publications
2023
- Implicit Transfer Operator Learning: Multiple Time-Resolution Surrogates for Molecular DynamicsSchreiner, Mathias, Winther, Ole, and Olsson, Simon2023
- A community effort to discover small molecule SARS-CoV-2 inhibitorsSchimunek, Johannes, Seidl, Philipp, Elez, Katarina, Hempel, Tim, Le, Tuan, Noé, Frank, Olsson, Simon, Raich, Lluı́s, Winter, Robin, Gokcan, Hatice, Gusev, Filipp, Gutkin, Evgeny M., Isayev, Olexandr, Kurnikova, Maria G., Narangoda, Chamali H., Zubatyuk, Roman, Bosko, Ivan P., Furs, Konstantin V., Karpenko, Anna D., Kornoushenko, Yury V., Shuldau, Mikita, Yushkevich, Artsemi, Benabderrahmane, Mohammed B., Bousquet-Melou, Patrick, Bureau, Ronan, Charton, Beatrice, Cirou, Bertrand C., Gil, Gérard, Allen, William J., Sirimulla, Suman, Watowich, Stanley, Antonopoulos, Nick A., Epitropakis, Nikolaos E., Krasoulis, Agamemnon K., Pitsikalis, Vassilis P., Theodorakis, Stavros T., Kozlovskii, Igor, Maliutin, Anton, Medvedev, Alexander, Popov, Petr, Zaretckii, Mark, Eghbal-zadeh, Hamid, Halmich, Christina, Hochreiter, Sepp, Mayr, Andreas, Ruch, Peter, Widrich, Michael, Berenger, Francois, Kumar, Ashutosh, Yamanishi, Yoshihiro, Zhang, Kam Y.J., Bengio, Emmanuel, Bengio, Yoshua, Jain, Moksh J., Korablyov, Maksym, Liu, Cheng-Hao, Marcou, Gilles, Glaab, Enrico, Barnsley, Kelly, Iyengar, Suhasini M., Ondrechen, Mary Jo, Haupt, V. Joachim, Kaiser, Florian, Schroeder, Michael, Pugliese, Luisa, Albani, Simone, Athanasiou, Christina, Beccari, Andrea, Carloni, Paolo, D’Arrigo, Giulia, Gianquinto, Eleonora, Goßen, Jonas, Hanke, Anton, Joseph, Benjamin P., Kokh, Daria B., Kovachka, Sandra, Manelfi, Candida, Mukherjee, Goutam, Muñiz-Chicharro, Abraham, Musiani, Francesco, Nunes-Alves, Ariane, Paiardi, Giulia, Rossetti, Giulia, Sadiq, S. Kashif, Spyrakis, Francesca, Talarico, Carmine, Tsengenes, Alexandros, Wade, Rebecca C., Copeland, Conner, Gaiser, Jeremiah, Olson, Daniel R., Roy, Amitava, Venkatraman, Vishwesh, Wheeler, Travis J., Arthanari, Haribabu, Blaschitz, Klara, Cespugli, Marco, Durmaz, Vedat, Fackeldey, Konstantin, Fischer, Patrick D., Gorgulla, Christoph, Gruber, Christian, Gruber, Karl, Hetmann, Michael, Kinney, Jamie E., Das, Krishna M. Padmanabha, Pandita, Shreya, Singh, Amit, Steinkellner, Georg, Tesseyre, Guilhem, Wagner, Gerhard, Wang, Zi-Fu, Yust, Ryan J., Druzhilovskiy, Dmitry S., Filimonov, Dmitry A., Pogodin, Pavel V., Poroikov, Vladimir, Rudik, Anastassia V., Stolbov, Leonid A., Veselovsky, Alexander V., Rosa, Maria De, Simone, Giada De, Gulotta, Maria R., Lombino, Jessica, Mekni, Nedra, Perricone, Ugo, Casini, Arturo, Embree, Amanda, Gordon, D. Benjamin, Lei, David, Pratt, Katelin, Voigt, Christopher A., Chen, Kuang-Yu, Jacob, Yves, Krischuns, Tim, Lafaye, Pierre, Zettor, Agnès, Rodrı́guez, M. Luis, White, Kris M., Fearon, Daren, Delft, Frank Von, Walsh, Martin A., Horvath, Dragos, III, Charles L. Brooks, Falsafi, Babak, Ford, Bryan, Garcı́a-Sastre, Adolfo, Lee, Sang Yup, Naffakh, Nadia, Varnek, Alexandre, Klambauer, Günter, and Hermans, Thomas M.2023
2022
- Markov field models: Scaling molecular kinetics approaches to large molecular machinesHempel, Tim, Olsson, Simon, and Noé, FrankCurrent Opinion in Structural Biology 2022
