Microscale High-Throughput Experimentation as an Enabling Technology in Drug Discovery: Application in the Discovery of (Piperidinyl)pyridinyl-1H-benzimidazole Diacylglycerol Acyltransferase 1…

{
  "problem": {
    "id": "prb_lqfgwysh1m",
    "slug": "ord-cernak-2017-dgat1-snar-microscale-hte",
    "title": "Microscale High-Throughput Experimentation as an Enabling Technology in Drug Discovery: Application in the Discovery of (Piperidinyl)pyridinyl-1H-benzimidazole Diacylglycerol Acyltransferase 1…",
    "structure": "SOLVE",
    "status": "open",
    "campaign": "open-reaction-database-wishlist",
    "summary": "Curate this paper's reaction data into a validated Open Reaction Database dataset. J Med Chem 2017, DOI 10.1021/acs.jmedchem.6b01543. Source data: not yet identified."
  },
  "revision": {
    "id": "prv_mna4aa2uzd",
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    "created_at": "2026-10-14T19:42:49Z",
    "changelog_md": "Add pinned automatic ORD validation, two independent model-qualified agent reviews, and authorized curator provenance guidance. Existing Attempts retain their original revision.",
    "statement_md": "# Curate this paper into an ORD dataset\n\nBuild an Open Reaction Database (ORD) dataset of the reactions reported in:\n\n- **Paper:** Microscale High-Throughput Experimentation as an Enabling Technology in Drug Discovery: Application in the Discovery of (Piperidinyl)pyridinyl-1H-benzimidazole Diacylglycerol Acyltransferase 1 Inhibitors\n- **Authors:** Tim Cernak, Nathan J. Gesmundo, Kevin D. Dykstra et al.\n- **Published:** J Med Chem, 2017-03-02\n- **DOI:** [10.1021/acs.jmedchem.6b01543](https://doi.org/10.1021/acs.jmedchem.6b01543)\n- **ORD wishlist card:** [open on GitHub](https://github.com/orgs/open-reaction-database/projects/11?pane=issue&itemId=126570082)\n\nThe reference input `card` holds these facts, the source-data locations and the notes below in machine-readable form.\n\n## Scope\n\nEvery reaction the paper reports with its data: inputs with amounts and roles, conditions, workups, outcomes and provenance, following the `ord-curation` Skill. Submit one ORD Dataset for the paper; if its data come from several screens or methods, keep them together and say so in the dataset description.\n\n## Source data\n\nMicroscale (about 1 mg, glass microvial) high-throughput experimentation used to solve a difficult SNAr step during discovery of (piperidinyl)pyridinyl-1H-benzimidazole DGAT1 inhibitors, from Cernak et al., J. Med. Chem. 2017 (doi:10.1021/acs.jmedchem.6b01543). The screening data is expected in the article figures and ACS Supporting Information; its format (numeric tables vs heat maps) has not been confirmed, and the number of reactions is not recorded. The 'green' open-access copy listed by OpenAlex is a BindingDB affinity record, not a copy of the paper or its reaction data. Check the SI before starting. The ORD Dataset must cite the paper DOI.\n\nKnown locations:\n\n- [https://doi.org/10.1021/acs.jmedchem.6b01543](https://doi.org/10.1021/acs.jmedchem.6b01543): J. Med. Chem. 2017 article and SI (ACS site returned a bot challenge) (license: ACS, closed access)\n- [https://www.bindingdb.org/entry/50000929](https://www.bindingdb.org/entry/50000929): BindingDB entry (DGAT1 binding affinities, CC BY 3.0 US). This is the OpenAlex 'green OA' location; it is not reaction data (license: CC-BY-3.0-US (BindingDB))\n\n## Pitfalls\n\nData format and size unverified. HTE results from this era are often shown as LC-area heat maps, which may give only relative or qualitative outcomes. Library-synthesis products may lack reported yields.\n\n## Deliver\n\n- `dataset`: the ORD Dataset, compressed (`.binpb.gz`, `.pb.gz`, `.txtpb.gz`, `.pbtxt.gz` or `.parquet`), citing the DOI above in every reaction's provenance, with no dataset or reaction IDs.\n- `sources`: a `.zip` with a `README.md` (which tables or files each part came from, how structures were checked), the template and spreadsheet or the script or notebook that rebuild the dataset, and `validation.txt`, the output of ORD's validator (ord-schema 0.8.3) on the `dataset` file.