AlphaFold Unofficial

Turkeys carry about 18,000 to 22,000 protein-coding genes.
Inside those cells, trillions of protein molecules build structure, repair damage, and keep the bird alive. About twenty thousand protein-coding genes and countless protein molecules operate in every cell.

A meal is never simple biology.

AlphaFold DB provides open access to over 200 million protein structure predictions to accelerate scientific research.

Besides, one could easily argue that AlphaFold (Ben's example) indeed made a paradigm shift.

alphafold.ebi.ac.uk

The Download: the future of AlphaFold, and chatbot privacy concerns This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. What’s next for AlphaFold: A conversation with a Google...

The Download: the future of AlphaFold, and chatbot privacy concerns #Science #TechnologyandEngineering #AlphaFold #ChatbotPrivacy #AIethics

The complete evolution of artificial intelligence: from neural networks to generative AI - The Urban Herald Explore the complete evolution of Artificial Intelligence, from 1943 neural networks to 2025 generative AI. Discover 82 years of breakthroughs, setbacks & transformative innovations.

From McCulloch-Pitts neurons (1943) to ChatGPT: 82 years of AI evolution. Explore breakthrough moments including Turing's test, AI winters, AlexNet's revolution, transformers, and AlphaFold. #AI #MachineLearning #TechNews #Tech #News
The complete timeline:

What’s next for AlphaFold: A conversation with a Google DeepMind Nobel laureate “I’ll be shocked if we don’t see more and more LLM impact on science,” says John Jumper.

What’s next for AlphaFold: A conversation with a Google DeepMind Nobel laureate | MIT Technology Review www.technologyreview.com/2025/11/24/1...

AlphaFold Database Structure Extractor: a web server and API to download AlphaFold structures using common protein accessions | BMC Bioinformatics - Ireland Background

AlphaFold Database Structure Extractor: a web server and API to download AlphaFold structures using common protein accessions | BMC Bioinformatics

https://www.europesays.com/ie/198966/

Background The AlphaFoldDB Structure Extractor (https://project.iith.ac.in/sharmaglab/alphafoldextractor/) is …

Google DeepMind won a Nobel prize for AI: can it produce the next big breakthrough? The company was created to use AI for world- changing science — and achieved that with AlphaFold. But the advent of large language models raises deep questions about the future of DeepMind.

Google DeepMind was created to use AI for world-changing science and achieved that with AlphaFold. Nature reports on how the advent of large language models has raised questions about DeepMind’s future and whether it can achieve blockbuster successes in other fields of science. 🧪

What’s next for AlphaFold: A conversation with a Google DeepMind Nobel laureate “I’ll be shocked if we don’t see more and more LLM impact on science,” says John Jumper.

It was five years ago this week that AlphaFold 2’s debut took scientists by surprise. Now that the hype has died down, what impact has AlphaFold really had? How are scientists using it? And what’s next? We talked to John Jumper (as well as a few other scientists) to find out.

Protein domains have no single definition, so why stick to one segmentation? 🧩

Instead of forcing structures into rigid classifications, we built AFragmenter. It uses AlphaFold PAE networks for a tuneable approach to domain parsing.

You control the granularity. 👇
🔗 doi.org/10.1093/bioi...

Alphafold model of LINE1 from UniProtKB

Finally peptides for 5 predicted proteins mapped to multiple regions in the genome. We believe that most of these peptides were also produced by aberrant translation. LINE 1 ORF1 would be a good example, present in hundreds of regions and with more than 50 peptides in cancers.

Alignment of the three placenta-expressed ERV gag ORFs supported by PeptideAtlas peptides. Residues are coloured by structural domains from the related AlphaFold model of ERVFRD-2 from the paper.

Another 6 coding genes derived from retroviruses, and 3 of these were detected exclusively in placenta. This is remarkable because up to now all well-known co-opted retroviral genes in human placenta were derived from env ORFs. All three PeptideAtlas-supported novel ORFs were ERV gag ORFs.

Predicted structures from AlphaFold for genes ZNF840P and CFAP144P1 with the detected PeptideAtlas peptides mapped in yellow. On the right, and analysis of one of the CFAP144P1 peptides by Vseq.

The other 14 genes can be split into two groups. Eight derived from gene duplications. Many of these have undergone considerable changes and may have been pseudogenes prior to gaining novel function. These genes include C5orf60 (now SPATA31J1), CFAP144P1, MSL3P1 (now MSL3B ) and ZNF840P.

AI integration into healthcare carries a long & storied history. From Watson identifying the correct diagnosis from pathology slides to Nobel prize winning AlphaFold predicting 3D computational structure of proteins from just amino acid sequences, there's no shortage of jaw dropping use cases

ProteinCHAOS runs entirely in the browser and lets you choose how to visualize your protein structures.
It supports PDB files from the PDB and AlphaFold servers and offers several visual themes so you can "paint" abstract art with protein traces. I hope it helps you create some interesting images!

