Publicly available dataset of protein-ligand affinities and structures!
In the era of AI models, high quality data is the key!
🔬 Biophysics Week a la @uvic-ucc.cat!
El 25/03/26 acollim la xerrada “Nanorobots in action” amb la Dra. Maria Guix Noguera, per descobrir com la biofísica nano pot transformar la medicina del futur.
📍 Aula Magna
🕥 11:30 h
🔗 Inscripcions: tuit.cat/NgpwL
#BioPhyzza2026 #BiophysicsWeek #UVicUCC #FCTE
A detailed comparison of de novo designed proteins by NMR finally puts to rest the idea that structure prediction confidence metrics have any correlation with local flexibility
#bioGUNE_News | 🎉 Yesterday we celebrated our 21st anniversary at #CICbioGUNE @brtaeus.bsky.social with a cutting-edge scientific day
🔸 Isabel Fariñas on neural stem cell quiescence
🔸 June Ereño-Orbea on Siglec–sialoglycan cancer immunotherapy
🔗 www.cicbiogune.es/news/cic-bio...
“It’s a major advance, on the scale of an AlphaFold4. The problem, of course, is that we know nothing of the details.”
Isomorphic Lab’s proprietary drug-discovery model is a major advance
go.nature.com/3Mm2ZnQ
My reply to @anshulkundaje.bsky.social on the other site has been quoted in this @nature.com report on Isomorphic's new DDE model, which relies on private data to a degree that is probably unprecedented in the history of this field 🧪🧬
Isomorphic Lab’s proprietary drug-discovery model is a major advance, but scientists developing open-source tools are left guessing how to achieve similar results.
Facultat de Ciències, Tecnologia i Enginyeries de la UVic-UCC
Gabriel Ortega
Diego del Alamo
Diego del Alamo
Nature
#OpenBind announces its first data drop marking a major milestone for AI‑Enabled #DrugDiscovery! It’s the first initiative to generate open, AI‑ready datasets for protein–drug complexes, produced continuously & at industrial scale to enable the next generation of #AI models. https://loom.ly/eIrsqqg
Finding one mutation that improves a protein is hard. Finding five that work together is exponentially harder.
Today in @science.org, Hsu and Konermann labs present MULTI-evolve, a lab-in-the-loop framework that does it in just one machine learning-guided round.
Oh no... 😢 se va uno de los mejores blogs que recuerdo.
No sólo divulgaban sobre economía y políticas públicas, también representaban una forma de afrontar el debate racional, sosegada, humilde frente a la complejidad.
Una víctima más de la inmediatez y la polarización de las redes sociales.
🚨 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭 🚨
💡epiGPTope: A Machine Learning-Based Epitope Generator and Classifier
📄 ACS Synthetic Biology
👉https://doi.org/10.1021/acssynbio.5c00693
Large-scale exploration of protein space by automated NMR [new]
enables high-throughput experimental characterization of designed protein structure and dynamics, revealing how sequences encode motion.
“It’s a major advance, on the scale of an AlphaFold4. The problem, of course, is that we know nothing of the details.”
Isomorphic Lab’s proprietary drug-discovery model is a major advance
go.nature.com/3Mm2ZnQ
In a development that could transform how scientists study cancer, neurodegeneration and inflammation, #UCSB researchers have invented a modular, genetically encoded, protein-based sensor that enables MRI machines to visualize molecular activity inside cells.
Full story: https://ow.ly/cRmg50YqsiU
Isomorphic Lab’s proprietary drug-discovery model is a major advance, but scientists developing open-source tools are left guessing how to achieve similar results.
In a development that could transform how scientists study cancer, neurodegeneration and inflammation, researchers have invented a modular, genetically encoded, protein-based sensor that enables MRI machines to visualize molecular activity inside cells.
