1
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Sheng H, Sun J, Rodríguez O, Hoar BB, Zhang W, Xiang D, Tang T, Hazra A, Min DS, Doyle AG, Sigman MS, Costentin C, Gu Q, Rodríguez-López J, Liu C. Autonomous closed-loop mechanistic investigation of molecular electrochemistry via automation. Nat Commun 2024; 15:2781. [PMID: 38555303 PMCID: PMC10981680 DOI: 10.1038/s41467-024-47210-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 03/18/2024] [Indexed: 04/02/2024] Open
Abstract
Electrochemical research often requires stringent combinations of experimental parameters that are demanding to manually locate. Recent advances in automated instrumentation and machine-learning algorithms unlock the possibility for accelerated studies of electrochemical fundamentals via high-throughput, online decision-making. Here we report an autonomous electrochemical platform that implements an adaptive, closed-loop workflow for mechanistic investigation of molecular electrochemistry. As a proof-of-concept, this platform autonomously identifies and investigates an EC mechanism, an interfacial electron transfer (E step) followed by a solution reaction (C step), for cobalt tetraphenylporphyrin exposed to a library of organohalide electrophiles. The generally applicable workflow accurately discerns the EC mechanism's presence amid negative controls and outliers, adaptively designs desired experimental conditions, and quantitatively extracts kinetic information of the C step spanning over 7 orders of magnitude, from which mechanistic insights into oxidative addition pathways are gained. This work opens opportunities for autonomous mechanistic discoveries in self-driving electrochemistry laboratories without manual intervention.
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Affiliation(s)
- Hongyuan Sheng
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
| | - Jingwen Sun
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Oliver Rodríguez
- Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Joint Center for Energy Storage Research (JCESR), Argonne National Laboratory, Lemont, IL, 60439, USA
| | - Benjamin B Hoar
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Weitong Zhang
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Danlei Xiang
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Tianhua Tang
- Department of Chemistry, University of Utah, Salt Lake City, UT, 84112, USA
| | - Avijit Hazra
- Department of Chemistry, University of Utah, Salt Lake City, UT, 84112, USA
| | - Daniel S Min
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Abigail G Doyle
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, Salt Lake City, UT, 84112, USA
| | | | - Quanquan Gu
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Joaquín Rodríguez-López
- Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Joint Center for Energy Storage Research (JCESR), Argonne National Laboratory, Lemont, IL, 60439, USA
| | - Chong Liu
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- California NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
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2
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Haas BC, Lim NK, Jermaks J, Gaster E, Guo MC, Malig TC, Werth J, Zhang H, Toste FD, Gosselin F, Miller SJ, Sigman MS. Enantioselective Sulfonimidamide Acylation via a Cinchona Alkaloid-Catalyzed Desymmetrization: Scope, Data Science, and Mechanistic Investigation. J Am Chem Soc 2024; 146:8536-8546. [PMID: 38480482 PMCID: PMC10990064 DOI: 10.1021/jacs.4c00374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2024]
Abstract
Methods to access chiral sulfur(VI) pharmacophores are of interest in medicinal and synthetic chemistry. We report the desymmetrization of unprotected sulfonimidamides via asymmetric acylation with a cinchona-phosphinate catalyst. The desired products are formed in excellent yield and enantioselectivity with no observed bis-acylation. A data-science-driven approach to substrate scope evaluation was coupled to high throughput experimentation (HTE) to facilitate statistical modeling in order to inform mechanistic studies. Reaction kinetics, catalyst structural studies, and density functional theory (DFT) transition state analysis elucidated the turnover-limiting step to be the collapse of the tetrahedral intermediate and provided key insights into the catalyst-substrate structure-activity relationships responsible for the origin of the enantioselectivity. This study offers a reliable method for accessing enantioenriched sulfonimidamides to propel their application as pharmacophores and serves as an example of the mechanistic insight that can be gleaned from integrating data science and traditional physical organic techniques.
