Erin Yang

Protein Design Scientist @generate_biomed, PhD from Baker and King Labs @UWproteindesign 🧬 🦠 | Semi retired triathlete (she/her)

[Erin Yang @erincyang]

Finally our work on designing pH responsive antibody nanoparticles capable of disassembling at ~tunable~ pH, packaging and releasing cargo, and targeting specific cell surface receptors is out in @NatureSMB! https://t.co/tsmlKktJfs

[Ian Humphreys @IanRHum]

Thrilled to share that today we report our human protein interactome in @ScienceMagazine! Predicting which pairs of proteins in the human proteome is a great challenge due to the shallow eukaryotic evolutionary signals but hugely important to understand. https://t.co/OtDqhcfG19

[Wenxian Shi @shi_wenxian]

🎉 Thrilled to share our paper just out in @NatureMedicine! We propose VaxSeer, a machine-learning framework that predicts how well vaccine strains will antigenically match future circulating viruses. https://t.co/ZHwaRsQP7v
w/ @jeremyWohlwend @menghua_wu @BarzilayRegina

[Rishwanth Raghu @rishwanth_raghu]

Excited to present CryoBoltz ❄️⚡, a multiscale guidance approach for steering AlphaFold3/Boltz-1 to sample structures that are consistent with experimental cryo-EM density maps. 🧵1/7

https://t.co/rPMtaPMsGF

Joint work with @axlevy0 @GordonWetzstein & @ZhongingAlong!

[Gabriele Corso @GabriCorso]

🚀 Excited to release a major update to the Boltz-1 model: Boltz-1x!

Boltz-1x introduces inference-time steering for much higher physical quality, CUDA kernels for faster, more memory-efficient inference and training, and more! 🔥🧵

[Yehlin Cho @ChoYehlin]

Excited to share our preprint “BoltzDesign1: Inverting All-Atom Structure Prediction Model for Generalized Biomolecular Binder Design” — a collaboration with @MartinPacesa, @ZhidianZ , Bruno E. Correia, and @sokrypton.

🧬 Code will be released in a couple weeks

[Erin Yang @erincyang]

@akaestli @katclone @atlasventure @BenKompa @wittyremarkhere @ecolienthusiast Sounds fun! Count me in!

[Brian L Trippe @brianltrippe]

🔥 Benchmark Alert! MotifBench sets a new standard for evaluating protein design methods for motif scaffolding.
Why does this matter? Reproducibility & consistent evaluation have been lacking—until now.
Paper: https://t.co/i2Lk3YZ24N | Repo: https://t.co/Xoun67eE9P
A thread ⬇️

[Simon Kohl @saakohl]

@Latent_Labs comes out of stealth today with $50M funding. Our goal? To push the frontiers of generative biology, giving partners instant access to tools capable of accelerating drug design.

Every biotech or pharma company searching for the best therapeutic molecules understands the role AI can play - but not all are in a position to develop their own advanced models. That’s where @Latent_Labs comes in.

[Kiera Sumida @KieraSumida]

Anna and Sam are X-less but they’ve done some excellent work with this project. It’s a very exciting time for enzyme designers!

[The Nobel Prize @NobelPrize]

“Science is a human activity.”

The week before chemistry laureate David Baker visited Stockholm to receive his Nobel Prize, his 101st PhD student had just graduated from his lab. For Baker, doing great science is about collaboration – he puts great effort into fostering a diverse, vibrant and sociable community of scientists that he works with. One hundred and thirty of those students and researchers joined him in Stockholm – perhaps the ultimate lab celebration!

More about Baker and the 2024 Nobel Prize in Chemistry: https://t.co/uOwBYCZDq6

[Sam Tipps @SamTipps]

Best read of the day - innovative design, and great science to generate large virus-like protein cages by breaking symmetry 🎉

https://t.co/TLyWPlGWwj

https://t.co/L7NYulQZrt

https://t.co/wXq5lsSzHt

Quinton Dowling,
@lsmin0152
@kribler
@KingLabIPD
@UWproteindesign

[Erin Yang @erincyang]

@yhsia_ipd @SamTipps @lsmin0152 @kribler @KingLabIPD @UWproteindesign We thought it was cute though! How far can we push 1wa3

[Zibo Chen @ZiboChen]

Excited to finally share Perceptein, a PERCEPtron made of proTEINs: https://t.co/saaO8ogAc3

[Bingxu Liu @BingxuL]

We are all born with a genetic lottery. Millions of T cell receptors are what we have with a hope to defend all cancer and viruses. What if that's not enough? Hope our work can give an interesting answer to you. https://t.co/o7HhX553RY

[Julia Bonzanini @jBonzaniniSci]

Can we use deep learning models to specifically target cancer cells? In our new preprint from the Baker lab we report how we can design fully de novo TCR mimics to distinguish antigenic peptides from “self” peptides on MHC class I and activate T cells https://t.co/kBJgnUQrjH

[Erin Yang @erincyang]

🤭

[King Lab @KingLabIPD]

One of the many King lab maxims:

[Erin Yang @erincyang]

@DaveJuergens How random is this walk?

[Google DeepMind @GoogleDeepMind]

Huge congratulations to @DemisHassabis and John Jumper on being awarded the 2024 Nobel Prize in Chemistry for protein structure prediction with #AlphaFold, along with David Baker for computational protein design.

This is a monumental achievement for AI, for computational biology, and science itself. 🧬

[Erin Yang @erincyang]

Congrats all!! It’s been remarkable to watch the field grow and now I can’t imagine this field without AI-based protein design and structure prediction. There was one day I remember watching David’s willingness to pivot to new ideas that I won’t forget 😉

[The Nobel Prize @NobelPrize]

BREAKING NEWS
The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in Chemistry with one half to David Baker “for computational protein design” and the other half jointly to Demis Hassabis and John M. Jumper “for protein structure prediction.”

[Ian Humphreys @IanRHum]

Here’s our human protein-protein interactome. We mined the SRA, devised a new distillation dataset for protein complexes, trained a new version of RF2 to screen millions of protein pairs, and identify > 18k binary interactions. https://t.co/rfEOJIlW1x