AlphaFold2 was apparently a trendline-breaking sudden jump in capability on protein structure prediction.

Judge as of 2020-12-12. True: CASP14 results show AlphaFold2 well above the historical trend of CASP performance (e.g. median GDT around 92 versus earlier progress), widely described as a discontinuous jump. Mostly true: a large jump that some analysts see as an acceleration partly anticipated by AlphaFold1, but still far above trend. Mixed: experts are seriously split on whether the gain broke the trend. Mostly false: the gain was large but roughly in line with the extrapolated trend after AlphaFold1. False: the CASP data show no unusual jump.

Set before the research began.

1. E1 Critical Assessment of Methods of Protein Structure Prediction (CASP) – Round XIV Proteins (author manuscript, PMC), by Kryshtafovych, Schwede, Topf, Fidelis, Moult · 27 March 2025

   “Astonishingly, the trend curve for CASP14 (the black straight-line) starts at a GDT_TS of about 95, and finishes at about 85 for difficult targets.”

2. E2 Critical Assessment of Methods of Protein Structure Prediction (CASP) – Round XIV Proteins (author manuscript, PMC), by Kryshtafovych, Schwede, Topf, Fidelis, Moult · 27 March 2025

   “In CASP13 (2018)18, with the introduction of effective deep learning methods, the trend line rose to above 60 on the GDT_TS scale, even for the most difficult targets, a major advance from the previous CASP.”

3. E3 Before and after AlphaFold2: An overview of protein structure prediction PMC (mini-review journal article) · 28 February 2023

   “Presented at CASP14 between May and July 2020, AlphaFold2 predicted protein structures with more accuracy than other competing methods, demonstrating a root-mean-square deviation (RMSD) among prediction and experimental backbone structures of 0.8Å versus the 2.8Å from the next best performing method.”

4. E4 Home Protein Structure Prediction Center (CASP, UC Davis, NIH/NIGMS-sponsored)

   “After the success of AlphaFold2 in CASP14 (2020), it was expected that deep learning methodology that brought monomeric modeling to qualitatively new level will be extended to multimeric modeling.”

The CASP14 assessment calls the result "astonishing": the CASP14 trend curve runs from a GDT_TS of about 95 down to about 85 for difficult targets (E1). At CASP13 the trend line had risen only to just above 60 for the hardest targets, and that was already called a major advance (E2). An independent review reports a backbone RMSD of 0.8Å for AlphaFold2, against 2.8Å for the next-best method (E3). The CASP organisers say AlphaFold2 brought monomeric modelling to a "qualitatively new level" (E4). Together these show a jump far above the earlier trend, and none of the evidence presents it as an expected extension of AlphaFold1.