In-person workshop, 18 March 2025 @ETH Zurich
About
Machine learning and data-driven approaches play an increasingly important role in enzyme design and engineering. These tools have the potential to drastically accelerate the development of bespoke biocatalysts, but numerous challenges remain. This workshop aims to bring together computer scientists and experimentalists to discuss recent advances as well as outstanding challenges in this emerging interdisciplinary field.
Goals of the Workshop:
- Foster collaboration among scientists in machine learning and biocatalysis.
- Share experiences and challenges from past projects.
- Discuss gaps in accuracy, throughput, directed information, and risk assessment.
- Develop a white paper documenting short-term challenges and actionable goals.
Key Topics to Address:
- Generalist tools like AlphaFold and ProteinMPNN.
- Specialized computational tools (e.g., molecular dynamics, docking).
- Defining search spaces for sequence and structure-based exploration.
- High-throughput experimental methods (e.g., microfluidics, automation).
- Measurement errors and assay reproducibility.
- Effective communication between wet-lab and dry-lab teams.
Speakers and Panelists
Confirmed speakers:
- Ditte Hededam Welner (DTU Biosustain)
- Silvia Osuna (University of Girona)
- Gustav Oberdorfer (TU Graz)
- Markus Jeschek (University of Regensburg/EPFL)
- Jürgen Pleiss (University of Stuttgart)
- Bettina Nestl (Innophore GmbH)
- Adrian Bunzel (ETH Zurich)
- Mattia Gollub (Jura Bio)
- Julian Englert (Adaptyv Bio)
Panel Discussion
A panel discussion will explore current challenges both from the experimental as well as the computational perspective. All workshop participants are invited to contribute to the discussion by asking questions or sharing their own experiences. Following the event, the discussion will be summarized in a white paper.
Poster Session
We invite poster contributions on topics including:
- De novo enzyme design
- Machine learning-assisted directed evolution
- Protein representation with ML
- Enzyme discovery and function prediction
- Molecular dynamics and docking
- High-throughput screening and automation
Location
ETH Zurich, Main Campus
HG F30 - Audi Max
Poster and Arrival Instructions
Date: 18 March 2025
Time: 9:30 AM - 7:00 PM
The workshop precedes the Mosbacher Kolloquium (19–22 March 2025 in Mosbach, Germany), which will also address the role of AI in biology.
Organizers
- Mojmir Mutny (ETH Zurich)
- Tobias Vornholt (University of Basel)
- Peter Stockinger (ZHAW)
- Rebecca Buller (ZHAW)
- Andreas Krause (ETH Zurich)
- Thomas Ward (University of Basel)
Sponsors
The National Centres of Competence in Research (NCCRs) are a funding scheme of the Swiss National Science Foundation.
Please reach out to us if you are interested in sponsoring the event!