AlphaFold Protein Structure Database 2025: a redesigned interface and updated structural coverage Abstract. The AlphaFold Protein Structure Database (AFDB; https://alphafold.ebi.ac.uk), developed by EMBL–EBI and Google DeepMind, provides open access to

From Sameer Velankar & colleagues in @narjournal.bsky.social #NARDatabaseIssue | #AlphaFold #Protein #Structure #Database 2025: a redesigned interface and updated structural coverage | #Bioinformatics #Proteomics #OpenScience #AFDB 🧪🔓 CC/ @ebi.embl.org
⬇️
academic.oup.com/nar/advance-...

Mind-altering ‘brain weapons’ no longer only science fiction, say researchers UK academics say latest chemicals are ‘wake-up call’ and urge global action to stop weaponisation of neuroscience

Advances in neuroscience, pharmacology and artificial intelligence are coming together to create a new threat. We must fund scientists to counter defend.

www.theguardian.com/world/2025/n...

Cannot emphasize enough that if SETI picks up a signal that turns out to be DNA sequence, you absolutely do not under any circumstances synthesize that shit, this is why the good lord made AlphaFold

🧪 Training includes:
• Cryo-EM + SPA
• Protein purification + interaction assays
• Computational structural biology (AlphaFold, modelling pipelines)

Open to UK applicants and international candidates.
💰 Fully funded (UKRI rate stipend + fees).
📅 Deadline: 7 January 2026

PDB101: Register for the Nov 24 Virtual Office Hour on Exploring CSMs at RCSB.org PDB-101: Training, Outreach, and Education portal of RCSB PDB

Register for the Nov 24 Virtual Office Hour on Exploring CSMs at RCSB PDB
Learn how to use RCSB PDB features to navigate 3D Computed Structure Models from AlphaFold DB and ModelArchive

📢 Join us for the next GlySpace Alliance Webinar!

🗓️ Tuesday, December 2, 2025 | 10 AM ET
🎙️Dr. Kelley Moremen & Chin Huang present: “Modeling glycans with AlphaFold 3: capabilities, caveats, and limitations”
🗒️Details: wiki.glygen.org/GlySpace_All...

#glycotime #glygen #researchtools

Mind-altering ‘brain weapons’ no longer only science fiction, say researchers UK academics say latest chemicals are ‘wake-up call’ and urge global action to stop weaponisation of neuroscience

Advances in neuroscience, pharmacology and artificial intelligence are coming together to create a new threat. We must fund scientists to counter defend.

www.theguardian.com/world/2025/n...

How do out binders bind HRas selectively? Mapping the binding modes of our initial non-isoform selective was relatively easy. Alphafold predicted the site of binding, which we confirmed biochemically and by a really nice X-ray structure…9/n

Periodicity-aware deep learning for polymers - EUROPE SAYS Abramson, J. et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 630, 493–500 (2024).

Periodicity-aware deep learning for polymers

https://www.europesays.com/2581972/

Abramson, J. et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 630, 493–500 (2024). Article  Google…

Periodicity-aware deep learning for polymers - EUROPE SAYS Abramson, J. et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 630, 493–500 (2024).

Periodicity-aware deep learning for polymers

https://www.europesays.com/2581972/

Abramson, J. et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 630, 493–500 (2024). Article  Google…

Lewis Kay on NMR’s Expanding Role in the Post–AlphaFold Era, from Eastern Analytical Symposium EAS 2025 www.spectroscopyonline.com/view/lewis-k... #NMRchat 🧲

How Alphafold Has Changed Biology Research, 5 Years On Google's tool for predicting how proteins “fold” turns 5 this year. How is it fitting into biological research—and where is it going?

In 2020, Google’s AI lab released a tool called Alphafold that could predict how amino acids would fold into proteins under many different scenarios. Here’s where it—and its Nobel-winning team—are five years later.

AI Opportunity Inventory From improving healthcare outcomes and educational access to accelerating energy development and enhancing disaster response, AI presents profound opportunities. Our goal is to make these opportunitie...

law.utexas.edu/ai/ai-opport...

#gatherverse #menshealth #moneysummit2025 #foodsummit2025 #ai #xr #wellbeing #mentalhealth #financialhealth #futureofwork #futureoffood #virtualglobal #communitycare | Christopher Lafayette | 30 comme... Everyone deserves well-being, stability, And a full table. The next three conversations we host will touch what most people think about every single day: health, money, and nourishment. Our three ...

Everyone deserves well-being, stability, and a full table.

www.linkedin.com/posts/christ...

Scientific discovery and research is more important than trade, tariffs and terabytes. We’re in the most important time for funded research. I’d like to see the major AI platforms of the world unite to fund science.

A perpetual universal global fund for scientists is what’s needed today. Earth is in desperate need now more than ever to create frontier labs. With the new discoveries made by AI, it’s the scientists, most importantly, whom will need to handle these discoveries with practiced care.