With recent advances in structural biology, including experimental techniques and deep learning-enabled high-precision structure predictions, molecular dynamics methods that scale up to large biomolecular systems are required. Current state-of-the-art approaches in molecular dynamics modeling focus on encoding global configurations of molecular systems as distinct states. This paradigm commands us to map out all possible structures and sample transitions between them, a task that becomes impossible for large-scale systems such as biomolecular complexes. To arrive at scalable molecular models, we suggest moving away from global state descriptions to a set of coupled models that each describe the dynamics of local domains or sites of the molecular system. We describe limitations in the current state-of-the-art global-state Markovian modeling approaches and then introduce Markov field models as an umbrella term that includes models from various scientific communities, including Independent Markov decomposition, Ising and Potts models, and (dynamic) graphical models, and evaluate their use for computational molecular biology. Finally, we give a few examples of early adoptions of these ideas for modeling molecular kinetics and thermodynamics.
- A litmus test for classifying recognition mechanisms of transiently binding proteinsChakrabarti, Kalyan S., Olsson, Simon, Pratihar, Supriya, Giller, Karin, Overkamp, Kerstin, Lee, Ko On, Gapsys, Vytautas, Ryu, Kyoung-Seok, Groot, Bert L., Noé, Frank, Becker, Stefan, Lee, Donghan, Weikl, Thomas R., and Griesinger, ChristianNature Communications 2022
2021
- A transferable Boltzmann generator for small-molecules conformers.Diez, Juan Viguera, Atance, Sara Romeo, Engkvist, Ola, Mercado, Rocı́o, and Olsson, SimonELLIS Machine Learning for Molecule Discovery Workshop (ML4Molecules) 2021 2021
- De novo drug design using reinforcement learning with graph-based deep generative modelsAtance, Sara Romeo, Diez, Juan Viguera, Engkvist, Ola, Olsson, Simon, and Mercado, Rocı́oReinforcement Learning for Real Life (RL4RealLife) Workshop in the 38 th International Conference on Machine Learning, 2021. 2021
- Camostat mesylate inhibits SARS-CoV-2 activation by TMPRSS2-related proteases and its metabolite GBPA exerts antiviral activityHoffmann, Markus, Hofmann-Winkler, Heike, Smith, Joan C., Krüger, Nadine, Arora, Prerna, Sørensen, Lambert K., Søgaard, Ole S., Hasselstrøm, Jørgen Bo, Winkler, Michael, Hempel, Tim, Raich, Lluı́s, Olsson, Simon, Danov, Olga, Jonigk, Danny, Yamazoe, Takashi, Yamatsuta, Katsura, Mizuno, Hirotaka, Ludwig, Stephan, Noé, Frank, Kjolby, Mads, Braun, Armin, Sheltzer, Jason M., and Pöhlmann, StefanEBioMedicine 2021
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2013
- PHAISTOS: A framework for Markov chain Monte Carlo simulation and inference of protein structureBoomsma, Wouter, Frellsen, Jes, Harder, Tim, Bottaro, Sandro, Johansson, Kristoffer E., Tian, Pengfei, Stovgaard, Kasper, Andreetta, Christian, Olsson, Simon, Valentin, Jan B., Antonov, Lubomir D., Christensen, Anders S., Borg, Mikael, Jensen, Jan H., Lindorff-Larsen, Kresten, Ferkinghoff-Borg, Jesper, and Hamelryck, ThomasJournal of Computational Chemistry 2013