Projects

Computational protein design projects and research initiatives

Factor X Engineering

2021-2025

Goal: Rationally engineer catalytically active serine protease coagulation Factor X variants with reduced binding of small-molecule and natural inhibitors for therapeutic purposes.

Key Achievements:

  • • Developed computational pipeline for assessing enzymatic competence of engineered variants
  • • Identified interaction hotspots for inhibitor-resistant design
  • • Guided experimental validation of computationally designed variants
  • • Manuscript under revision at Journal of Chemical Information and Modeling
AlphaFold-Multimer AMBER MM/PBSA Python

Protein Abundance Prediction

2025

Roche PMDA Summer School 2025: Developed predictive models for protein abundance in mouse kidney tissue using curated multi-species datasets.

Approach:

  • • Performed exploratory data analysis revealing strong correlations between orthologs
  • • Trained multiple ML models (XGBoost, Neural Networks, Random Forest)
  • • Investigated sequence-based embeddings for improved predictions
  • • Outperformed baseline linear regression models
XGBoost Neural Networks Python R

Protein-Oligosaccharide Modeling

2021

Master's Thesis: Current modelling approaches to generate 3D structures of protein-oligosaccharide complexes.

Investigated computational methods for modeling complex carbohydrate-protein interactions, which are crucial for understanding biological recognition processes and designing therapeutics.

Molecular Modeling Structure Prediction

Factor Xa Variant Engineering

2019-2021

Minor Internship: Engineering Factor Xa variants with lower Apixaban binding affinity.

Early work in computational protein design, focusing on understanding and modifying protein-drug interactions through molecular modeling and free energy calculations.

Molecular Docking Free Energy

Collaborative Research

Throughout my research, I have maintained active collaborations with experimental groups at Vrije Universiteit Amsterdam and the University of Basel, bridging computational predictions with experimental validation.

My work has contributed to multiple peer-reviewed publications and has been presented at international conferences, including the International Society on Thrombosis & Haemostasis and the European Congress of Thrombosis and Haemostasis.