Release month 2022-06

TM-score: how similar the two 3D shapes are overall, 0–1 (a random pair scores ~0.17, an identical fold ~1). Length-normalised so large and small proteins compare fairly. TM = (1/L) Σᵢ 1/(1 + (dᵢ/d₀)²) — dᵢ is the gap between the i-th aligned Cα atoms after best-fit superposition, and d₀ = 1.24(L−15)^⅓ − 1.8 sets the distance scale for length L. Ref: Zhang & Skolnick, Proteins 2004 doi:10.1002/prot.20264; computed with TM-align, doi:10.1093/nar/gki524.

pLDDT: AlphaFold's own confidence in each residue, 0–100 (higher = surer). It is the model predicting its own accuracy before ever seeing the experiment. We plot the per-structure mean. pLDDT = (1/N) Σᵢ pLDDTᵢ, where pLDDTᵢ is the network's confidence output for residue i.

FRAUD score: the headline number — how wrong the prediction was, weighted by how confident AlphaFold was, so a big error it was sure about counts most. FRAUD = (1/N) Σᵢ (pLDDTᵢ/100) · min(Δᵢ,15)/15, where Δᵢ is residue i's Cα distance from the experiment (Å) after superposition, capped at 15 Å. Runs 0 (perfect) to 1.

Novelty: how little AlphaFold had to go on — 100 minus the highest sequence identity between this protein and any structure released before the 2018-04-30 training cutoff. High = genuinely unseen (100% = nothing similar was ever in the training set). novelty = 100 − maxₚ identity(s, p) over pre-cutoff PDB chains p, with identity = 100 × (matching aligned residues)/(alignment length), from an MMseqs2 search.

Homology: the point colour. High novelty (above 70%) flags the sequence as novel (amber) — AlphaFold had no close template; otherwise a pre-cutoff homolog existed (blue) it could have learned the fold from. novel ⇔ novelty > 70%.

TM-score: overall shape match, 0–1 (above 0.5 = same fold, above 0.9 near-identical), length-normalised. TM = (1/L) Σᵢ 1/(1 + (dᵢ/d₀)²) with dᵢ the aligned-Cα gap after superposition and d₀ = 1.24(L−15)^⅓ − 1.8. Ref: Zhang & Skolnick, Proteins 2004 doi:10.1002/prot.20264.

Cα-RMSD: the average straight-line distance between matching backbone Cα atoms once the two structures are best-fit superposed (Å; lower is better, under ~2 Å excellent). RMSD = √( (1/N) Σᵢ |Pᵢ − (R·Qᵢ + t)|² ), with Pᵢ/Qᵢ the experimental/model Cα coordinates and R,t the rotation and translation from Kabsch superposition.

lDDT: local accuracy with no superposition — the fraction of short-range inter-residue distances the model reproduces, so it is not fooled by a single wrongly-placed domain. lDDT = (1/N) Σᵢ ¼ Σ_t 1[ |d_exp − d_model| < t ] over thresholds t ∈ {0.5, 1, 2, 4} Å and all residue pairs within 15 Å.

Mean TM-score: the month's average shape-match score. TM̄ = (1/M) Σ TM over the M structures deposited that month.

Trend line: a monotonic-trend test over the monthly means — Mann-Kendall (Kendall's τ) for significance, with a robust Theil-Sen slope for the line. Rank-based, so it tolerates the skewed TM distribution and noisy low-count months. Shown only when p < 0.05; otherwise a note reports that no significant trend was found.

Confidently wrong: the count that were both confident and wrong. count( mean pLDDT > 70 AND TM < 0.5 ).