Drug Discovery

J. Schimunek, P. Seidl, L. Friedrich, D. Kuhn, F. Rippmann, S. Hochreiter, and G. Klambauer (2023) Context-Enriched Molecule Representations Improve Few-Shot Drug Discovery. arXiv:2305.09481, 2023-04-24. (more) (download)

J. Schimunek, P. Seidl, K. Elez, T. Hempel, T. Le, F. Noé, S. Olsson, L. Raich, R. Winter, H. Gokcan, F. Gusev, E. M. Gutkin, O. Isayev, M. G. Kurnikova, C. H. Narangoda, R. Zubatyuk, I. P. Bosko, K. V. Furs, A. D. Karpenko, Y. V. Kornoushenko, M. Shuldau, A. Yushkevich, M. B. Benabderrahmane, P. Bousquet-Melou, R. Bureau, B. Charton, B. C. Cirou, G. Gil, W. J. Allen, S. Sirimulla, S. Watowich, N. A. Antonopoulos, N. E. Epitropakis, A. K. Krasoulis, V. P. Pitsikalis, S. T. Theodorakis, I. Kozlovskii, A. Maliutin, A. Medvedev, P. Popov, M. Zaretckii, H. Eghbal-zadeh, C. Halmich, S. Hochreiter, A. Mayr, P. Ruch, M. Widrich, F. Berenger, A. Kumar, Y. Yamanishi, K. YJ Zhang, E. Bengio, Y. Bengio, M. J. Jain, M. Korablyov, C.-H. Liu, G. Marcou, E. Glaab, K. Barnsley, S. M. Iyengar, M. Jo Ondrechen, V. J. Haupt, F. Kaiser, M. Schroeder, L. Pugliese, S. Albani, C. Athanasiou, A. Beccari, P. Carloni, G. D'Arrigo, E. Gianquinto, J. Goßen, A. Hanke, B. P. Joseph, D. B. Kokh, S. Kovachka, C. Manelfi, G. Mukherjee, A. Muñiz-Chicharro, F. Musiani, A. Nunes-Alves, G. Paiardi, G. Rossetti, S. K. Sadiq, F. Spyrakis, C. Talarico, A. Tsengenes, R. C. Wade, C. Copeland, J. Gaiser, D. R. Olson, A. Roy, V. Venkatraman, T. J. Wheeler, H. Arthanari, K. Blaschitz, M. Cespugli, V. Durmaz, K. Fackeldey, P. D. Fischer, C. Gorgulla, C. Gruber, K. Gruber, M. Hetmann, J. E. Kinney, K. M. P. Das, S. Pandita, A. Singh, G. Steinkellner, G. Tesseyre, G. Wagner, Z.-F. Wang, R. J. Yust, D. S. Druzhilovskiy, D. A. Filimonov, P. V. Pogodin, V. Poroikov, A. V. Rudik, L. A. Stolbov, A. V. Veselovsky, M. De Rosa, G. De Simone, M. R. Gulotta, J. Lombino, N. Mekni, U. Perricone, A. Casini, A. Embree, D. B. Gordon, D. Lei, K. Pratt, C. A. Voigt, K.-Y. Chen, Y. Jacob, T. Krischuns, P. Lafaye, A. Zettor, M. L. Rodríguez, K. M. White, D. Fearon, F. Von Delft, M. A. Walsh, D. Horvath, C. L. B. III, B. Falsafi, B. Ford, A. García-Sastre, S. Y. Lee, N. Naffakh, and A. Varnek (2023) A Community Effort to Discover Small Molecule SARS-CoV-2 Inhibitors. ChemRxiv, 2023-04-07. (more) (download)

P. Seidl, A. Vall, S. Hochreiter, and G. Klambauer (2023) Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language. arXiv:2303.03363, 2023-03-06. (more) (download)

P. A. Robert, R. Akbar, R. Frank, M. Pavlović, M. Widrich, I. Snapkov, A. Slabodkin, M. Chernigovskaya, L. Scheffer, E. Smorodina, P. Rawat, B. B. Mehta, M. Ha Vu, I. F. Mathisen, A. Prósz, K. Abram, A. Olar, E. Miho, D. T. T. Haug, F. Lund-Johansen, S. Hochreiter, I. H. Haff, G. Klambauer, G. K. Sandve, and V. Greiff (2022) Unconstrained Generation of Synthetic Antibody–Antigen Structures to Guide Machine Learning Methodology for Antibody Specificity Prediction. Nature Computational Science, 2, 12, 845-865, 2022-12-19. (more) (download)

