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1,248 claims from 785 papers are on the record. 46 have been checked so far; the other 1,202 have no check with a result yet.

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Keyword: AlphaFold2 ×Clear all

15 claims from 10 papers

1. Biochemistry, Genetics and Molecular Biology › Protein Structure and Dynamics

   Highly accurate protein structure prediction for the human proteome

   Tunyasuvunakool, Adler, Wu et al. · Nature · 2021

   The authors applied AlphaFold 2 to almost the whole human proteome (98.5% of human proteins), greatly expanding structural coverage, and released the predictions freely.

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   1. UncheckedAlphaFold predictions for the human proteome gave a confident structure for 58% of amino-acid residues, and very high confidence for 36%.“The resulting dataset covers 58% of residues with a confident prediction, of which a subset (36% of all residues) have very high confidence.”

2. Biochemistry, Genetics and Molecular Biology › Protein Structure and Dynamics

   Improved prediction of protein-protein interactions using AlphaFold2

   Bryant, Pozzati and Elofsson · Nature Communications · 2022

   The authors applied AlphaFold2 to predict heterodimeric protein complexes, and built a score from the predicted interfaces to judge model quality and to tell interacting from non-interacting protein pairs.

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   1. UncheckedAlphaFold2 with optimised sequence alignments produced acceptable-quality models (DockQ ≥ 0.23) for 63% of the heterodimeric protein complexes tested.“We find that the AlphaFold2 protocol together with optimised multiple sequence alignments, generate models with acceptable quality (DockQ ≥ 0.23) for 63% of the dimers.”
   2. Unchecked“From the predicted interfaces we create a simple function to predict the DockQ score which distinguishes acceptable from incorrect models as well as interacting from non-interacting proteins with state-of-art accuracy.”

3. Biochemistry, Genetics and Molecular Biology › Protein Structure and Dynamics

   A structural biology community assessment of AlphaFold2 applications

   Akdel, Pires, Porta‐Pardo et al. · Nature Structural & Molecular Biology · 2022

   The authors assessed how well AlphaFold2 protein structure predictions work across several structural-biology applications, and conclude they are likely to have a transformative impact.

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   1. UncheckedAcross 11 proteomes, AlphaFold2 could confidently model on average 25% more residues than homology modelling, including features rarely seen in the Protein Data Bank.“For 11 proteomes, an average of 25% additional residues can be confidently modeled when compared with homology modeling, identifying structural features rarely seen in the Protein Data Bank.”

4. Biochemistry, Genetics and Molecular Biology › Protein Structure and Dynamics

   Learning inverse folding from millions of predicted structures

   Hsu, Verkuil, Liu et al. · bioRxiv (Cold Spring Harbor Laboratory) · 2022

   The authors enlarge the training data for inverse folding, predicting a protein sequence from its backbone, by about three orders of magnitude using 12M AlphaFold2-predicted structures.

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   1. UncheckedTrained on millions of AlphaFold2-predicted structures, a transformer recovers 51% of native sequences on held-out backbones, about 10 points above existing methods.“Trained with this additional data, a sequence-to-sequence transformer with invariant geometric input processing layers achieves 51% native sequence recovery on structurally held-out backbones with 72% recovery for buried residues, an overall improvement of almost 10 percentage points over existing…”

5. Biochemistry, Genetics and Molecular Biology › Protein Structure and Dynamics

   OpenFold: retraining AlphaFold2 yields new insights into its learning mechanisms and capacity for generalization

   Ahdritz, Bouatta, Floristean et al. · Nature Methods · 2024

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   1. Unchecked“We find that OpenFold is remarkably robust at generalizing despite extreme reductions in training set size and diversity, including near-complete elisions of classes of secondary structure elements.”

6. Biochemistry, Genetics and Molecular Biology › Protein Structure and Dynamics

   OpenFold: retraining AlphaFold2 yields new insights into its learning mechanisms and capacity for generalization

   Ahdritz, Bouatta, Floristean et al. · Nature Methods · 2024

   The authors present OpenFold, a trainable open implementation of AlphaFold2, and use it to study how the model generalises and how it learns to fold proteins.

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   1. UncheckedThe authors say OpenFold, trained from scratch by them, matches the prediction accuracy of AlphaFold2.“We train OpenFold from scratch, matching the accuracy of AlphaFold2.”
   2. Unchecked“Having established parity, we find that OpenFold is remarkably robust at generalizing even when the size and diversity of its training set is deliberately limited, including near-complete elisions of classes of secondary structure elements.”
   3. UncheckedLooking at structures OpenFold produced during training gives insight into how it learns to fold proteins in a hierarchical manner.“By analyzing intermediate structures produced during training, we also gain insights into the hierarchical manner in which OpenFold learns to fold.”

7. Computer Science › Computational Drug Discovery Methods

   AlphaFold2 structures guide prospective ligand discovery

   Lyu, Kapolka, Gumpper et al. · Science · 2024

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   1. Unchecked“Hit rates were high and similar for the experimental and AF2 structures, as were affinities.”
   2. Unchecked“Determination of the cryo–electron microscopy structure for one of the more potent 5-HT2A ligands from the AF2 docking revealed residue accommodations that resembled the AF2 prediction.”

8. Biochemistry, Genetics and Molecular Biology › Protein Structure and Dynamics

   Easy and accurate protein structure prediction using ColabFold

   Kim, Lee, Karin et al. · Nature Protocols · 2024

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   1. Unchecked“ColabFold-AF2 shortens turnaround times of experiments because of its optimized usage of AF2's models.”
   2. Unchecked“Using Google Colaboratory, it takes <2 h to run each procedure.”

9. Biochemistry, Genetics and Molecular Biology › Protein Structure and Dynamics

   Structure prediction of alternative protein conformations

   Bryant and Noé · Nature Communications · 2024

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   1. Unchecked“Over 50% of experimentally known nonredundant alternative protein conformations evaluated here are predicted with high accuracy (TM-score > 0.8).”

10. Biochemistry, Genetics and Molecular Biology › Protein Structure and Dynamics

    From interaction networks to interfaces, scanning intrinsically disordered regions using AlphaFold2

    Bret, Gao, Zea, Andréani and Guérois · Nature Communications · 2024

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    1. Unchecked“Using a dataset of protein-peptide complexes involving intrinsically disordered regions that are non-redundant with the structures used in AlphaFold2 training, we show that when using the full sequences of the proteins, AlphaFold2-Multimer only achieves 40%…