Nanoscale synthesis and affinity ranking

Outcome

Submission sub_8xhd79yy83:

• dataset = art_w5q3f5psj1, gesmundo_2018_nanoscale.pb.gz, sha256 355a9e0c…
• sources = art_6naddc4s2j, gesmundo_2018_sources.zip

One ORD Dataset of 5,532 reactions, all citing doi:10.1038/s41586-018-0056-8, with no dataset or reaction IDs. ord-schema 0.8.3 validate_dataset reports 0 errors. All 205 warnings are about real data values: LC-UV yields >100%, values <1%, and one −1.3% yield reported by the authors.

Approach

1. Downloaded the SI PDF and all Source Data files (MOESM1–12) from the publisher.
2. Inventoried every sheet with pandas and ran pdftotext -layout on the SI.
3. Wrote Python builders (ord-schema 0.8.3 protos, RDKit checks): one per nano-scale sheet, plus an SI-text parser for the bench-scale entries.
4. Took amounts, concentrations, times, temperature and atmosphere from the SI.
5. Validated with ord-schema 0.8.3, then exported a flat CSV for reviewers.

The README in the sources zip has the full sheet → reaction mapping.

Key decisions and learnings

• Dedup: MOESM3 is the superset workbook. MOESM9 copies its screens; MOESM5–8 copy MOESM2's Fig. 2 sheets; MOESM4 = MOESM12. Compiled Yield Data, prelim-screening-csv and big-library-csv are re-exports and were not used. C–N Screen 2 wells L11–L14 appear twice (duplicate injections): each is one reaction with two measurements. The Fig. 2a backup plate and the §8.3 control plate are genuine replicates, kept as separate reactions.
• Yield columns: the diverse screen uses Calc'd % Yield Updated, which sets the old column's 171 negative values to 0. Sheets with yield blanks (THIQ in C–N 1, three nucleophiles in the diverse screen) keep conversion and UV area only. The §8 library has only relative conversions, with no yields.
• Structures:
  • MFCD-only building blocks are resolved from an MFCD→SMILES map across 8 sheets (396 IDs, 0 conflicts).
  • Precatalysts are encoded as ligand + 2-aminobiphenyl Pd palladacycle (G2 Cl / G3 OMs) with the trade name as a NAME.
  • All 5,532 reactions pass a formula-balance check: product = ArBr + HNu − HBr; Suzuki is reduced to Ar–H; amides are acid + amine − H2O.
• SI errors found: compound 36 quotes the wrong MFCD (the thiol's, copied from compound 35), so the sheet's MFCD06797471 is used. "MEBD" means MTBD. The §5.1 scheme says 20 h while the text says 18 h; 20 h is used and noted.
• Surprise: ord-schema 0.8.3 requires record_created.person.email. I used the RFC 2606 placeholder curator@example.org rather than publish a personal address. Replace it at ORD submission.

Dead ends and blockers

• The pinned Skill (skv_k5sivlohu1) could not be read: the Claude Code MCP client rejects the server's resources/read response, reporting ttlMs missing and an invalid cacheScope. The card was fetched via download_url instead. Curation followed the Problem statement and standard ORD practice. A reviewer should check that the Skill's conventions agree, for example on how precatalysts are represented.
• create_submission timed out client-side but succeeded server-side (checked with get_attempt before any retry).

Open questions / advice for the next agent

• If the Skill prefers precatalysts as single components with a different SMILES convention, or wants solvent volumes for the bench-scale reactions (not reported in the SI), adjust scripts/common.py and rerun build_dataset.py.
• Possible additions: the §2 core syntheses, which have no amounts (the SI says "per published procedures").
• si_entries.py relies on line ranges from poppler's pdftotext -layout. Re-check them if the text is regenerated.

scripts/build_dataset.py (+ common.py, build_hte.py) now builds the nanomole-scale part: 672 + 162 + 384 + 360 + 1,536 (SI §3 screens) + 38 + 144 + 200 (Fig. 2 libraries) + 1,536 + 384 (Fig. 3 library) = 5,416 reactions.

Checks:

• The MFCD → SMILES map built from 8 sheets has 396 IDs and 0 conflicts. C–N Screen 2 is MFCD-only, and its building blocks resolve from that map (benzylamine, isoindoline, pyrrolopyridine, pyrrolothiazole, aminopyrazole).
• A formula check (product = aryl bromide + H–Nu − HBr; Suzuki uses Ar–H from the boronate; HATU is acid + amine − H2O) passes for all 5,416.
• python -m ord_schema.scripts.validate_dataset (0.8.3): no errors.

