Chenlin_Lu

Biophysicist fascinated by proteins

[Bowen Jing @bjing2016]

Binder design has come of age thanks to generative models—but how can we access the wider array of dynamic, multistate protein functions, so elegantly employed by nature?

@mihirbafna14 and I are excited to share SwitchCraft, a framework for designing such functions. (1/7)

[Chenlin_Lu @chenlin_lu]

Compared to the preprint, we‘ve added an experimental HX/NMR benchmark showing near-perfect agreement. It’s also fully compatible with the new HXMS standardized file format.

[Glasgow Lab @glasgow_lab]

🎉 PIGEON-FEATHER is now published online. In this work, we present a Bayesian framework for extracting site-resolved free energies of opening (∆Gop) from HX/MS data, linking experimental exchange kinetics to underlying conformational free energy landscapes.

[Chenlin_Lu @chenlin_lu]

Excited to share our study on how proteins with the same fold evolve distinct allosteric networks to drive different functions—even in response to the same chemical triggers.

https://t.co/mZjes4Pi2Z

[Frank Noe @FrankNoeBerlin]

Super excited to preprint our work on developing a Biomolecular Emulator (BioEmu): Scalable emulation of protein equilibrium ensembles with generative deep learning from @MSFTResearch AI for Science.
#ML #AI #NeuralNetworks #Biology #AI4Science

https://t.co/yzOy6tAoPv

[Chenlin_Lu @chenlin_lu]

I am excited to share our recent work on deriving site-resolved energetic information (∆Gop) from hydrogen exchange/mass spectrometry (HX/MS) experiments, ensemble energy determined by the distribution of conformational states it occupies.

https://t.co/iUbmPJ0ucJ

[Leon Klein @leonklein26]

Excited to share that our paper "Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics" has been accepted as a spotlight for #NeurIPS2023.
@AndrewFoongYK @torfjelde @kayembruno @mmjb86 @sebnowozin @FrankNoeBerlin @ryotat
1/12

[Xiang Sheng @xish2046]

Novel Au(I)-Based Artificial Metallo-Cycloisomerase for Catalyzing the Cycloisomerization of γ-Alkynoic Acids | ACS Catalysis https://t.co/4TBi3TNXd0

[Christopher Frank @chrisfrank662]

Roughly one year ago we started out venturing in the world of #proteindesign. Today I am very happy to share our first preprint ‘Efficient and scaleable de-novo protein design using a relaxed sequence space’ (https://t.co/UCZJoNSXhE) with @sokrypton & @hendrik_dietz 1/x

[Noora Aho @noora_aho]

Constant pH molecular dynamics in GROMACS - our two publications are finslly out!✨🖥️ Theory, code, small tutorial and best practices are out there🏆
(method) https://t.co/NtBEawiSvB
(best practices) https://t.co/Q32eeu4Unz

[Justas Dauparas @JustasDauparas]

ProteinMPNN paper: https://t.co/BLPg2XdmYE
Github: https://t.co/ECb926ECsu
Colab notebook: https://t.co/y6x6GZwYj3
HuggingFace notebook: https://t.co/lbXXAKWTHK

Hallucinating symmetric protein assemblies paper:
https://t.co/cBoI8RuK5Q

Thanks to all collaborators!

[Roberto Chica Lab @Chica_lab]

Save the date! The rescheduled Keystone Symposium on "Computational Design and Modeling of Biomolecules" will take place in Banff 🇨🇦 on March 14-17, 2023. #proteindesign

https://t.co/q6lNpvypaB

[Rommie Amaro @RommieAmaro]

🚨🚨 New paper alert! 🚨🚨

Need to compute k_off, k_on & deltaG for your ligand-protein complexes? 🤔

Check out SEEKR2 - now out @JCIM_JCTC & powered by @openmm_toolkit

Highlights... 🧵:

https://t.co/CsUTYxjrpn

[Mohammed AlQuraishi @MoAlQuraishi]

Building on last week’s announcement of OpenFold, an academic-industry consortium is being announced today within the non-profit @openmsf. The OpenFold Consortium https://t.co/vwzkot9aVA will develop open source ML-based molecular modeling tools in a community-driven fashion. 1/3

[Mohammed AlQuraishi @MoAlQuraishi]

We have successfully trained OpenFold from scratch, our trainable PyTorch implementation of AlphaFold2. The new OpenFold (OF) (slightly) outperforms AlphaFold2 (AF2). I believe this is the first publicly available reproduction of AF2. We learned a lot. A🧵1/12

[Joshua Meier @joshim5]

Protein folding from single sequences is enabled by replacing MSAs with protein language models! Amazing how rapidly this field has evolved since we started with LM-based "contact prediction" in 2019 🚀

[Communications Chemistry @CommsChem]

.@chenlin_lu @maitybasudev @pengxuexue and coworkers elucidate the formation of a multinuclear Au cluster in apo-ferritin using SCXRD and quantum chemical calculations
https://t.co/eNUPJ6GsAy

[Steve Brohawn @SteveBrohawn]

New preprint from the lab! Toby Turney shows how the K+ channel TWIK1 is gated shut by a selectivity filter "zipper". Congrats Toby + Vivian! https://t.co/EvqzLxZbeb

[Sergey Ovchinnikov @sokrypton]

End-to-end learning of multiple sequence alignments with differentiable Smith-Waterman
https://t.co/4KKHCc3OZ0
A fun collaboration with Samantha Petti, Nicholas Bhattacharya, @proteinrosh, @JustasDauparas, @countablyfinite, @keitokiddo, @srush_nlp & @pkoo562 (1/8)

[Angel J. Ruiz-Moreno 🇲🇽 @ruiz_moreno_aj]

My first release of #Jupyter_Dock: Molecular Docking integrated in Jupyter Notebooks (Git repo: https://t.co/cJJe2TcRA9)

Notebooks for:

- Molecular Docking
- Virtual Screening
- Blind Docking
- Reverse Docking
- Docking Analysis

Example:
https://t.co/o0dz7VlH06

#compchem

[Sergey Ovchinnikov @sokrypton]

@LindorffLarsen Don't think I've ever seen tweets cited before 😂 #OpenTwitterScience