Open_Fold_Challenge / README.md
John-Burden's picture
Upload README.md
5d5e821 verified
|
Raw History Blame Contribute Delete
7.35 kB
---
license: cc-by-4.0
tags:
- structure-prediction
- protein-ligand
- zika
- openbind-challenge
---
# OpenBind Blind Challenge 1 — Method Report
**Track:** Structure Prediction
**Target:** Zika virus NS2B-NS3 protease
**Compounds:** 400 / 400 submitted
---
## Summary
Poses were generated by **MCS-guided template transfer followed by protein-aware
constrained minimisation**. No GPU was used for the submitted poses. Co-folding
(Boltz-2, OpenFold3) was evaluated and rejected on measured performance; its results
are reported below as negative findings.
The method is conditional rather than general: where a close structural analogue
exists among deposited ZIKV protease complexes it is accurate, and where one does not
it fails. That bimodality is quantified below rather than averaged away.
## Pipeline
1. **Receptor ensemble.** All ZIKV NS2B-NS3 entries were retrieved from the RCSB by
sequence search on the 168-residue NS3 construct and superposed on 29HN (apo,
closed, 1.774 A, P4(3)22 — the challenge crystal form) by NS3 Calpha, with residue
correspondence established by sequence alignment rather than residue number.
195 of 200 members superposed within 1.0 A (median Calpha RMSD 0.253 A).
The pocket has one meaningful degree of freedom, a bimodal Tyr161 rotamer, so two
receptors are carried: 7H1Z (majority rotamer) and 7HOQ (minority).
2. **Template library.** 129 orthosteric ligand poses extracted in the common frame,
disjoint from the validation set. Peptidomimetics, covalent adducts and macrocycles
were excluded as unrepresentative of the blinded compound set.
3. **Template selection.** For each compound, an ECFP4 prefilter over the library
followed by `rdFMCS` (ringMatchesRingOnly, completeRingsOnly, CompareElements /
CompareOrderExact). The donor maximising **MCS coverage** — matched atoms divided by
query heavy atoms — is chosen.
4. **Pose transfer.** Constrained embedding (ETKDGv3 with `coordMap`) pins the MCS
atoms onto the donor's crystallographic coordinates; MMFF relaxation with position
constraints on the pinned atoms completes the remainder. Pinned atoms land a median
0.002 A from their template positions.
5. **Protein-aware minimisation.** The MMFF relaxation above has no protein term, so
peripheral atoms are drawn back into the receptor. Every protein heavy atom within
6 A is added to the force field as a fixed extra point and flat-bottom distance
restraints push any too-close pair out to 0.80 x (sum of van der Waals radii), while
MCS atoms are held to 0.30 A of slack. Median displacement 0.32 A.
6. **Assembly.** Receptor chains A (NS2B) and B (NS3) plus the ligand as a single
`LIG` residue in chain C, waters stripped, explicit CONECT records. The receptor is
chosen per compound to match the donor's Tyr161 rotamer.
## Validation
Tuning and evaluation used a **held-out benchmark of 41 public ZIKV NS2B-NS3 holo
structures**, disjoint from the template library, scored with OpenStructure
(`SCRMSDScorer`, `LDDTPLIScorer`) and PoseBusters under the challenge's conjunction:
BiSyRMSD < 1.5 A **and** lDDT-PLI > 0.8 **and** all PoseBusters checks. No leaderboard
feedback was used at any point.
A calibration of the three gates under rigid displacement showed that **lDDT-PLI binds
before BiSyRMSD**: at 1.25 A displacement the RMSD gate still passes 100% while
lDDT-PLI passes about a third. The effective accuracy requirement is nearer 1.1 A than
the nominal 1.5 A.
### Head-to-head, 41-complex benchmark
| method | passes all three gates |
|---|---|
| Boltz-2, rank-0 sample | 24.4% |
| Boltz-2, oracle over 5 samples | 34.1% |
| Boltz-2 with pocket restraints | 19.5% |
| Template transfer | 34.1% |
| **Template transfer + protein-aware minimisation** | **39.0%** |
Boltz-2's 34.1% requires selecting the correct sample out of five, which its confidence
score does not support (Spearman -0.59 against RMSD). The template method emits one
pose, so its figure needs no selector.
### Performance is conditional on template precedent
| MCS coverage | benchmark pass rate | compounds in this submission |
|---|---|---|
| >= 0.8 | 88% (15/17) | 220 |
| 0.6 - 0.8 | 9% | 116 |
| < 0.6 | 0% | 64 |
MCS coverage is a usable *a priori* selector (Spearman -0.80 against BiSyRMSD), known
before any compute is committed. Median coverage across the submission is 0.818.
## Negative results
Reported because they constrain what the remaining gap is, not as asides.
- **Pocket restraints degrade co-folding.** A paired run (identical seed and inputs;
the unrestrained YAML is a strict text prefix of the restrained one) restraining the
ligand to within 6 A of 25 pocket residues moved Boltz-2 from 25.9% to 19.0%.
`minimum_distance_to_protein` failures rose from 44 to 69 of 205 models: the
restraint drives the ligand too deep.
- **Co-folding does not complement template transfer.** Stratified by MCS coverage,
Boltz-2's oracle is 18% below 0.8 and 59% above it — the same compounds are hard for
both. A hybrid adds little.
- **Free docking is the worst option tested.** On the 22 low-coverage benchmark
complexes, smina produced 0/22, scoring zero on *both* accuracy gates with a
PoseBusters pass rate of 31.8%, against 4.5% and 54.5% for template transfer.
- **Anchored search** (MCS core pinned, 60 conformers of the remainder ranked by the
smina scoring function) gave 2/22 versus 1/22 — a sound mechanism but not a solution
at this sample size.
## Limitations
- Roughly 180 of the 400 compounds fall below 0.8 MCS coverage, where no method tested
here exceeds ~10%. They are chemically novel rather than small (median 23-25 heavy
atoms, Tanimoto 0.25-0.46 to their nearest donor).
- 56% of benchmark poses still exceed the 1.5 A RMSD gate after minimisation; the
method is not generally accurate.
- Minimised poses remain less physically clean than co-folded ones (PoseBusters 71.8%
versus 78.1% for plain Boltz-2).
- The improvement from minimisation (+2 compounds of 39) is not statistically
significant on its own (paired exact test, p = 0.25); it is adopted on mechanism and
on the absence of any regression, not on the delta.
- Performance depends on an unusually dense structural prior for this target (196
liganded entries, one dominant crystal form, a rigid pocket). It would not transfer
to a target with few co-crystals.
## Data and code declarations
- **Proprietary data: none.** Every structure used is a public RCSB deposition and
every compound SMILES came from the challenge distribution.
- **Training data leakage:** not applicable to the submitted poses, which come from
template transfer rather than a learned model. For the co-folding comparisons,
benchmark structures were checked against each engine's training cutoff by
*deposition* date (the conservative choice); all 42 fall outside the Chai-1, AF3 and
OpenFold3 windows. Benchmark co-folding runs used `--use-templates false` to prevent
inference-time retrieval of the reference structures.
- **Software:** RDKit, OpenStructure, PoseBusters, gemmi, smina, Boltz-2 (v2.2.1),
OpenFold3-preview — all open source.