Journal club

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

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

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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

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presented by Gilberto

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

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

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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

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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

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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

April 21, 2021
Predicting new protein conformations from molecular dynamics simulation conformational landscapes and machine learning

Yiming Jin, Linux O. Johannissen, Sam Hay: Prediction new protein conformations from molecular dynamics simulation conformational landscapes and machine learning. Proteins (2021)

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presented by Michael

April 21, 2021
MSA Transformer

Rao R, Liu J, Verkuil R, Meier J, Canny JF, Abbeel P, et al. MSA Transformer. bioRxiv. 2021.

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presented by Lim

April 14, 2021
Protein sequence design by conformational landscape optimization

Norn et al., (2021) PNAS

Abstract | PDF | SI

Presented by Giacomo

April 7, 2021
FtsZ-Induced shape transformation of coacervates

Fanalista, F., Deshpande, S., Lau, A., Pawlik, G., & Dekker, C. (2018). Advanced Biosystems2(9), 1800136. https://doi.org/10.1002/adbi.201800136

Abstract PDF | SI

presented by Gilberto

March 24, 2021
Mechanistic basis for ubiquitin modulation of a protein energy landscape

Carroll, E.C., Latorraca, N.R., Lindner, J.M., Maguire, B.C., Pelton, J.G., and Marqusee, S. Proc. Natl. Acad. Sci. U.S.A. (2021).

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presented by Lim

March 17, 2021
Discovery of a hidden transient state in all bromodomain families

Raich et al., (2021) PNAS

Abstract | PDF | SI

Presented by Giacomo

March 3, 2021
Spontaneous driving forces give rise to protein−RNA condensates with coexisting phases and complex material properties

Boeynaems, S., Holehouse, A. S., Weinhardt, V., et al. (2019). PNAS, 116(16), 7889–7898. https://doi.org/10.1073/pnas.1821038116

Abstract PDF | SI

presented by Gilberto

February 17, 2021
Extraction of protein dynamics information from cryo-EM maps using deep learning

Matsumoto et al., Nature Machine Intelligence (2021).

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presented by Lim

February 10, 2021
Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning

Gainza et al., (2020) Nature Methods

Abstract | PDF | SI

Presented by Giacomo

February 3, 2021
Lysine/RNA-interactions drive and regulate biomolecular condensation

Ukmar-Godec, T., Hutten, S., Grieshop, M.P. et al. Nat Commun 10, 2909 (2019) https://doi.org/10.1038/s41467-019-10792-y

Abstract PDF | SI

presented by Gilberto