Tessera
Folgen

Andrea Pasquadibisceglie

@andpdb.bsky.social

Staff scientist @tigem.bsky.social | Computational structural biologist

14 Posts193 Follower881 Folgt
Khmelinskaia Lab@akhmelinlab.bsky.social · 7mo ago

🗓️ Save the Date! The 5th European RosettaCon – Crossing Boundaries with Protein Design will take place in Lisbon, Portugal 🇵🇹 🗓️ October 28–30, 2026 Join the protein design community for an inspiring scientific meeting at the intersection of innovation and design.

Bild
Jeffrey J. Gray@jeffreyjgray.bsky.social · 7mo ago

Final stretch to apply for undergraduate summer internships in the Rosetta Commons! Come design proteins, develop AI and physics-based methods to model biomolecules, and impact health, materials, and sustainability! Application deadline is Sunday Feb 1. rosettacommons.org/education/reu/

Undergraduates

Rosetta Commons Research Experience for Undergraduates (REU) AI for Biomolecular Structure Prediction and Design Interns in this geographically-distributed REU program participate in research using…

rosettacommons.org

Andrew Plested@andrewplested.bsky.social · 7mo ago

"While the concept of condensates is successfully rewriting cell biology textbooks, there is some danger of overhype and backlash." This workshop summary is great - particularly the idea to shift from "Is it a condensate?" to "what problem does that solve?" but "successfully" stood out for me here

Stephen Royle@steveroyle.bsky.social · 7mo ago

Physicists' perspective on the future direction of condensates in Cell Biology. arxiv.org/abs/2601.03677

Simon Waddington@profsimonwad.bsky.social · last yr.

A new paper hitting the press: Gene therapy for AIPL-1 retinal dystrophy. Almost all kids with this can only perceive light, at best. Getting early will help with vision also neurodevelopment and psychosocial aspects. 🧬 ⭐ 👁 www.thelancet.com/journals/lan...

Gene therapy in children with AIPL1-associated severe retinal dystrophy: an open-label, first-in-human interventional study

Our findings indicate that young children with AIPL1-related retinal dystrophy benefited substantially from subretinal administration of rAAV8.hRKp.AIPL1, with improved visual acuity and functional vi...

thelancet.com

Sammy Chan@sammyhschan.bsky.social · last yr.

Preprint! All-atom structures of 2 folding intermediates on the ribosome, along parallel pathways & conserved across Ig domains, by 19F NMR & MD Co-led by @julianstreit.bsky.social, & thanks twlodarski.bsky.social, Alki, Lisa & John Christodoulou! #nmrchat #compbio www.biorxiv.org/content/10.1...

Structures of protein folding intermediates on the ribosome

The ribosome biases the conformations sampled by nascent polypeptide chains along folding pathways towards biologically active states. A hallmark of the co-translational folding (coTF) of many protein...

biorxiv.org

Jorge Bravo Abad@bravo-abad.bsky.social · last yr.

Leung et al. used deep autoencoders with outlier detection to guide weighted ensemble simulations of NTL9 folding, achieving up to threefold better efficiency than standard methods. pubs.acs.org/doi/full/10....

Unsupervised Learning of Progress Coordinates during Weighted Ensemble Simulations: Application to NTL9 Protein Folding

A major challenge for many rare-event sampling strategies is the identification of progress coordinates that capture the slowest relevant motions. Machine-learning methods that can identify progress coordinates in an unsupervised manner have therefore been of great interest to the simulation community. Here, we developed a general method for identifying progress coordinates “on-the-fly” during weighted ensemble (WE) rare-event sampling via deep learning (DL) of outliers among sampled conformations. Our method identifies outliers in a latent space model of the system’s sampled conformations that is periodically trained using a convolutional variational autoencoder. As a proof of principle, we applied our DL-enhanced WE method to simulate the NTL9 protein folding process. To enable rapid tests, our simulations propagated discrete-state synthetic molecular dynamics trajectories using a generative, fine-grained Markov state model. Results revealed that our on-the-fly DL of outliers enhanced the efficiency of WE by >3-fold in estimating the folding rate constant. Our efforts are a significant step forward in the unsupervised learning of slow coordinates during rare event sampling.

pubs.acs.org

Jorge Bravo Abad@bravo-abad.bsky.social · last yr.

Chronowska et al. introduce the Protein Design Archive, a curated database of over 1,500 de novo designs, revealing rapid growth from rational to deep learning–based methods. Their website offers key metrics and filtering tools for guiding future designs. www.nature.com/articles/s41...

The Protein Design Archive (PDA): insights from 40 years of protein design - Nature Biotechnology

Nature Biotechnology - The Protein Design Archive (PDA): insights from 40 years of protein design

nature.com