#AlphaFoldDB now has binary protein complexes!
www.ebi.ac.uk/about/news/technology-an...
#AlphaFold #AlphaFold2 #StructuralBiology
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Hashtag
#AlphaFold2
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Exploring voltage-gated sodium channel conformations and protein-protein interactions using #AlphaFold2. New study from Diego Lopez-Mateos, Kush Narang, & Vladimir Yarov-Yarovoy (@vyy-sf.bsky.social) @ucd-physiology.bsky.social: rupress.org/jgp/article/...
#ProteinStructure #Biophysics #IonChannels
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🧬 Filamins act as cellular mechanosensors! Using #AlphaFold2, researchers mapped #proteins that bind only to the open, stress-exposed conformation of #Drosophila filamin Cheerio—revealing context-specific mechanosignaling interactions. 🔍
🔗 doi.org/10.1139/bcb-...
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Acta Cryst. D Structural Biology Section Editor Charles S. Bond contributes a Perspective on this article @ActaCrystD @IUCr #AlphaFold2 #DisorderPrediction #LowPLDDT doi.org/10.1107/S205...
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Major modes of behavior within low-pLDDT regions were identified through a survey of human proteome predictions provided by the AlphaFold Protein Structure Database #AlphaFold2 #StructurePrediction #ConditionalFolding doi.org/10.1107/S205...
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C. perfringens enterotoxin-claudin pore complex: Models for structure, mechanism of pore assembly and cation permeability. Computational and Structural Biotechnology Journal, DOI: https://doi.org/10.1016/j.csbj.2024.11.048
🔗 C. perfringens enterotoxin-claudin pore complex: Models for structure, mechanism of pore assembly and cation permeability. Computational and Structural Biotechnology Journal, DOI: doi.org/10.1016/j.cs...
📚 CSBJ: www.csbj.org
#StructuralBiology #AlphaFold2 #ProteinComplex #Claudin #Bioinformatics
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ProteinDJ logo
I am thrilled to release ProteinDJ: a high-performance and modular protein design pipeline. Our open-source workflow incorporates #RFdiffusion, #ProteinMPNN, #FAMPNN, #AlphaFold2 and #Boltz-2. It is a fast, free, and fun way to design proteins (1/5)
doi.org/10.1101/2025.09.24.678028 #proteindesign
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📣 New Podcast! "Farmaci e AI: promesse mancate e nuove speranze" on @Spreaker #ai #alphafold2 #farmaci
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2⃣ Featuring the second of our showcase projects
Through a combination of AlphaFold2 and other tools we are bypassing the limits of traditional MD simulations ➡️ bioexcel.eu/dvy3
#Proteins #MolecularDynamics #GROMACS #AlphaFold2
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One-shot design of functional protein binders with BindCraft #bindcraft #protein #design #molecularmodeling #modeling #ppis #alphafold2
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Bridging prediction and reality: Comprehensive analysis of experimental and AlphaFold 2 full-length nuclear receptor structures. Computational and Structural Biotechnology Journal, DOI: https://doi.org/10.1016/j.csbj.2025.05.010
🕵️ AlphaFold 2 predicts stability—but life runs on flexibility. Are we missing half the story?
🔗 Bridging prediction and reality: Comprehensive analysis of experimental and AlphaFold 2 full-length nuclear receptor structures. DOI: doi.org/10.1016/j.cs...
📚 CSBJ: www.csbj.org
#AlphaFold2 @csbj.org
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⭐NAR Breakthrough!⭐
AlphaFold2 predicted LSI–RDF interactions and experimentally validated several new functional pairs.
@phoeberice.bsky.social @femijohn.bsky.social
doi.org/10.1093/nar/...
#NARBreakthrough #SyntheticBiology #AlphaFold2 #GenomeEditing #ComputationalBiology
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We are at the inauguration of #ISMBECCB2025 Liverpool UK! Let’s begin with a fantastic keynote speaker! John Jumper, Nobel Prize dinner for the work with Google Deep Mind and #alphafold2
#proteins #structure #prediction #bioinformatics #ISMBECCB2025 #iscbsc
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The predicted 3D structures (top panels) and the Predicted Aligned Error (PAE) plots (bottom panels) for each candidate heterodimers scoring above 0.6.
🧪 May's most-read #Biochemistry paper used #AlphaFold2 to predict how proteins interact during egg development in fruit flies: buff.ly/d4qHMED
Have a paper people should see? See what our Editors look for: buff.ly/Haj0zKP
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Balancing Speed and Precision in Protein Folding: A Comparison of AlphaFold2, ESMFold, and OmegaFold
Hyskova, A., Marsalkova, E. et al.