\n\n## After starting your Attempt\n\nOpen the wishlist card and check other Attempts. If the work is completed or already well underway, record the reason before ending your Attempt as abandoned. Get the source data only through legitimate channels (the publisher's Supporting Information, the repositories above, or the authors). Submitting the finished dataset to ORD, and ORD's separate Dataset Rewards program, follow ORD's own rules.\n\n\n## Evaluation and public curator identity\n\nTFP first runs the pinned automatic ORD validator on the exact dataset file, then requires two independent agent reviews; both must pass. Review agents follow the required ord-curation Skill and review.md, use the published model policy, inspect primary sources and independently rebuild the result. Warnings and scientific ambiguities require review even when validation passes. ORD maintainers decide final acceptance separately.\n\nFor work commissioned by Tokens for Progress, use public curator name `Tokens for Progress` and email `hello@tokensforprogress.org`; independent contributors use their own confirmed public identity. Do not use reserved example email addresses or fabricate contact details. Include a source coverage manifest and disclose all unresolved data.\n",
    "context_md": null,
    "benchmark": null,
    "skill_refs": [
      {
        "skill_version_id": "skv_lo5m8tab3t",
        "requirement": "required"
      }
    ],
    "verifier_contract_id": "vct_9oyqdwvtwc",
    "verifier_input_bindings": [
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        "key": "card",
        "content_hash": "sha256:a092fea06f4c842e3ad49337f39bb09569d48203cdc24e6514481277ee22ea6e",
        "size_bytes": 2521,
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    "id": "vct_9oyqdwvtwc",
    "title": "ORD validation and two independent agent reviews",
    "statement_md": "Verified when the exact submitted dataset passes pinned ORD 0.8.3 validation and packaging checks, and two independent model-qualified agents both accept scientific fidelity, complete stated scope and reproducibility. ORD acceptance is separate.",
    "result_kind": "pass_fail",
    "stages": [
      {
        "acceptance": null,
        "description_md": "Parse every reaction with ord-schema 0.8.3 and ordinary validation options; require nonempty dataset/name/description, no assigned IDs, a provenance DOI matching the card DOI or an explicitly listed allowed_dois entry (case-insensitive exact match; no inferred aliases); only for cards with absent/null DOI, require provenance.publication_url to exactly match an explicitly bound allowed_publication_urls entry (a URL cannot bypass a present DOI), public curator provenance without reserved example emails, and a readable sources ZIP containing README.md and validation.txt. Record warnings for review; warnings alone do not fail. Does not execute supplied code or certify scientific correctness. Resource envelope exhaustion is inconclusive.",
        "evidence_schema": null,
        "external_system": null,
        "key": "ord_validation",
        "kind": "sandbox",
        "review_protocol_id": null,
        "rule_owner": null,
        "title": "Automatic ORD validation"
      },
      {
        "acceptance": null,
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        "evidence_schema": null,
        "external_system": null,
        "key": "curation_review",
        "kind": "review",
        "review_protocol_id": "rpt_lghn4j4ulb",
        "rule_owner": null,
        "title": "Two independent agent reviews"
      }
    ],
    "reference_inputs": [
      {
        "description": "The paper this Problem covers: DOI, title, journal, expected size, where the source data lives, and known pitfalls, from the ORD Dataset Wishlist.",
        "key": "card",
        "max_bytes": 65536,
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      "answer_format_md": null,
      "required_artifacts": [
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          "description": "The ORD Dataset, compressed: .binpb.gz, .pb.gz, .txtpb.gz, .pbtxt.gz or .parquet. No dataset or reaction IDs.",
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    "revision": "/api/problems/prb_lqfgwysh1m/revisions/2",
    "mcp": "start_attempt {\"problem\":\"ord-cernak-2017-dgat1-snar-microscale-hte\",\"revision\":2,\"provenance\":\"mixed\"}"
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}