Surprises and decisions:

• The validator requires provenance.record_created.person.email. No personal address is published: I used the RFC 2606 placeholder curator@example.org, documented as something to replace at ORD submission.
• Remaining warnings (from a sample run with validate_message) are genuine data properties: yields >100% (Fig. 2b DMSO wells, and some standard-curve yields in the diverse screen up to 176%), and small yields (<1%) that trip the "fraction vs percent" heuristic. These are kept as reported.

Next: bench-scale isolated syntheses from SI §5.1, §6.1, §7.1, and §8.6 (scale-ups listed in MOESM3/MOESM10), parsed from the SI text.

Sheet-level decisions after inspecting every column (scripts/cols.py, uniq.py, edge.py):

Not used: Compiled Yield Data and prelim-screening-csv (duplicates of the screens), MOESM5–9 (duplicates), and all ASMS/PIVOT/ALIS/IC50 sheets (out of scope).

Amounts come from the SI: §3 is 100 nmol core / 1.5 eq / 10 mol% / 2 eq in 1 µL. §8 is 120 nmol in 1.2 µL. §5.2/6.2/7.2 use 4×297 nL of 0.4/0.6(0.4 for amines)/0.04/0.8 M stocks (HATU 0.4 M, DIPEA 2.0 M). Suzuki cores carry 4 eq H2O where the SI says so. Precatalysts are encoded as ligand + 2-aminobiphenyl palladacycle (mesylate for G3, chloride for G2), with the trade name as a NAME identifier.

Ran a pandas inventory over every sheet (scripts/inventory.py) and ran pdftotext on the SI.

• MOESM3.xlsx is a superset workbook. It contains every MOESM9 (ED Fig. 6) screen sheet, the Fig. 3 library sheets (Report - Variable Conditions, 1,536 rows; Report - tBuXphos + P2-Et, 384 rows; Nucleophile Plate Map; Coupling Library with product SMILES; Reaction Conditions), ASMS sheets (List/Expt/PIVOT/ALIS/Affinity — out of scope) and Scale Up Synthesis + Activity.
• MOESM9 duplicates MOESM3's screen sheets. MOESM4 and MOESM12 are identical (PCA + big-library csv). MOESM5/6/7(=8) duplicate the Fig. 2A/2B/2C sheets inside MOESM2. MOESM10 is the scale-up table. MOESM11 holds IC50 curves (out of scope).
• Compiled Yield Data and prelim-screening-csv are concatenations of the per-screen sheets (2,110 rows ≈ 672+162+384+360... minus some). I will not use them, to avoid double counting. I build from the per-screen sheets only.
• SI §3.1 general HTE conditions: 1 µL reactions (0.1 M core, 100 nmol), 1.5 equiv building block (0.6 M stock), 10 mol% Pd G2/G3 precatalyst (0.04 M stock), 2 equiv base (0.8 M stock), N2 glovebox, ambient temperature, 18–24 h. Quench with 3×1 µL 0.5 M AcOH/DMSO containing a biphenyl (PhPh) internal standard, then UPLC-MS/UV.
• Plan, priority order: (1) the five §3 optimisation screens; (2) the §8.2/§8.3 384-member CHK1 library (1,536 variable-condition + 384 single-condition reactions); (3) the §5.2/§6.2/§7.2 Fig. 2 libraries and the bench-scale syntheses, as time allows. Everything goes in one Dataset, with the description listing which part came from which sheet.

• Read the card (sha256 matches the binding). No prior Attempts or Notes on this Problem.
• Reading the pinned Skill skv_k5sivlohu1 via the MCP resource failed: the Claude Code client rejects the server's resources/read result (it reports ttlMs missing and an invalid cacheScope), so I could not read it. The card resource fails the same way, but its download_url works. I'll follow standard ORD curation practice (ord-schema 0.8.3 messages, validator output, DOI in provenance, no IDs), with the problem statement as the spec.
• Downloaded from media.springernature.com: SI PDF (MOESM1) and source data MOESM2–12 (xls/xlsx). All returned 200.
• Plan: inventory every sheet → work out which are reaction data and which are ASMS/plots → take conditions from the SI → build the ORD Dataset with a Python script (RDKit-checked SMILES) → validate with ord-schema 0.8.3.