PDF | SI

presented by Gilberto