AlphaFold2 achieved atomic accuracy at CASP14 in 2020.

Judged as of 2024-12. True if CASP14 assessors' reports, the CASP14 results or peer-reviewed papers (e.g. Jumper et al. 2021, Nature) describe AlphaFold2's CASP14 (2020) predictions as reaching atomic or near-atomic accuracy. A benchmark is a median backbone RMSD of about 1 Å or a median GDT around 90 or more. Mostly true if sources describe the accuracy as 'competitive with experimental' or 'near-atomic' for most targets but not all. Mostly false if it was only the top performer, without accuracy approaching the atomic level. False if AlphaFold2 did not compete at CASP14 or performed poorly.

Set before the research began.

1. E1 Critical Assessment of Methods of Protein Structure Prediction (CASP) – Round XIV Proteins (author manuscript, PMC); Kryshtafovych, Schwede, Topf, Fidelis, Moult (CASP assessors and Prediction Center)

   “One research group, AlphaFold2 from the company DeepMind, submitted models competitive with experimental accuracy for at least 2/3 of the targets”

2. E2 Critical Assessment of Methods of Protein Structure Prediction (CASP) – Round XIV Proteins (author manuscript, PMC); Kryshtafovych, Schwede, Topf, Fidelis, Moult (CASP assessors and Prediction Center)

   “In CASP14, about 2/3 of the 96 targets reached GDT_TS values greater than that, and so are considered competitive with experiment in backbone accuracy.”

3. E3 Applying and improving AlphaFold at CASP14 - PMC Proteins (PMC); Jumper, Evans, Pritzel et al. (DeepMind) · 24 November 2021 Own record

   “The predictions made by AlphaFold had a median domain GDT_TS of 92.4”

4. E4 Highly accurate protein structure prediction with AlphaFold - Nature Nature · 15 July 2021 Own record

   “AlphaFold structures had a median backbone accuracy of 0.96 Å r.m.s.d.95”

The independent CASP14 assessors' overview says AlphaFold2 submitted models competitive with experimental accuracy for at least two-thirds of the targets (E1, E2). The peer-reviewed Jumper et al. 2021 Nature paper, which the criteria name directly, reports a median backbone accuracy of 0.96 Å r.m.s.d.95 (E4). That meets the benchmark of about 1 Å. The DeepMind Proteins paper reports a median domain GDT_TS of 92.4 (E3), which is above the benchmark of about 90. E3 and E4 come from the subject's own group. The independent assessors report that AlphaFold2 was competitive with experimental accuracy for at least two-thirds of the targets [E1][E2], which is consistent with them, and the median domain GDT_TS of 92.4 for AlphaFold's CASP14 predictions in the peer-reviewed E3 meets the benchmark for true.