Debangana Moitra

Find me in Interested in Plant Immunity; Researcher in ZMBP, Tübingen; DAAD research fellow at TU Munich

[Debangana Moitra @DebanganaMoitra]

Looking back at some of the inspiring lectures from #PPRM2025 in Edinburgh—such a privilege to learn from so many outstanding researchers. Grateful for this community and the ideas it sparks.

[Debangana Moitra @DebanganaMoitra]

Bittersweet farewells: Skylar returns to the US after her DAAD internship under my supervision, many thanks to her for three cheerful, hardworking months and excellent lab work. Vahid, thanks for supporting me since I began my PhD. Thanks to Birgit for a wonderful dinner!

[Debangana Moitra @DebanganaMoitra]

@TheSainsburyLab @wenboEffector @ERC_Research Congratulations @wenboEffector

[Julien Gronnier @NanoSignaling]

PPRM2026 Registration is now OPEN!
https://t.co/EyXr60KSsl
You can book hotel rooms at the venue using the link below

[Andre Cornman @ancornman1]

Predicting protein-protein interactions (PPIs) at proteome scale can take months with co-folding models due to massive all-vs-all comparisons required.

We are excited to announce FlashPPI, a contrastive model that predicts proteome wide physical interfaces in minutes. 1/🧵

[Jiorgos Kourelis @JiorgosKourelis]

📢 2 PhD Positions - Plant Immune Receptor Bioengineering at Imperial College London
🌱 Start: Oct 2026
📅 Deadline: 10 Feb 2026
🇬🇧 UK/settled status only
💰 Fully funded (48 months)
ℹ️ https://t.co/JEoV7SJ29i
#PlantImmunity #PlantPathology
🙏 Share with interested candidates!

[Hannes Stark @HannesStaerk]

Join our online BoltzGen presentation and Q&A on Wed. Dec. 17th at noon ET!

A few new results, many new insights, and lots of good discussion, I am sure!

Paper: https://t.co/50EoQgppFN
Presentation sign up + Zoom: https://t.co/41AXvPNEH4

[Jakub Lála 👨🏻‍🍳🥯 @jakublala]

excited to see BAGEL published in PLOS Computational Biology. my first proper first-author publication 🥳. let's keep on cooking 🍳.
https://t.co/zYPeFYKADV

[Ameya Daigavane @BigAmeya]

Will be presenting JAMUN, our conformational ensemble sampling method bridging molecular dynamics and diffusion models, at #NeurIPS2025 at 11 AM PT (Poster #1616) today!

[Caroline Gutjahr @carogutj]

Are you interested in using synthetic approaches to promote arbuscular mycorrhiza symbiosis? Then our PostDoc position may be for you: https://t.co/i1VjQYfFs0

[Mauricio Contreras @mpcontreras4]

Check out our new story on the famous rice Pik NLR pair, led by @ClemMarchal and @HsuanPai1 ! Turns out they form a massive 1 MDa membrane-associated complex before activation 🤯 A cool new example of the diversity of NLR resting states!

[Diana Gómez De La Cruz @dianagdlc]

It’s been an absolute pleasure to be part of TSL for this long. I’m very grateful to everyone I’ve met along the way—I’ve learned a lot. I’ll miss TSL and Norwich so much. Tons of mixed feelings, leaving Norwich behind, and the excitement of new adventures ahead🇨🇭✨

[Sergey Ovchinnikov @sokrypton]

A few 2Dmol updates 🧬

https://t.co/iHwS4XvrUj
Integration with AlphaFoldDB (will auto fetch results). Drag and drop results from AF3-server or ColabFold for interactive experience!
(1/5)

[Suman Chakrabarty @SumanPhysChem]

Our team @snbkol introduces PathGennie (just published in @JCIM_JCTC), a fast and unbiased computational framework for uncovering rare molecular events such as drug unbinding and protein folding.

Instead of using any biased forces or elevated temperatures, PathGennie launches ultrashort unbiased MD trajectories and selectively propagates only those that show real progress toward the transition. This lets us generate complete rare-event pathways in just 10–100 ps, while preserving true molecular dynamics.

