// Single-seq arm · high-confidence prediction · near@1

Near-perfect global structure. Still near@1, not strict.

2GIS is the best-quality structure in the v0.2 benchmark by both metrics that matter for the structure prediction step: pLDDT 0.822 and a backbone RMSD of 1.33 Åvs the deposited co-crystal. The rank-1 cluster nonetheless lands at 38% binding-site overlap: above near@1 (30%) but below strict@1 (50%). The pre-pilot screen correctly excludes MSA mode (min_id 0.780, no diverse tail).

Why this case matters: a near-perfect global fold is necessary but not sufficient for strict recovery. What ultimately decides overlap is which residues a cluster contacts — not just where its centroid sits. We surface both metrics so the customer can see when they decouple.

pLDDT
0.82
high
RMSD
1.3 Å
low
overlap
38%
near@1

Numbers from locked v0.2 benchmark ·  strict@K / near@K definitions

Example output — non-customer demo

RNA pocket discovery

SAM-I riboswitch · 2GIS

Bound by S-adenosyl-L-methionine (PDB ligand SAM). 94 nt RNA target.

v0.2 scope: cleft-binding RNA ≤500 nt|Pre-pilot screen: PASS
// pre-pilot screenPASSsingle-seq armmin_id 0.780 · 0.0% homologs at 70–80% identityNo diverse-tail homologs — MSA correctly excluded
Sequence length
94 nt
Conformers sampled
5
Structure pLDDT (mean)
0.822
Pocket clusters
5 / 11
passing persistence floor
SAM-I riboswitch predicted structure with top-3 candidate pockets highlighted
Predicted structure, top-3 pockets highlighted.Rank 1Rank 2Rank 3

Top-3 candidate pockets

ranked by persistence × binding-residue stability
#1Cluster 4persistence 100%
Geom. score
9.00
persistence × intersected
Residues (∩)
9
every frame
Residues (∪)
12
union, all frames
residues (union): 7, 8, 9, 10, 11, 12, 59, 60, 61, 62, 63, 64
residues (∩ all frames): 9, 10, 11, 12, 60, 61, 62, 63, 64
benchmark6/16 binding-site residues (38%) — near recovery
#2Cluster 0persistence 80%
Geom. score
8.80
persistence × intersected
Residues (∩)
11
every frame
Residues (∪)
15
union, all frames
residues (union): 23, 24, 25, 26, 27, 28, 29, 64, 65, 66, 67, 68, 85, 86, 87
residues (∩ all frames): 23, 24, 25, 26, 27, 28, 64, 65, 66, 67, 85
benchmark1/16 binding-site residues (6%)
#3Cluster 2persistence 100%
Geom. score
4.00
persistence × intersected
Residues (∩)
4
every frame
Residues (∪)
10
union, all frames
residues (union): 67, 68, 69, 70, 71, 80, 81, 82, 83, 84
residues (∩ all frames): 68, 69, 83, 84
benchmark0/16 binding-site residues (0%)
Rotate the structure yourself

Cartoon backbone of the predicted reference frame. Top-3 pocket residues highlighted as licorice; centroid spheres mark each cluster's geometric centre across the ensemble. Hover a card to isolate that pocket. Toggle the experimental SAM overlay to see where the co-crystal ligand sits relative to the rank-1 cluster.

Sequence with pocket residues highlighted

GGCUUAUCAAGAGAGGUGGAGGGACUGGCCCGAUGAAACCCGGCAACCAGAAAUGGUGCCAAUUCCUGCAGCGGAAACGUUGAAAGAUGAGCCA
Rank 1 pocket residuesRank 2 pocket residuesRank 3 pocket residuesknown binding-site residue

Methods summary

v0.2 detects cavities on the predicted 3D structure using RNA-tuned fpocket parameters (consistent with the published fpocketR approach, Veenbaas et al. PNAS 2025), samples a 5-frame ANM conformational ensemble, and ranks pockets by structural persistence weighted by binding-residue stability (score = persistence × n_residues_intersected). The cross-frame geometric ranker is the load-bearing contribution: on a 7-target cleft-binder benchmark, RNA-tuned detection alone recovers 0 of 7 at strict@1; the ensemble + ranker lifts recovery to 3 of 7 strict@1 and 6 of 7 near@1. Druggability assessment itself is left to your medicinal-chemistry workflow; we provide the geometric metadata and conformational stability metrics as inputs to it. Computational predictions only — experimental validation is required before use in drug development.

// rank-1 binding-site overlap, this target

fpocketR single-frame
6%NEITHER
v0.2 ensemble + ranker
38%NEAR

+32 pp · NEITHER → NEAR

Read full methodology →

Binding-mode caveat

Pipeline detects cleft-shaped binding pockets. Groove-binding modes and shallow surface-deformation binding may be missed. Contact us if your target's binding mode is groove-mediated.

Computational predictions only. Experimental validation required before drug-development use.