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Drug Discovery and Molecular Design with Artificial Intelligence

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"Our drug discovery approach amalgamates a learning machine intelligence with the synthesis of pharmacologically relevant chemical matter."

 

Atz, K. et al. (2024) Prospective deep interactome learning for de novo drug design. external page Nat. Commun. 15, 3408.

Schneider, P. et al. (2020) Rethinking drug design in the artificial intelligence era. external page Nature Reviews Drug Discovery 19, 353–364.

Schneider, G. (2019) Mind and machine in drug design. external page Nature Machine Intelligence 1, 128-130.

Schneider, G. (2018) Automating drug discovery. external page Nature Reviews Drug Discovery 2, 97–113.

There are currently no open PhD or Post-Doc positions in the CADD group.

MODLAB in the News

Read the latest article with Prof Schneider here :
AI designs new drugs based on protein structures

The accompanying publication can be found here:

Atz, K., Cotos Muñoz, L., Isert, C., Håkansson, M., Focht, D., Hilleke, M., Nippa, D. F., Iff, M., Ledergerber, J., Schiebroek, C. C. G., Romeo, V., Hiss, J. A., Merk, D., Schneider, P., Kuhn, B., Grether, U. & Schneider, G. (2024) Prospective deep interactome learning for de novo drug design. external page Nat. Commun. 15, 3408.

 

Check out this interview with Prof. Dr. Gisbert Schneider external page ChemistryViews.

 

Read the latest comment by Prof. Gisbert Schneider and Dr. Kenneth Atz  on "Artificial intelligence finds ways to develop new drugs" here.

Reference: Nippa DF, Atz K, Hohler R, Müller AT, Marx A, Bartelmus C, Wuitschik G, Marzuoli I, Jost V, Wolfard J, Binder M, Stepan AF, Konrad DB, Grether U, Martin RE, Schneider G: Enabling Late-Stage Drug Diversification by High-Throughput Experimentation with Geometric Deep Learning. Nature Chemistry, November 23, 2023. doi external page 10.1038/s41557-023-01360-5external page