Dr. GPCR Podcast

What if models didn’t just explain the past — but could truly predict what comes next?

In this episode, Dr. Jens Carlsson reveals how computational modeling is evolving from explanation to real prediction—and how that shift accelerates real-world discovery.

Dr. Jens Carlsson, Professor of Computational Biochemistry at Uppsala University, joins Dr. Yamina Berchiche to share his unconventional journey from aspiring engineer to GPCR modeler. With a deep focus on structure-based drug design, Jens discusses how his lab bridges simulation and experiment—and why understanding the limits of prediction is just as critical as the predictions themselves.

From virtual screening of billions of molecules to leveraging AlphaFold for structure prediction, Jens shares the cutting-edge tools his lab uses—and the collaborative mindset required to turn models into testable hypotheses. Along the way, he reflects on key career moments, the role of mentorship, and how curiosity continues to drive his work across both academic and industry settings.

Why This Matters

• Computational models are moving beyond interpretation into real-world prediction of ligand-receptor interactions.

• Bridging computation, chemistry, and pharmacology is key to speeding up drug discovery.

• AI and machine learning are opening new doors—but only if scientists know their tools’ limits.

What You’ll Learn

• Why Jens Carlsson believes modeling should predict, not just explain

• How his team uses structure-based modeling to identify novel GPCR ligands

• The value of failure—and how it shaped his path as a scientist

• Why collaborations between modelers and experimentalists are more vital than ever

• How AlphaFold is shaking up structural biology—and where it still falls short

• Advice for junior scientists: what really matters when building a research career

Who Should Listen

• GPCR scientists and pharmacologists

• Computational chemists and structural biologists

• Early-career researchers exploring drug discovery

• Biotech leaders and R&D strategists

• Anyone interested in predictive modeling, AI in biology, or structure-function relationships

About Jens Carlsson

Jens Carlsson is a Professor of Computational Biochemistry at Uppsala University, where his research group uses structure-based modeling to investigate GPCRs. His team focuses on understanding how ligands modulate receptor function and how those insights can drive drug discovery. By combining molecular docking, molecular dynamics, and machine learning, Jens works at the intersection of computation and pharmacology, often in close collaboration with experimental labs.

Trained initially as a biotechnology engineer, Jens discovered his true calling during an internship where his modeling skills stood out, mainly because his bench skills didn’t. That moment launched a career built around using computational tools to answer big biological questions. His journey took him from Sweden to Scripps Research and UCSF, where he was first introduced to GPCRs and mentored by pioneers like Brian Shoichet and Ken Jacobson.

Jens is passionate about prediction over explanation: building models that can guide experiments, not just interpret them. Outside academia, he advises companies through a consulting arm focused on ligand design strategy. With a reputation for collaborative science, Jens is a strong advocate for bringing together chemists, modelers, and biologists to accelerate discovery and train the next generation of GPCR researchers.

Jens Carlsson on the web

• Carlsson Group

• Uppsala University

• LinkedIn

Hit play now to hear how prediction is reshaping GPCR science, and what that means for the future of drug discovery.