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sandrobottaro.bsky.social

@sandrobottaro.bsky.social

37 Followers  |  25 Following  |  1 Posts  |  Joined: 26.12.2023  |  1.5175

Latest posts by sandrobottaro.bsky.social on Bluesky

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Excited to unveil Boltz-2, our new model capable not only of predicting structures but also binding affinities! Boltz-2 is the first AI model to approach the performance of FEP simulations while being more than 1000x faster! All open-sourced under MIT license! A thread… πŸ€—πŸš€

06.06.2025 13:46 β€” πŸ‘ 215    πŸ” 91    πŸ’¬ 10    πŸ“Œ 11
Overlayed configurations of a small molecule binding (?) to an unstructured protein

Overlayed configurations of a small molecule binding (?) to an unstructured protein

We have a job opening at Peptone.io for an ML researcher.

Come help us find new ways to understand and drug intrinsically disordered proteins (IDPs), it's a very interesting and important problem!

Link in the reply ↓

09.05.2025 15:26 β€” πŸ‘ 17    πŸ” 7    πŸ’¬ 1    πŸ“Œ 0

Check out our recent preprint πŸ‘‡on counting particles to estimate populations in #cryoem: noise can bias the estimates; with Luke Evans & a great team.

30.03.2025 13:29 β€” πŸ‘ 29    πŸ” 13    πŸ’¬ 0    πŸ“Œ 1
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Delighted to announce that our paper "Predicting absolute protein folding stability using generative models"(lnkd.in/dZJMiY4r) has been awarded the Protein Science BEST PAPER 2024 by @proteinsociety.bsky.social.

27.03.2025 16:44 β€” πŸ‘ 23    πŸ” 6    πŸ’¬ 1    πŸ“Œ 0
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We are sill accepting applications for poster presentations at the CECAM conference 'RNA Modelling Across Scales". Join us in the beautiful Trieste β˜€οΈπŸ–οΈπŸ°! Apply now: www.cecam.org/workshop-det... Co-organized with @bussigio.bsky.social @marcodevivo.bsky.social

27.03.2025 19:04 β€” πŸ‘ 10    πŸ” 5    πŸ’¬ 0    πŸ“Œ 0
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Our paper on prediction of phase-separation propensities of disordered proteins from sequence is now published:
www.pnas.org/doi/10.1073/...

The paper has been substantially updated compared to the preprint including new experimental data and using the neural network to finetune CALVADOS. 1/n

25.03.2025 17:55 β€” πŸ‘ 71    πŸ” 17    πŸ’¬ 1    πŸ“Œ 1

This is the moment we've worked toward for a long time: First public disclosure of the @asapdiscovery.bsky.social pan-coronavirus antiviral aiming to help keep humanity safe from future pandemic threats like MERS-CoV and other bat coronaviruses.

25.03.2025 19:47 β€” πŸ‘ 96    πŸ” 36    πŸ’¬ 4    πŸ“Œ 1
Careers Careers

We’re looking for fellow nerds to help us make disordered proteins druggable. Love #IDPs, #MD, #NMR, #AI, #DrugDiscovery, or #MassSpec? Let’s talk.
@bindresearch.org is hiring across the board: bindresearch.org/careers/
#compchem #compbio #NMRChat #TeamMassSpec #chemjobs @chemjobber.bsky.social

24.03.2025 10:51 β€” πŸ‘ 28    πŸ” 17    πŸ’¬ 0    πŸ“Œ 0

link is broken but I think I know that paper πŸ˜‡

20.03.2025 21:11 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0
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πŸ“Œ Don't miss our Research Nodes #seminar this week, with Dr. @lindorfflarsen.bsky.social, from the #LinderstrΓΈmLang Centre for Protein Science (Denmark)πŸ‘‡

🀝 Hosted by Dr. @xsalvatella1.bsky.social  

Register now! ➑️ shorturl.at/Q1LVA

#BarcelonaBiomed

πŸ§ͺ

06.01.2025 10:01 β€” πŸ‘ 24    πŸ” 7    πŸ’¬ 0    πŸ“Œ 0
Conclusion slide on RNA assessment

Conclusion slide on RNA assessment

Conclusion of RNA assessors in #CASP16 - we are still in the β€œtemplate” phase. Prediction of nucleic acids structure is still challenging for targets without templates, often relying on intuition. No big leap in accuracy since CASP15. AI based methods have not (yet?) made a major difference.

03.12.2024 13:30 β€” πŸ‘ 20    πŸ” 5    πŸ’¬ 0    πŸ“Œ 2
CECAM - Generative models for classical and quantum matter

Our research presented at the @cecamevents.bsky.social workshop www.cecam.org/workshop-det...! Ivan Gilardoni will show a poster about our #python package MDrefine. See also arxiv.org/abs/2411.07798

02.12.2024 01:40 β€” πŸ‘ 23    πŸ” 4    πŸ’¬ 0    πŸ“Œ 0

Meet the CALVADOS RNA model

Ikki Yasuda, SΓΆren von BΓΌlow & Giulio Tesei have parameterized a simple model for disordered RNA. Despite it's simplicity (no sequence, no base pairing) we find that it captures several phenomena that depend on the charge, stickiness and polymer properties of RNA 🧬🧢πŸ§ͺ

29.11.2024 08:25 β€” πŸ‘ 89    πŸ” 21    πŸ’¬ 4    πŸ“Œ 2

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