Jürgen Claesen is back for the second part of our conversation. In Part 1 we covered mass spectrometry. This time we go a level up and look at the broader landscape of proteomics: what proteins do, how we predict their shape, and how that knowledge becomes medicine. We start with the basic chain from genome to transcriptome to proteome to metabolome. Then we ask why roughly 20,000 genes produce many times more proteins. From there we get into AlphaFold: what it predicts, why physics alone couldn’t crack protein folding, and how the field has moved on now that structure prediction is largely solved. The second half moves toward the clinic. We cover how drugs bind to proteins, how mRNA vaccines differ from traditional ones, the promise and risks of CRISPR (including off-target effects), and why every cell has the same DNA but does very different jobs. We also discuss why viruses like HIV are so hard to beat. We finish on an open problem: proteins aren’t static structures. They constantly shift between shapes, and we don’t yet have the technology to measure that across thousands of proteins at once. That gap is where machine learning could matter next. In this episode * What proteomics is, and how it sits between genomics and metabolomics * Isoforms and post-translational modifications: why there are so many more proteins than genes * The protein folding problem: why physics alone isn’t enough, and what AlphaFold borrowed from decades of earlier work * The four levels of protein structure, and what a predicted 3D structure actually gives you * Folding in the cell: ribosomes, chaperones, and why some proteins stay unfolded until they leave the cell * From structure to drugs: the lock-and-key idea, binding sites, and how most medications block or boost a protein’s function * mRNA vaccines: training the immune system on a single spike protein * CRISPR: how it works, off-target effects, ethical concerns, and use cases like BRCA-linked cancers and early-onset Alzheimer’s * Same DNA, different cells: gene expression, epigenetic regulation, and differentiation * Targeted gene editing, such as editing only the pancreatic cells in type 1 diabetes * Viruses vs. bacteria, and how HIV hijacks the immune system itself * Why the common cold and COVID keep evolving away from our vaccines * The new frontier: protein dynamics, conformational switching, and why one protein can have several functions * The missing tool: high-throughput measurement of protein structure over time, and what machine learning could do with itAbout the guest Jürgen Claesen is an Assistant Professor of Epidemiology and Data Science at Amsterdam UMC (VU Amsterdam) and a guest lecturer at the Data Science Institute, Hasselt University. He develops statistical and computational methods for high-throughput biological experiments, especially in sequencing and mass spectrometry. His work includes computational proteomics, structural bioinformatics, hydrogen/deuterium exchange mass spectrometry (HDX-MS), T-cell–based immune age metrics, and the effects of radiation on microbial communities. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit onedeeper.substack.com
