About Me
Computational protein designer passionate about engineering therapeutic proteins through advanced molecular simulations
Professional Background
I am a computational protein designer with a PhD in computational biochemistry from Leiden University Medical Center (LUMC). My research focuses on rationally engineering protein variants with desired therapeutic properties, particularly in the field of coagulation factors.
As the sole computational scientist in a predominantly experimental group, I bridge the gap between computational modeling and experimental validation. I translate complex simulation results into actionable insights for clinicians and experimentalists, facilitating interdisciplinary collaboration.
My work has contributed to the development of inhibitor-resistant coagulation factor variants, with applications in bypassing direct oral anticoagulants for therapeutic purposes. I have extensive experience in molecular dynamics simulations, protein-ligand interaction analysis, and computational pipeline development.
Expertise & Skills
Computational Methods
- • Molecular Dynamics (AMBER, Desmond)
- • Structure Prediction (AlphaFold-Multimer)
- • Molecular Docking (HADDOCK, Schrödinger Glide)
- • Free Energy Calculations (MM/PBSA, MM/GBSA)
- • Enhanced Sampling Techniques
Programming & Tools
- • Python, R, Bash scripting
- • HPC cluster management (Slurm)
- • Data visualization (PyMol, VMD)
- • Statistical analysis (GraphPad Prism)
- • Machine Learning (XGBoost, Neural Networks)
Research Focus
My primary research interest lies in computational protein engineering, with a focus on:
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Protein-Ligand Interactions: Understanding and predicting binding modes of small molecules and natural inhibitors to therapeutic targets
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Rational Protein Design: Using computational insights to guide the design of protein variants with specific functional properties
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Computational Pipeline Development: Creating robust workflows for assessing protein function and guiding experimental validation
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Machine Learning Applications: Leveraging ML techniques for predictive modeling of protein properties
Looking Forward
I am actively seeking opportunities in Switzerland to contribute to cutting-edge research in computational protein design and therapeutic development. I am particularly interested in positions that combine computational modeling with experimental validation, allowing me to continue bridging the gap between theory and application.
My experience in interdisciplinary collaboration, combined with my expertise in both computational methods and understanding of experimental constraints, makes me well-suited for roles in pharmaceutical companies, biotech firms, or academic research institutions.