Desktop: ENP.19.N507
Simon Dürr studied Life Science at the University of Konstanz with stays at Université de Montreal, Kings College London, Uppsala University and EPFL.
He completed his PhD at EPFL and Stanford University working on design of novel metalloproteins using deep learning, evolutionary algorithms, and molecular modelling. He has published state of the art deep learning models for modelling metal cofactors in proteins and used these algorithms to design novel metalloproteins. He has also published various articles about computational modelling of proteins using classical methods (e.g. molecular dynamics simulations) and high-level quantum mechanical molecular mechanical (QM/MM) simulations to study ligand binding, tunnel formation and enzymatic catalysis.
He collaborates with the startups HuggingFace and AdaptyvBio on machine learning for proteins. He built popular FAIR web applications for some of the workhorse models of modern protein design such as ProteinMPNN. To further the cause of FAIR scientific software he developed several open source packages such as a set of open components for visualization of proteins and small molecules for the Gradio framework.
Simon Dürr also runs the largest open platform of open and FAIR scientific illustrations: bioicons.com.
Simon Dürr’s current research interests include:
More information on simonduerr.eu
Ongoing
Role: Co-applicant
Description du projet :
Lonza ABL Project
Research team within HES-SO: Duerr Simon , Rüdt Matthias
State : Ongoing
2026
Gina El Nesr, Duerr Simon, Irimpan I. Mathews, Qi Wen, Kewei Zhao, Ritimukta Sarangi, Ursula Rothlisberger, Fanny Sunden, Po-Ssu Huang
BioRxiv, 2026
Link to the publication
2023
Duerr Simon, Andrea Levy, Ursula Rothlisberger
Nature Communications, 2023
Achievements
2026 ; Webapp
Collaborateurs: Duerr Simon
Link to the achievement
Gradio Apps for Protein Design
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