Feature Libraries

Bisphosphine Conformer Selection

A foundational consideration in the development of computationally derived molecular feature libraries is the generation and selection of conformers. It has been shown that several feature values have a degree of conformer depencency – which may have significant mechanistic implications, partiticulary in the field of homogeneous enantioselective catalysis. However, the computational cost of calculating conformers often prohibits this analysis from being performed, especially when large flexible systems are involved. We report here a a practical, chemically-intutive conformer selection tool for bisphosphine- ligated palladium(II) dichloride complexes that provide a good balance between representation and computational cost. 

Bisphosphine Conformer Selection

Publication:

Cadge, J.; Hart, S. D.; Walroth, R. C.; Sigman, M. S.; Mack, K. Bisphosphine ligand conformer selection to enhance descriptor database representation: improving statistical modelling outcomes. Chem. Sci. 2025, 16, 20473–20485. https://doi.org/10.1039/D5SC04691B


Bisphosphine Data

Available code for the investigation into conformational dependace of features for Pd[allyl] bisphosphine complexes.

Bisphosphine Data

Publication:

Stenfors, B. A.; Cadge, J. A.; Aikonen, S.; Luchini, G.; Wahlers, J.; Koh, K. H.; Murronen, M.; Menche, M.; Pfeifle, M.; Keto, A.; Paton, R.; Sigman, M. S.; Wiest, O. “Conformation Dependent Features of Bisphosphine Ligand” J. Org. Chem. 2025, 90, 13874–13884. https://doi.org/10.1021/acs.joc.5c01682


Alkyl Amines

Primary Alkyl Amines

Secondary Alkyl Amines

Combined Alkyl Amines

Publication:
Haas, B.; Hardy, M. A.; Sowndarya, S. S.; Adams, K.; Coley, C. W.; Paton, R. S.; Sigman, M. S. Rapid Prediction of Conformationally-Dependent DFT-Level Descriptors using Graph Neural Networks for Carboxylic Acids and Alkyl Amines. Digit. Discovery 2025, 4, 222–233. https://doi.org/10.1039/D4DD00284A


Anilines

Anilines

Publication:

Żurański, A.M.; Wang, J.Y.; Shields, B.J.; Doyle, A.G. Auto-QChem: an automated workflow for the generation and storage of DFT calculations for organic molecules. React. Chem. Engin. 2022, 7, 1276-1284 doi.org/10.1039/D2RE00030J


Aryl Bromides

Aryl Bromides

Publication:

Żurański, A.M.; Wang, J.Y.; Shields, B.J.; Doyle, A.G. Auto-QChem: an automated workflow for the generation and storage of DFT calculations for organic molecules. React. Chem. Engin. 2022, 7, 1276-1284 doi.org/10.1039/D2RE00030J


BUNNY: An N, N-Bidentate Nitrogen Ligand Descriptor Library

N,N-Bidentate ligands are widely employed in Ni-catalyzed cross-electrophile coupling (CEC) reactions; however, it is often difficult to predict a priori which scaffold will provide optimal selectivity and yield for a reaction under development. More generally, for a given Ni-catalyzed reaction, models that provide structure-reactivity and structure-selectivity relationships across different N,N-bidentate ligand scaffolds remain elusive. Here, we report BUNNY, a density functional theory-based descriptor library of approximately 1100 N,N-bidentate ligands designed to support modeling tasks for Ni-catalyzed cross-coupling. 

 

Publication:

Gutiérrez-Valencia, N. E.; Schleinitz, J.; Wild, T. H.; Williams, W. L.; Mantin, D. Doyle, A. G.; Reisman, S. E.; Sigman, M. S. BUNNY: An N, N-Bidentate Nitrogen Ligand Descriptor Library. Development and Application to Modeling of Ni-Catalyzed Asymmetric Cross-Electrophile Coupling Reactions ACS Catal. 2026, 16, 11532–11547. https://doi.org/10.1021/acscatal.6c02585


Carboxylic Acids

Carboxylic Acids 

 Publication:
Haas, B.; Hardy, M. A.; Sowndarya, S. S.; Adams, K.; Coley, C. W.; Paton, R. S.; Sigman, M. S. Rapid Prediction of Conformationally-Dependent DFT-Level Descriptors using Graph Neural Networks for Carboxylic Acids and Alkyl Amines. Digit. Discovery 2025, 4, 222–233. https://doi.org/10.1039/D4DD00284A
 

Cyanoarenes

Cyanoarenes


Kraken

Kraken is a discovery platform covering monodentate organophosphorus(III) ligands providing comprehensive physicochemical descriptors based on representative conformer ensembles. Using quantum-mechanical methods, we calculated descriptors for 1558 ligands, including commercially available examples, and trained machine learning models to predict properties of over 300000 new ligands.