Full credit goes to my PhD student Dibyendu Maity @MAITYDIBYENDU99 for formulating and implementing the PathGennie code. Thanks to @ANRFIndia for funding.

✨ Key Highlights:
• Identified 7 distinct unbinding routes for benzene from T4 lysozyme
• Recovered all major exit pathways for imatinib from Abl kinase within a handful of attempts
• Captured folding/unfolding pathways of Trp-cage and Protein G that align with minimum free-energy paths
• Weighted Ensemble (WE) simulations converge 3–4× faster when initialised with PathGennie-generated pathways
• Path finding works even with suboptimal CVs

🔗 Try our code: https://t.co/pO8gfhZNda
📄 Read the paper: https://t.co/jThJvhBTjW

#CompChem #RareEvent #EnhancedSampling #MolecularDynamics #PathSampling #DrugDiscovery

[Schneeberger lab @LabSchneeberger]

🌱 Postdoc position in Plant Genomics/Bioinformatics!

Love genome plasticity, computational methods, and solving big questions in plant biology? Join our Institute for Crop Biology at HHU Düsseldorf.

More info on https://t.co/dKXZtNjtgY
Apply by Nov. 30 | 3-year position

[Pranam Chatterjee @pranamanam]

What if molecules or cells could be modeled as truly entangled, in which each particle’s motion shaping the others? Meet EntangledSBM, a Schrödinger Bridge framework for interacting second-order dynamics! ⚛️

📜: https://t.co/JnwkS6RaxQ
💻: https://t.co/rPb8s9oSmu

In her recent BranchSBM paper, @_sophia_tang_ extended Schrödinger Bridge Matching to branched systems, formulating a sum of unbalanced conditional stochastic optimal control problems to model how single states diverge into multiple fates. But while real biological systems branch, they also interact -- each particle’s motion depends on the evolving velocities of others! 🤝

To address this, Sophia introduced an entangled bias force ⚛️ that couples the velocities of all particles (letting each influence the others’ motion) and reformulated Schrödinger Bridge optimization as a convex off-policy objective, building on the weighted cross-entropy ideas from TR2-D2, her framework with @YuchenZhu_ZYC. This stabilizes training even in high-dimensional coupled systems and yields a scalable bridge solver that captures interacting dynamics without intermediate simulation. 🌌

As a result, EntangledSBM accurately reconstructs cell-state trajectories under Clonidine and Trametinib perturbations 🧫, recovering unseen perturbed populations with order-of-magnitude lower error and smoother, biologically consistent paths. In molecular dynamics, it generates realistic transition pathways for Alanine Dipeptide and fast-folding proteins (Chignolin, Trp-cage, BBA), reaching >90 % target-hit accuracy and sub-angstrom RMSDs, showing that a single bridge can capture both collective cell behaviors and rare molecular transitions! 🌟

2025 has been a landmark year for @_sophia_tang_ (just >1 year in my lab!): from PepTune 🧩, Gumbel Flow Matching ⚙️, BranchSBM 🌿, and TR2-D2 🤖🌳, to now EntangledSBM ⚛️. With @yinuo_z98 always by her side, she's built new theoretical foundations for our lab (both dry and wet!), and is redefining generative modeling for biology! Couldn’t be prouder to be her advisor. 👏

[Debangana Moitra @DebanganaMoitra]

@Surbhiphulia ❤️

[Quantitative Plant Biology @qpb_journal]

New Article!

"Molecular tipping points in plant cell surface H+ homeostasis and signalling"

https://t.co/92h17XyzhC

#OpenAccess

[Debangana Moitra @DebanganaMoitra]

Time flies—just a year ago I gave my first chalk talk at the ZMPP symposium. This year I had the privilege to present again, now with a flash talk + poster. A wonderful experience sharing and learning with the community! #ZMPP2025
@ZMBP_Tuebingen

[El Kasmi Lab @Farid_El_Kasmi]

Here are some pics from the 1st chalk-talk session…

[Frank Menke @Frank_Menke]

@Nature @I_GuzmanBenito The Next PLANT PEPTIDE AND RECEPTOR meeting will be in Muenich in 2026 organized by @JulienGronnier and #friends #watchthisspace