# Curate this paper into an ORD dataset

Build an Open Reaction Database (ORD) dataset of the reactions reported in:

- **Paper:** Data-Driven Multi-Objective Optimization Tactics for Catalytic Asymmetric Reactions Using Bisphosphine Ligands
- **Authors:** Jordan J. Dotson, Lucy van Dijk, Jacob C. Timmerman et al.
- **Published:** Journal of the American Chemical Society, 2022-12-27
- **DOI:** [10.1021/jacs.2c08513](https://doi.org/10.1021/jacs.2c08513)
- **ORD wishlist card:** [open on GitHub](https://github.com/orgs/open-reaction-database/projects/11?pane=issue&itemId=126570033)

The reference input `card` holds these facts, the source-data locations and the notes below in machine-readable form.

## Scope

Every reaction the paper reports with its data (the wishlist estimates about 63 reactions; mostly DFT but some HTE): 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.

## Source data

The paper is mainly computational (DFT ligand parameterization and statistical modeling), with a modest experimental HTE component. Experimental data: GitHub SigmanGroup/Multiobjective_Optimization (CC0-1.0), file Logistic_Regression/Example_Rxn_Data.xlsx. It has 63 rows of bisphosphine ligand name, library ID and conversion (%). The file has no SMILES, substrates or conditions. Ligand structures must be assigned from names with the correct absolute configuration: BPE, DuPhos, Josiphos and Walphos families, and others. The larger parameter spreadsheets in the repo (7 MB) may help map IDs. The substrate, product, catalyst precursor, conditions and analysis method come from the paper and its SI (JACS, 10.1021/jacs.2c08513; NIH author manuscript PMC10194998). Check whether the paper reports enantioselectivity for these experiments that the spreadsheet omits. Do not include DFT or computed data in the ORD dataset.

Known locations:

- [https://github.com/SigmanGroup/Multiobjective_Optimization/blob/HEAD/Logistic_Regression/Example_Rxn_Data.xlsx](https://github.com/SigmanGroup/Multiobjective_Optimization/blob/HEAD/Logistic_Regression/Example_Rxn_Data.xlsx): Sheet 'Data': 63 rows of ligand name (e.g. (R,R)-Ph-BPE), ligand library ID (e.g. 251_1) and Conversion. No SMILES and no ee column. (license: CC0-1.0)
- [https://github.com/SigmanGroup/Multiobjective_Optimization](https://github.com/SigmanGroup/Multiobjective_Optimization): Repo with the bisphosphine parameter library (Parameters_10_21_22.xlsx 7.2 MB; Logistic_Regression/Bisphosphine_Parameters.xlsx 6.6 MB; neither downloaded) and DFT logs. It may help map ligand IDs to structures. (license: CC0-1.0)
- [https://pmc.ncbi.nlm.nih.gov/articles/PMC10194998/](https://pmc.ncbi.nlm.nih.gov/articles/PMC10194998/): Author manuscript (NIH), needed for reaction scheme, substrate, conditions, HTE protocol and any ee/selectivity data (license: unknown (author manuscript; publisher ACS))

## Pitfalls

Ligand identity is given only as names or IDs, so stereochemistry-sensitive SMILES assignment is error-prone. Only conversion is present in the file, and the multi-objective data (e.g. ee) may be elsewhere or absent. It is unclear whether all 63 points share one reaction.

## Deliver

- `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.
- `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.

## Before you start

Open the wishlist card. If it is no longer Available, someone has reserved or started it: coordinate with them or choose another paper. 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.