This is me. Please note!

Persepolis (2000), autobiographical graphic novel by Iranian cartoonist, illustrator, author and film director Marjane Satrapi #WomensArt ❤️ RIP

It‘s time to remove the question mark! A huge congrats to @CraigMCrews, Ray Deshaies and the scientists @ArvinasInc. 1st FDA approval for a #PROTAC on May 1st 2026. A day to remember. Extra drinks at the Proxidrugs GRC in a few weeks!

Statistical crystallography as a route to understanding protein dynamics! 1,146 crystal structures of SARS-CoV-2 Mpro reveal correlated motions connecting the dimer interface to the active site. Great to see this work out by the DESY team. Link: rdcu.be/fgzPF

Flow matching is emerging as a unifying framework for generative biology Biology is full of mappings between states: a healthy cell turning diseased, amino acids folding into a functional protein, a ligand docking into its target. Deriving such transformations analytically is intractable—which is where generative AI steps in, and flow matching is quickly becoming its backbone. Morehead and coauthors review how flow matching (FM) is reshaping generative modeling in bioinformatics. Unlike diffusion models, FM doesn't force the source distribution to be Gaussian: it learns a time-dependent vector field that transports samples between any two distributions along straight-line, optimal-transport paths. The payoff: fewer inference steps, simulation-free training, and built-in support for geometric priors like SE(3) equivariance—essential for 3D biomolecules. What's striking is how fast FM has spread across biological scales. For molecules, FoldFlow, FrameFlow, and Multiflow generate protein backbones on SE(3)ᴺ manifolds, SemlaFlow produces valid small molecules up to 100× faster than diffusion, and Dirichlet FM handles discrete DNA/RNA sequences. FlowDock and NeuralPLexer3 predict protein–ligand complexes that match or exceed AlphaFold 3 on key benchmarks, while AlphaFlow and MDGen generate conformational ensembles and MD trajectories. At the cellular scale, CellFlow and Meta FM map unperturbed populations to perturbed states, and CryoFM and FlowSDF extend FM to cryo-EM and microscopy. The deeper point: FM subsumes diffusion models, continuous normalizing flows, and optimal transport as special cases, providing scaffolding for an AI-based virtual cell—simulating molecular, structural, and phenotypic effects of perturbations across scales. Overall, this signals a shift in what's computationally tractable. Instead of narrow, stage-specific models, FM points to unified conditional generators that design sequences, predict complexes, and model perturbation responses in one framework—shortening wet-lab cycles and making closed-loop, active-learning workflows practical. Paper: Morehead and coauthors, Nature Machine Intelligence (2026) — Journal license | doi.org/10.1038/s42256-026-0…

Who did this? 😂

Respect!!

Basically

Excited to share our work on β1AR activation! Unique microswitches in extracellular regions, trigger the common GPCR activation mechanism. Led by @shrutikoulgi, with Uddhavesh Sonawane, @durbignon and in collaboration with Daniel Nietlispach and team. pubs.acs.org/doi/10.1021/acs…

My passion project is out today, in the US, UK, Europe, Australia ... About the book from the Yale University Press website: yalebooks.yale.edu/book/9780…

🙏🏾🙏🏾🙏🏾🙏🏾 to the hard work & fantastic organization for #OBMT26 to Front row L to R: @Ssaleem_M Abdur Rahaman @kuruhoornambi Back row L to R trainees: Urbi Ghosh, Divit Solanki, Aninda Sundar, Debraj Koiri, Gargi Dey, Riddhisha Patra, Neelrathan, Srijita Roy, Swapnil Sahoo

Coarse grain Martini molecular model of Caveolin-binding shows that Caveolin both induces and senses membrane curvature. Caveolin binding induced curvature shows that cholesterol & PS are found in the neck. @durbignon @csir_ncl #OBMT26

Becoming more critical with all the cylinder shortages

So who discovered the Fibonacci sequence? Fibonacci? No, afraid not (no disrespect Leonardo Bonacci, aka Fibonacci). Another scientist? Nope. Who then? Here's @MarcusduSautoy (it wasn't him either in case you're wondering).

We have known that proteins are made of amino-acids for ~ 120 years. In 1902, Fischer and Hofmeister proposed that the -NH2 of one amino acid binds the -C00H of another, resulting in a linear structure that Fischer termed "peptide".

Happy to share our recent paper doi.org/10.1021/acschemneuro… where we computationally analyzed the specificity of the serotonin1A receptor-PIP lipid interactions using multi-microsecond long coarse-grain MD simulations.@durbignon @ccmb_csir @CSIR_IND @ACSChemNeurosci #gpcr

Yet another new index! But this time calculating "mentorship"... My M10-index is 36! Find yours at: jef.works/Mentorship-Index/

A real issue in science administration here...

Dmitri Mendeleev, who is credited with creating the Periodic Table of Elements was nominated for a Nobel Prize in Chemistry 9 times but never won. His awarding was blocked each time by the 1903 winner, Svante Arrhenius, who held a grudge against Mendeleev for criticizing one of his papers.

We are organizing a 7-day EMBO sponsored international workshop at @iiscbangalore @MBU_IISc (April 26-May 03, 2026). "AI-driven approaches in Structural Biology". Link: lnkd.in/gSGASks8. Please retweet. Looking forward to seeing some of you in Bangalore!