Top Tweets for #AlphaFill
@Robbie_Joosten @kasikp @olexandr @tkapler @A_Aspuru_Guzik @kopeckyk @ProfvLilienfeld Good, I like ligands in #AlphaFill more than in #AF3 :)
I have made an animation of the cover of @Ida_deVries's Interview. It makes me feel so calm when I'm watching it, am I the only one?
Wouldn't be nice to have short videos on the website version @Chem2W ?
#AlphaFold #AlphaFill @NKI_nl @TassosPerrakis
▶️Listen to the article "AlphaFill- enriching AlphaFold models with ligands and cofactors" by M. Hekkelman, A. Perrakis et al. https://t.co/5PpZa5uamb 🔊 @TassosPerrakis @Robbie_Joosten @Ida_deVries
#AlphaFill
#AlphoFold
#PubReading #Podcast 🎙️
@nanome_inc @Robbie_Joosten @instructhub @Nature #AlphaFill is great - and has been around for a while, but not *the* answer to placing ligands in protein structures. It can place co-factors - when there is sufficient similarity to existing (experimentally determined) structures with these co-factors present, AFAIK.
The downside of #AlphaFold is that it does not predict ligands. Not anymore. @Robbie_Joosten & @TassosPerrakis at @instructhub developed #AlphaFill: an algorithm 'fills' the empty binding pockets of protein predictions ✨Published @Nature https://t.co/oNleA6E4tW
Biochemists Present AlphaFill, An Upgraded Version Of AlphaFold For Protein Folding.
#DeepMind #AlphaFold #ESMFold #proteinfolding #AlphaFill
https://t.co/pEAQNg1GCb
Our publication on 3D-Beacons (https://t.co/Whltd9mkU3), an easy-to-use platform for finding protein structure models from groups like #AlphaFoldDB, #AlphaFill,
@SWISS_MODEL, @PDBeurope, and more is now available in @GigaScience: https://t.co/zndvRaAhIW
Our paper on 3D-Beacons (https://t.co/mG8ZFOQQVE), an easy-to-use platform for finding protein structure models from groups like #AlphaFoldDB, #AlphaFill, @SWISS_MODEL , @PDBeurope, and more is now available in GigaScience: https://t.co/9npH1QqksR
#AlphaFill is pretty cool. We have been using it since the preprint and help to identify the AF models for which we need to include cofactor remodeling in our works.
Amazing talks including #Bertiniaward recipient @SjorsScheres, @instructhub director @Schwalbe_BMRZ , @PetzoldKatja and many more
And what about @Ida_deVries describing #AlphaFill: Enriching the AlphaFold models with ligands and co-factors
Well deserved! #AlphaFill
Since #coffee we've had super cool talk from #PetrLeiman complete w #molecular #movies on #contractile #injection #systems & now an excellent person I've just met @Ida_deVries @nki_nl on #AlphaFill a way to put #metals & #cofactors into #AlphaFold #models
Our #3DBeacons publication is now on BioRxiv! This federated network provides access to experimental and predicted protein structures including:
#AlphaFoldDB #AlphaFill #SWISSMODEL @proteinEnsemble @genome3d #HegeLab #Isoformio #SASBDB #ModelArchive
🔗https://t.co/zj1OGiulXM
Our publication describing #3DBeacons is now on @biorxivpreprint! You can now easily get protein structures from many different data providers like @PDBeurope, #AlphaFoldDB, #AlphaFill and many others using a single entry point!
https://t.co/v3srvajLZk
Seeing #AlphaFoldDB models next to other predicted structures and PDB entries at #PDBeKB show the best of all worlds! For example, #AlphaFill has ligands #AlphaFoldDB lack, #ModelArchive has complexes, and the @proteinEnsemble provides conformational ensembles, all on one page!
You can access predicted protein structures, including structures from #AlphaFoldDB, alongside PDB data at the #PDBeKB aggregated views. See more below or try it yourself:
🔗https://t.co/4BYspPGTbY
Alphafold open many opportunities Ida de Vries uses #PDB_REDO to expand its capabilities #alphafill
Work being presented now at the @instructhub Biennial Conference #ibsbc2022
We've enriched #PDBeKB pages with data from AlphaFill, which 'transplants' ligands and co-factors into #AlphaFold models giving more complete context for the predicted structure - developed by @TassosPerrakis & @Robbie_Joosten of @NKI_nl. Try it at https://t.co/FeJUT3pJ42
They already are... #alphafill
Very interesting @biorxivpreprint by the groups of @TassosPerrakis and @Robbie_Joosten @NKI_nl. They used homology information to "transplant" ligands from experimental structures into ligand-free #AlphaFold predicted structures using #AlphaFill. https://t.co/1xArG58vXa
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