Willem Jespers
Assistant Professor in Computer-Aided Drug Discovery, University of Groningen |
Founder & Chief Scientific Officer, MODSIM Pharma
Dr. Willem Jespers is Assistant Professor in Computer-Aided Drug Discovery at the University of Groningen and Founder & Chief Scientific Officer of MODSIM Pharma. His work focuses on the development and application of computational methods, molecular simulations and artificial intelligence to better understand drug-target interactions and support the discovery of new therapeutic strategies.
Willem obtained his MSc in Bio-Pharmaceutical Sciences cum laude from Leiden University and completed his PhD in Computational Chemistry at Uppsala University. He subsequently worked as a computational chemist at Galapagos and as Assistant Professor at the Leiden Academic Centre for Drug Research before joining the University of Groningen in 2025.
In his research, Willem combines physics-based modelling, machine learning, structural biology and pharmacology, with a particular focus on G protein-coupled receptors, G proteins and disease-associated mutations. He leads an interdisciplinary research group and supervises PhD students and postdoctoral researchers across national and international collaborations.
Alongside his academic work, Willem is actively involved in entrepreneurship, education and career development. Through his dual role in academia and biotech, he aims to bridge fundamental pharmaceutical research, computational innovation and real-world drug discovery.
Presentation: From Structural Insight to Therapeutic Design
Structure-based drug discovery has become a key enabler of innovation in modern pharmaceutical research, offering a rational framework for the design and optimization of new therapeutics. By revealing how drug molecules interact with their biological targets at the atomic level, structural insight provides a powerful foundation for informed decision-making throughout the discovery process. This session will highlight how both experimental and computational methods contribute to this effort, from structural biology techniques that uncover target architecture and ligand binding modes to in silico approaches that support modeling, prediction, and design. Together, these complementary strategies help guide medicinal chemistry, accelerate lead optimization, and improve the progression from target identification to high-quality drug candidates. By integrating experimental data with computational insight, structure-based drug discovery enables more efficient discovery pathways and ultimately supports the development of safer and more effective medicines.
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