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1,005 claims from 629 papers are on the record. 39 have been checked so far; the other 966 have no check with a result yet.

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Status: Unchecked ×Keyword: protein structure prediction ×Clear all

11 claims from 7 papers

1. 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

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   1. Unchecked“Powered by AlphaFold v2.0 of DeepMind, it has enabled an unprecedented expansion of the structural coverage of the known protein-sequence space.”
   2. Unchecked“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.”

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

   Evolutionary-scale prediction of atomic-level protein structure with a language model

   Lin, Akin, Rao et al. · Science · 2023

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   1. Unchecked“We demonstrate direct inference of full atomic-level protein structure from primary sequence using a large language model.”

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

   Protein complex prediction with AlphaFold-Multimer

   Evans, O’Neill, Pritzel et al. · bioRxiv (Cold Spring Harbor Laboratory) · 2021

   Unchecked3 claims
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   1. Unchecked“On a benchmark dataset of 17 heterodimer proteins without templates (introduced in [2]) we achieve at least medium accuracy (DockQ [3] ≥ 0.49) on 13 targets and high accuracy (DockQ ≥ 0.8) on 7 targets, compared to 9 targets of at least medium accuracy and 4…
   2. Unchecked“For heteromeric interfaces we successfully predict the interface (DockQ ≥ 0.23) in 70% of cases, and produce high accuracy predictions (DockQ ≥ 0.8) in 26% of cases, an improvement of +27 and +14 percentage points over the flexible linker modification of Alp…
   3. Unchecked“For homomeric inter-faces we successfully predict the interface in 72% of cases, and produce high accuracy predictions in 36% of cases, an improvement of +8 and +7 percentage points respectively.”

4. 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

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   1. Unchecked“We find that the resulting potential can be optimized by a simple gradient descent algorithm to generate structures without complex sampling procedures.”
   2. Unchecked“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 doma…

5. 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

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   1. Unchecked“The resulting dataset covers 58% of residues with a confident prediction, of which a subset (36% of all residues) have very high confidence.”

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

   Simulating 500 million years of evolution with a language model

   Hayes, Rao, Akin et al. · Science · 2025

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   1. Unchecked“Among the generations that we synthesized, we found a bright fluorescent protein at a far distance (58% sequence identity) from known fluorescent proteins, which we estimate is equivalent to simulating 500 million years of evolution.”

7. 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

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   1. Unchecked“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.”