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1,167 claims from 736 papers are on the record. 43 have been checked so far; the other 1,124 have no check with a result yet.

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Status: Unchecked ×Keyword: AlphaFold ×Clear all

9 claims from 5 papers

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

   Highly accurate protein structure prediction with AlphaFold

   Jumper, Evans, Pritzel et al. · Nature · 2021

   The paper presents a redesigned AlphaFold neural network that predicts protein 3D structure from amino acid sequence, and reports that it regularly reached atomic accuracy in the CASP14 assessment.

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   1. UncheckedIn the CASP14 blind assessment, a redesigned AlphaFold predicted protein structures with accuracy competitive with experiments in most cases, far ahead of other methods.“We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14) 15 , demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other…”

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

   AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models

   Váradi, Anyango, Deshpande et al. · Nucleic Acids Research · 2021

   The paper presents AlphaFold DB, an open database of predicted protein structures, with over 360,000 structures across 21 model-organism proteomes at first release and planned expansion.

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   1. UncheckedThe AlphaFold database, built on DeepMind's AlphaFold v2.0, is described as greatly widening the share of known protein sequences with structural models.“Powered by AlphaFold v2.0 of DeepMind, it has enabled an unprecedented expansion of the structural coverage of the known protein-sequence space.”
   2. UncheckedAlphaFold DB's first release holds over 360,000 predicted protein structures from 21 model organisms, with expansion planned to most UniRef90 representative sequences.“The initial release of AlphaFold DB contains over 360,000 predicted structures across 21 model-organism proteomes, which will soon be expanded to cover most of the (over 100 million) representative sequences from the UniRef90 data set.”

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

   Improved protein structure prediction using potentials from deep learning

   Senior, Evans, Jumper et al. · Nature · 2020

   The authors trained a neural network to predict distances between amino acid residues, built a potential from them, and used it in AlphaFold, which performed well in the CASP13 blind assessment.

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   1. UncheckedA potential built from predicted residue distances can be optimised by simple gradient descent to produce protein structures, without complex sampling.“We find that the resulting potential can be optimized by a simple gradient descent algorithm to generate structures without complex sampling procedures.”
   2. UncheckedIn the CASP13 blind assessment, AlphaFold reached TM scores of 0.7 or higher on 24 of 43 free modelling domains; the next best method managed 14 of 43.“In the recent Critical Assessment of Protein Structure Prediction 5 (CASP13)-a blind assessment of the state of the field-AlphaFold created high-accuracy structures (with template modelling (TM) scores 6 of 0.7 or higher) for 24 out of 43 free modelling domains, whereas the next best method, which…”

4. Biochemistry, Genetics and Molecular Biology › Genomics and Rare Diseases

   Accurate proteome-wide missense variant effect prediction with AlphaMissense

   Cheng, Novati, Pan et al. · Science · 2023

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   1. Unchecked“By combining structural context and evolutionary conservation, our model achieves state-of-the-art results across a wide range of genetic and experimental benchmarks, all without explicitly training on such data.”
   2. Unchecked“The average pathogenicity score of genes is also predictive for their cell essentiality, capable of identifying short essential genes that existing statistical approaches are underpowered to detect.”
   3. Unchecked“As a resource to the community, we provide a database of predictions for all possible human single amino acid substitutions and classify 89% of missense variants as either likely benign or likely pathogenic.”

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

   Uncovering new families and folds in the natural protein universe

   Durairaj, Waterhouse, Mets et al. · Nature · 2023

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   1. Unchecked“By searching for novelties from sequence, structure and semantic perspectives, we uncovered the β-flower fold, added several protein families to Pfam database 2 and experimentally demonstrated that one of these belongs to a new superfamily of translation-tar…