Taken together, our results point to new exciting directions for structural biology through distograms:
- Rapid flexibility detection
- Improved EM map interpretation
- Distogram-informed ensemble modeling

Full story 👉 doi.org/10.1101/2025...
💻 GitHub: github.com/CSB-KaracaLa...

We next asked: how do AF2-based sampling strategies affect distograms?

We tested MinnieFold, AFsample2, and AF_cluster.

The biggest impact came from the AF2 version itself. Only AF2.3 mirrored AF3’s flexibility-aware distogram profile.

We run MD of apo and holo AK2 and revealed that holo AK2 hinge distance is sampled rarely in its apo state!

Strikingly, apo AF3 distogram reproduces the exact same behavior!!🤯

Surprisingly, AF3 apo and holo AK2 predictions beautifully reflect this conformational change, where C-ter of AK2 experiences a disorder-to-order transition upon beta-stacking itself to AIFM1👇

To track hinge motion, we concentrated on 230-233 CB–CB distances of AK2.

We tested this hypothesis on AK2:AIFM1 complex, a molecular switch between energy metabolism and cell death. 🔁💀

Its function depends on a hinge-driven motion, that is:
✔Recently revealed by two cryo-EM maps
✔ Occurs upon binding
❌Not seen in crystal structures

A primer on distograms: for each residue pair, AF outputs distance probability distributions.

Earlier, it was shown that the shape of the distogram peaks may inform us on protein flexibility.

How?
✔ Unimodal peak → rigid behavior
✔ Bimodal peak → flexible behavior

It really was a blast!