Cricket and Willow hosted a W-S lab dinner!

Did some quick curation for ~30 of 133 proteins in our new dataset RelaxDB, which is the first of its kind to gather experimental info on timescales of motions per residue. The x-axis is intentionally silly to make a point - these dynamics expts do not use more than 10% D2O in samples.

BioEmu actually doesn't pass this test for AdK: majority of samples are in closed state (1AKE), which is the same intrinsic bias that AF2 + random sampling gets.

I don't know the other apo/holo systems bioEmu looks at as well, but same story: sampled density is primarily at the holo state.

You can see this in this FRET data for AdK here: in ligand-free form, the open state is more populated than closed.

Really nice resource from @delalamo.xyz !!

Wanna mention the "AdK test" we're noticing newer DL methods fall short on:

many proteins (like AdK) that have apo/holo conf change sample both the apo/holo state even without ligand bound. But w/o ligand bound, they *are mainly in the apo state*

There are so many interesting things that Dyna-1 predicts, but I wanna talk about a trend it didn't predict in RelaxDB! We realized that in many RelaxDB datasets where Dyna-1 did poorly, the Rex came from phosphate buffer binding/unbinding to the protein, an experimental artefact.

We split the mBMRB into train, val, and test set, and held out RelaxDB too as eval set. Sure enough, many pre-trained models that we tried - AF2, ESM2, ESM3 - had predictive power for Rex in RelaxDB. The best model we found was a middle layer of ESM3. We named it Dyna-1. Here's NtrC from test set:

Some aa's in RelaxDB didn't have Rex data bc they were missing from assignments, step 1 of any NMR study. This can happen if a peak is exchange-broadened due to µs-ms motion.

AA's missing assns were also conserved.

Then I realized - we have that data for >10,000 proteins, way more than 133!

I found a trend that amazed me in RelaxDB: aa's with µs-ms motion were more conserved than aa's with no motion, which were more conserved than aa's with ps-ns motion.

**Depending on what timescale of motion we want to predict, we should expect different evol patterns.**

What's the red category?

People have measured Rex for decades and these measurements have elucidated all sorts of phenomena, like allostery in this NtrC signaling domain. But there was no standard collection!

Time to make a benchmark! Over 18 months, I curated 133 R1/R2/NOE datasets into "RelaxDB" (including NtrC).

Protein dynamics was the first research to enchant me >10yrs ago, but I left in PhD bc I couldn't find big experimental data to evaluate models.

Today w @ginaelnesr.bsky.social, I'm thrilled to share the big dynamics data I've been dreaming of, and the mdl we trained w them: Dyna-1.
📝: rb.gy/de5axp

Incredible moon over Lake Mendota waiting for the bus that iPhone can hardly do justice

Unrelated: looking for recs for tech-sensitive gloves that can handle a “feels like” of -15F 😅

❄️🕸️!

Good roast near NeurIPS!

First W-S lab dinner, selfie, and 0.5x selfie! Grateful so many awesome people around in what’s technically year -1 of the lab!

Re docking: @workshopmlsb.bsky.social has been piloting a leaderboard for the PLINDER benchmark. It would be awesome to get submissions using existing methods, then everyone can see comparisons better 😁
leaderboard & instructions are on mlsb.io

I think Bucky liked my nmr hoodie ☺️ @nmrfam.bsky.social @uwbiochem.bsky.social

A nice Sunday morning where one of us is working on job applications and one of us is destroying a cardboard box.

Hello world! (aka, Bluesky)

Have you had a fun weekend? I sure did!