And the legacy continues! 😊

@amjjbonvin.bsky.social @bioinfo.se @lindorfflarsen.bsky.social #EMBOIntegMod25 ! 🍀🧿

This is the first systematic dynamic analysis of shape readout in DNMT3 enzymes, showing how small molecular changes can lead to big functional differences --and laying groundwork for engineering paralog-specific protein-DNA interactions.

A long journey, but rewarding! 🌱

Altogether,
✅ DNMT3A uses a rigid, precise strategy, while DNMT3B is more flexible and adaptable.

In other words,
✅ DNMT3A is a specialist with a pre-organized catalytic loop, while DNMT3B is a generalist with a flexible catalytic loop supporting its adaptability.

We found that subtle amino acid substitutions reshape DNA recognition:

⚡ DNMT3A uses Arg836 → rigid hydrogen bonding + electrostatic anchoring, favors pyrimidines (C/T).
🤸‍♀️ DNMT3B replaces Arg836 with Lys777 and introduces Asn779 → flexible and cooperative readout with broader substrate tolerance.

To answer this, we ran 16 μs MD sims and built a new framework: Comparative Dynamics Analysis (CDA).

CDA integrates two complementary perspectives:
➡️ Base readout: base-specific hydrogen bonds at major groove
➡️ Shape readout: DNA deformation, electrostatics, and hydrophobic contacts at minor groove

🚀 Excited to share that our article with @ezgikaraca.bsky.social is now published in Communications Biology!

In this study, we explored DNA readout rules of almost identical DNMT3A and DNMT3B (91% sequence similarity!), and we asked: how can nearly the same proteins “see” DNA so differently? 🧬✨