A. Sanchez-Fernandez, E. Rumetshofer, S. Hochreiter, and G. Klambauer (2022) CLOOME: Contrastive Learning Unlocks Bioimaging Databases for Queries with Chemical Structures. bioRxiv 2022.11.17.516915, 2022-11-18. (more) (download)

A. Sanchez-Fernandez, E. Rumetshofer, S. Hochreiter, and G. Klambauer (2022) Contrastive Learning of Image- and Structure-based Representations in Drug Discovery. ICLR 2022 Machine Learning for Drug Discovery, 2022-04-29. (more) (download)

C. Shen, M. Krenn, S. Eppel, and A. Aspuru-Guzik (2021) Deep Molecular Dreaming: Inverse Machine Learning for De-novo Molecular Design and Interpretability with Surjective Representations. Machine Learning: Science and Technology, 2, 3, 03LT02, 2021-07-13. (more) (download)

P. A. Robert, R. Akbar, R. Frank, M. Pavlović, M. Widrich, I. Snapkov, M. Chernigovskaya, L. Scheffer, A. Slabodkin, B. B. Mehta, M. Ha Vu, A. Prósz, K. Abram, A. Olar, E. Miho, D. T. T. Haug, F. Lund-Johansen, S. Hochreiter, I. H. Haff, G. Klambauer, G. K. Sandve, and V. Greiff (2021) One Billion Synthetic 3D-Antibody-Antigen Complexes Enable Unconstrained Machine-Learning Formalized Investigation of Antibody Specificity Prediction. bioRxiv, 2021.07. 06.451258, 2021-07-11. (more) (download)

P. Seidl, P. Renz, N. Dyubankova, P. Neves, J. Verhoeven, J. K. Wegner, S. Hochreiter, and G. Klambauer (2021) Modern Hopfield Networks for Few- and Zero-Shot Reaction Prediction. arXiv:2104.03279, 2021-04-07. (more) (download)

P. Renz, D. Van Rompaey, J. K. Wegner, S. Hochreiter, and G. Klambauer (2020) On failure modes in molecule generation and optimization. Drug Discovery Today: Technologies, 32, 55-63, 2020-10-24. (more) (download)

N. Sturm, A. Mayr, T. Le Van, V. Chupakhin, H. Ceulemans, J. Wegner, J.-F. Golib-Dzib, N. Jeliazkova, Y. Vandriessche, S. Böhm, V. Cima, J. Martinovic, N. Greene, T. V. Aa, T. J. Ashby, S. Hochreiter, O. Engkvist, G. Klambauer, and H. Chen (2020) Industry-scale application and evaluation of deep learning for drug target prediction. Journal of Cheminformatics, 12, 1-13, 2020-04-19. (more) (download)

M. Hofmarcher, A. Mayr, E. Rumetshofer, P. Ruch, P. Renz, J. Schimunek, P. Seidl, A. Vall, M. Widrich, S. Hochreiter, and G. Klambauer (2020) Large-Scale Ligand-Based Virtual Screening for SARS-CoV-2 Inhibitors Using Deep Neural Networks. SSRN 3561442, 2020-03-23. (more) (download)

A. Mayr, G. Klambauer, T. Unterthiner, and S. Hochreiter (2020) The LSC Benchmark Dataset: Technical Appendix and Partial Reanalysis. 2020-02-12. (more) (download)

K. Preuer, G. Klambauer, F. Rippmann, S. Hochreiter, and T. Unterthiner (2019) Interpretable Deep Learning in Drug Discovery. in Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, Springer, 331, 2019-09-10; preprint at arXiv, 1903.02788v2. (more) (download)

M. P. Menden, D. Wang, M. J. Mason, B. Szalai, K. C. Bulusu, Y. Guan, T. Yu, J. Kang, M. Jeon, R. Wolfinger, T. Nguyen, M. Zaslavskiy, A.-S. D. C. D. Consortium, I. S. Jang, Z. Ghazoui, M. E. Ahsen, R. Vogel, E. C. Neto, T. Norman, E. K. Y. Tang, M. J. Garnett, G. Y. Di Veroli, S. Fawell, G. Stolovitzky, J. Guinney, J. R. Dry, and J. Saez-Rodriguez (2019) Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen. Nature Communications, 10, 2674, 2019-06-17. (more) (download)

G. Klambauer, S. Hochreiter, and M. Rarey (2019) Machine Learning in Drug Discovery. Journal of Chemical Information and Modeling , 59, 3, 945, 2019-03-25. (more) (download)

M. Hofmarcher, E. Rumetshofer, D.-A. Clevert, S. Hochreiter, and G. Klambauer (2019) Accurate prediction of biological assays with high-throughput microscopy images and convolutional networks. Journal of Chemical Information and Modeling, 59, 3, 1163, 2019-03-06. (more) (download)