Kraken Web Interface

Kraken GitHub

The molecular descriptors in Kraken form the basis of the Phosphine Predictor, a web tool by Sigma-Aldrich for the selection of phosphine ligands for cross-coupling reactions.

Publication:

Gensch, T.; dos Passos Gomes, G.; Friederich, P.; Peters, E.; Gaudin, T.; Pollice, R.; Jorner, K.; Nigam, A.; Lindner-D'Addario, M.; Sigman, M. S.; Aspuru-Guzik, A. A Comprehensive Discovery Platform for Organophosphorus Ligands for Catalysis. J. Am. Chem. Soc. 2022, 144, 3, 1205–1217. doi.org/10.1021/jacs.1c09718

Tutorial Material:

Kraken Tutorial


SMART Molecular Descriptors

An open-source Python package for generation of SMART probe pockets and calculation of molecular descriptors.

SMART Molecular Descriptors GitHub

Publication:

Miller, B. R.; Cammarota, R. C; Sigman, M. A Python Package for the Generation of Cavity-Specific Steric Molecular Descriptors and Applications to Diverse Systems. ChemRxiv. 2024. 10.26434/chemrxiv-2024-gk1bp


Sulfides

Sulfides


Sulfonimidamides

Given the lack of commercially available racemic sulfonimidamides, chemists generated a list totaling 117 diverse, synthetically-feasible sulfonimidamides. These included aryl, benzylic, allylic, alkyl, alkenyl, and alkynyl sulfonimidamides with various halide substitutions, heteroatom containing rings, and substitution patterns.

Sulfonimidamides
 
Publications:
van Dijk, L.; Haas, B. C.; Lim, N.; Clagg, K.; Dotson, J. J.; Treacy, S. M.; Piechowicz, K. A.; Roytman, V. A.; Zhang, H.; Toste, F. D.; Miller, S. J.; Gosselin, F.; Sigman, M. S. "Data Science-Enabled Palladium-Catalyzed Enantioselective Aryl-Carbonylation of Sulfonimidamides." J. Am. Chem. Soc. 2023, 145, 20959–20967. https://doi.org/10.1021/jacs.3c06674
 
Haas, B. C.; Lim, N.-K.; Jermaks, J.; Gaster, E.; Guo, M. C.; Malig, T. C.; Werth, J.; Zhang, H.; Toste, F. D.; Gosselin, F.; Miller, S. J.; Sigman, M. S. Enantioselective Sulfonimidamide Acylation via a Cinchona Alkaloid-Catalyzed Desymmetrization: Scope, Data Science, and Mechanistic Investigation. J. Am. Chem. Soc. 2024, 146, 8536–8546. DOI: 10.1021/jacs.4c00374


Sulfonates

Sulfonates


Sulfonyl Fluorides

Sulfonyl Fluorides


Quinones

Quinones


Unactivated Primary Aryl Bromides

The initial library of primary alkyl bromides was selected from the Auto-QChem database developed by the Doyle Lab. After excluding alpha-carbonyl, benzylic, allylic, propargylic bromides, and alkyl bromides containing iodide, a curated set of 878 structurally diverse and synthetically tractable primary alkyl bromides was obtained. This final collection represents a broad range of substitution patterns and functional group compatibility, ideal for cross-coupling reactivity studies.

Unactivated Primary Aryl Bromides

Publication:

Żurański, A.M.; Wang, J.Y.; Shields, B.J.; Doyle, A.G. Auto-QChem: an automated workflow for the generation and storage of DFT calculations for organic molecules. React. Chem. Engin. 2022, 7, 1276-1284 doi.org/10.1039/D2RE00030J