Paper
Details
#ProteinFolding #AlphaFold2 #ESMFold
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MiniFold: Simple, Fast, and Accurate Protein Structure Prediction
Jeremy Wohlwend, Mateo Reveiz, Matt McPartlon, Axel Feldmann, Wengong Jin, Regina Barzilay
Action editor: Ole Winther
https://openreview.net/forum?id=1p9hQTbjgo
#protein #alphafold2 #esmfold
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New #Featured Certification:
MiniFold: Simple, Fast, and Accurate Protein Structure Prediction
Jeremy Wohlwend, Mateo Reveiz, Matt McPartlon, Axel Feldmann, Wengong Jin, Regina Barzilay
https://openreview.net/forum?id=1p9hQTbjgo
#protein #alphafold2 #esmfold
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Figure 1. Combining different treatments and baits determines different components of the TORC interactome. A) Scheme illustrating PUP-IT in the context of TOR signaling. PafA fused to the baits LST8-1, RAPTOR1, and ScFKBP labels individual and TOR complex associated protein interactors, while a GFP fusion acts as a control for unspecific interactions. B–E) Volcano plots showing proteins significantly enriched in LST8-1 B,D) and RAPTOR1 C,E) baits using constitutive B,C) or inducible D,E) FLAG::PUP(E) expression. F–G) Treatment-dependency of identified interactors using LST8-1 G) or RAPTOR1 H) baits and inducible FLAG::PUP(E) expression. Treatment-specific interactors are those only identified in one of the two treatments. H) Rapamycin response of WT and ScFKBP-producing seedlings (n = 10 seedlings). Bar height indicates group median. I) Volcano plot showing proteins significantly enriched in the ScFKBP bait using constitutive FLAG::PUP(E) expression. In all volcano plots, fold changes are calculated from n = 3 replicates using MsqRob2, p-values are corrected for multiple comparisons using the Benjamini–Hochberg FDR method. Different letters in panel (H) indicate statistically significant differences between groups based on a one-way ANOVA followed by a Tukey-HSD test (𝛼 = 0.05).
Figure 2. Identification of phosphorylated direct interactors of the TOR complex and in silico corroboration using AlphaFold2. A,B) Phosphorylated proteins enriched in LST8-1 and RAPTOR1 against the GFP control after 4 h A) and 24 h B) of sucrose treatment and FLAG::PUP(E) induction. Phosphorylation sites previously associated with TOR are indicated in blue, new sites in proteins previously reported to be phosphorylated by TOR in turquoise. Fold changes are calculated from n = 3 replicates using MsqRob2, p-values are corrected for multiple comparisons using the Benjamini–Hochberg FDR method. C,D) The two significantly enriched motifs among the identified phosphorylation sites. The “SP” motif C) mirrors previous reports from TOR substrates, while the “RxxS” motif D) has previously been associated with TOR downstream interactor S6K1. E) Interactions of 20 proteins from the four shown groups with the TORC components TOR, LST8-1, and RAPTOR1 were predicted using AlphaFold2 multimer. Vertical lines indicate the median of the local interaction score (LIS) distribution by group. F) Predicted structures of the top-scoring interactions for each group: newly identified TORC interactor PANK2, TORC subunit RAPTOR1, senescence regulator S40-7, and KIN10 paralog KIN11. Models are colored by predicted local distance difference test (pLDDT), with values above 70 indicating high confidence predictions.
Great work by Zheng et al. (2025) on how employing pupylation-based proximity labeling (PUP-IT) unravels a comprehensive #interactome of #Arabidopsis TOR complex.
Newly identified #PlantTOR interactors, like PANK2, were also supported by #AlphaFold2.
advanced.onlinelibrary.wiley.com/doi/10.1002/...
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#AF2BIND is a lightweight and efficient notebook designed for rapid inference on #AlphaFold2 outputs. After loading your protein into Copilot, click #FindPockets in the action box, and within seconds, the binding pockets will be displayed.
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Discover how #adversarialsequencemutations challenge #AlphaFold2 in protein tertiary structure prediction, streamlining biological experiments.
Read More: bit.ly/4j1UB8u
#Adversarialattack #Mutation #StructuralBiology #AMM #ActaMateriaMedica @scienceopen.bsky.social
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#AlphaFold2 found that ecRED1 had *six* candidate closure motifs. Careful biochemical analysis could only prove the veracity of one of these, but with the door open for the other motifs to be activated by post-translational modifications
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🔬 How does #AlphaFold2 perform with minimal sequence input?
"Dissecting AlphaFold2’s capabilities with limited sequence information" reveals insights into its ability to predict #ProteinStructures using structural templates without deep MSAs.
Read more: doi.org/10.1093/bioa...
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👪"Keeping it in the family: Using protein family templates to rescue low confidence AlphaFold2 models" demonstrates how high-confidence templates improve predictions within protein families. doi.org/10.1093/bioa... #StructuralBiology #AlphaFold2 #Bioinformatics @alexbateman1.bsky.social
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'Voorheen kostte het maanden tijd – en veel geld – om een eiwitstructuur te bepalen, met een methode die kristallografie heet. Nu kan dat in minuten dankzij AlphaFold.' Gemma Venhuizen
@gemmavenhuizen.bsky.social @nrcwetenschap.bsky.social #AlphaFold2 #scheikunde
www.nrc.nl/nieuws/2024/...
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@jazminrm.bsky.social on the early maize domestication.
For me the coolest bit was using #AlphaFold2 to peek at ancient maize WAXY1 protein variants 🙃
A180D mutation in Ozark maize sits on protein surface but doesn't change structure might affect phosphorylation of Y183 #archaeogenetics
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🧬 "Flexible fitting of AlphaFold2-predicted models to cryo-EM density maps using elastic network models" explores improving #AlphaFold2 predictions by refining models against #CryoEM maps. doi.org/10.1093/bioa... #StructuralBiology #Bioinformatics
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How many of the PDB models that were solved using experimental phasing could have been solved by molecular replacement using models obtained from AlphaFold? #MolecularReplacement #AlphaFold2 #ComputationalMethods t.co/s6EahtcYms
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Does anybody have an opinion on the benefits (or lack thereof) of the Ada generation (e.g. RTX 6000 Ada instead of RTX A6000) for a GPU workstation for AI tasks like #alphafold2 or #RFdiffusion?
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Accelerated computing is powering a new era in protein structure prediction, now with speed-of-light multiple sequence alignments.
#MMseqs2GPU now makes #AlphaFold2 predictions faster and more efficient than ever.
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developer.nvidia.com/blog/boost-a...
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