moragroup
AI driven biochemistry
AITHYRA, Austria
Ariane Mora, PhD
amora@aithyra.at
https://moragroup.github.io/
Gabriela presenting her project and Luca brought a "Munich style" breakfast! 26.02.2026.
Who We Are
We are an interdisciplinary research group working at the interface of machine learning, synthetic biology, and enzyme engineering.
Our mission:
Build models that translate sequence → function, and use them to discover and design enzymes that matter.
We combine computational modeling with wet-lab experimentation, enabling a full loop from hypothesis → prediction → experiment → better models.
Lab culture is really important - we aim to be:
- Inclusive
- Collaborative
- Scientifically ambitious
- Supportive and fun
Research Focus
We develop machine learning methods for enzyme discovery and design, grounded in real experimental validation.
Our core idea:
If we can learn to map protein sequence directly to biochemical function, we can scale discovery to the billions of enzymes sampled from nature.
Why this matters:
- Enables discovery of distant functions across evolutionary scales
- Makes enzyme design scalable
- Supports antibiotic development and resistance mitigation
- Allows model-guided experimental exploration
Because we run both computational and experimental labs, we can:
- Generate missing training data
- Run lab-in-the-loop active learning
- Test high-impact questions directly
Example question we care about:
Can we design antibiotics that are both potent and less susceptible to resistance?
The Team
We currently have 5 local and 2 global members.
Ariane Mora
- Principal Investigator, AITHYRA, Austria (from 2025)
- Postdoc in enzyme engineering (wet + dry lab), California Institute of Technology (Caltech), USA – Frances Arnold Lab (2023–2025)
- PhD in Computational Biology, The University of Queensland, Australia (2019–2023)
- Background in Computer Engineering –> transitioned into computational biology
Postdocs
- Gabriela – Evolutionary biology; generating new antibiotic enzymes with DNA language models
Technician
- Manuel – Molecular biology; building our automated enzyme evaluation pipeline
PhD Students (Local)
- Luca – Biochemistry; contrastive learning for protein fitness prediction
- Sebastian – Chemistry; using DPO to identify improved catalysts
PhD Students (Remote)
- Will (Brisbane, Australia) – Flow matching for enzyme mechanisms
- Ikumi (Tokyo, Japan) – Biosensor design
Techniques & Tools
Experimental
- Enzyme screening (lysate & whole-cell systems)
- LC–MS
- HPLC
- Plate reader assays
- Automated evaluation pipelines
Machine Learning & Statistics
We use the method that best fits the biological question:
- Contrastive learning
- Direct Preference Optimization (DPO)
- Large Language Models (LLMs)
Collaborations
We actively collaborate across Europe and Australia:
- New-to-nature chemistry with the Reisenbauer Lab (ISTA, Austria)
- Peptide-based chemistry with the Nguyen Lab (EPFL, Switzerland)
- Causal inference for enzyme mechanisms with Dr. Loomba (Imperial College London, UK)
- Bioinformatics and evolutionary methods with the Boden Lab (University of Queensland, Australia)
And we’re always open to new collaborations 🙂
Fun and work things
The team with the robotics setup 20.02.2026.
Us attending LEAD DigiBiotech Symposium – Artificial Intelligence for Sustainable Bioengineering in Graz, Austria 24.02.2026.
Us attending AMLD in Laussane, Swizterland 12.02.2026.
Team Doing Cool Things
Gabriela was featured in Time Magazine for getting her recent USA-APART grant.
Scientists Are Leaving the US for Europe — and the Impact on Global Research — Time.com
Contact
For specific questions, feel free to reach out to:
- Will – w.rieger@uq.edu.au
- Gabriela – globinska@aithyra.at
- Sebastian – shaeussermann@aithyra.at
- Luca – lherrmann@aithyra.at
- Manuel – mmaluenda@aithyra.at
Or me directly:
Ariane Mora – amora@aithyra.at