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Affiliation(s)
- Brittany C Haas
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Ngiap-Kie Lim
- Department of Synthetic Molecule Process Chemistry, Genentech, Inc., South San Francisco, California 94080, United States
| | - Janis Jermaks
- Department of Synthetic Molecule Process Chemistry, Genentech, Inc., South San Francisco, California 94080, United States
| | - Eden Gaster
- Department of Chemistry, Yale University, New Haven, Connecticut 06511, United States
| | - Melody C Guo
- Department of Chemistry, Yale University, New Haven, Connecticut 06511, United States
| | - Thomas C Malig
- Department of Synthetic Molecule Analytical Chemistry, Genentech, Inc., South San Francisco, California 94080, United States
| | - Jacob Werth
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Haiming Zhang
- Department of Synthetic Molecule Process Chemistry, Genentech, Inc., South San Francisco, California 94080, United States
| | - F Dean Toste
- Department of Chemistry, University of California, Berkeley, California 94720, United States
| | - Francis Gosselin
- Department of Synthetic Molecule Process Chemistry, Genentech, Inc., South San Francisco, California 94080, United States
| | - Scott J Miller
- Department of Chemistry, Yale University, New Haven, Connecticut 06511, United States
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
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3
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Gao Y, Jiang B, Friede NC, Hunter AC, Boucher DG, Minteer SD, Sigman MS, Reisman SE, Baran PS. Electrocatalytic Asymmetric Nozaki-Hiyama-Kishi Decarboxylative Coupling: Scope, Applications, and Mechanism. J Am Chem Soc 2024; 146:4872-4882. [PMID: 38324710 DOI: 10.1021/jacs.3c13442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
The first general enantioselective alkyl-Nozaki-Hiyama-Kishi (NHK) coupling reactions are disclosed herein by employing a Cr-electrocatalytic decarboxylative approach. Using easily accessible aliphatic carboxylic acids (via redox-active esters) as alkyl nucleophile synthons, in combination with aldehydes and enabling additives, chiral secondary alcohols are produced in a good yield with high enantioselectivity under mild reductive electrolysis. This reaction, which cannot be mimicked using stoichiometric metal or organic reductants, tolerates a broad range of functional groups and is successfully applied to dramatically simplify the synthesis of multiple medicinally relevant structures and natural products. Mechanistic studies revealed that this asymmetric alkyl e-NHK reaction was enabled by using catalytic tetrakis(dimethylamino)ethylene, which acts as a key reductive mediator to mediate the electroreduction of the CrIII/chiral ligand complex.
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Affiliation(s)
- Yang Gao
- Department of Chemistry, Scripps Research, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Baiyang Jiang
- Department of Chemistry, Scripps Research, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Nathan C Friede
- The Warren and Katharine Schlinger Laboratory for Chemistry and Chemical Engineering, Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, United States
| | - Arianne C Hunter
- The Warren and Katharine Schlinger Laboratory for Chemistry and Chemical Engineering, Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, United States
| | - Dylan G Boucher
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Shelley D Minteer
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
- Kummer Institute Center for Resource Sustainability, Department of Chemistry, Missouri University of Science and Technology, 400 W 11th Street, Rolla, Missouri 65409, United States
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Sarah E Reisman
- The Warren and Katharine Schlinger Laboratory for Chemistry and Chemical Engineering, Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, United States
| | - Phil S Baran
- Department of Chemistry, Scripps Research, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
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4
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Bartholomew GL, Kraus SL, Karas LJ, Carpaneto F, Bennett R, Sigman MS, Yeung CS, Sarpong R. 14N to 15N Isotopic Exchange of Nitrogen Heteroaromatics through Skeletal Editing. J Am Chem Soc 2024; 146:2950-2958. [PMID: 38286797 DOI: 10.1021/jacs.3c11515] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
The selective modification of nitrogen heteroaromatics enables the development of new chemical tools and accelerates drug discovery. While methods that focus on expanding or contracting the skeletal structures of heteroaromatics are emerging, methods for the direct exchange of single core atoms remain limited. Here, we present a method for 14N → 15N isotopic exchange for several aromatic nitrogen heterocycles. This nitrogen isotope transmutation occurs through activation of the heteroaromatic substrate by triflylation of a nitrogen atom, followed by a ring-opening/ring-closure sequence mediated by 15N-aspartate to effect the isotopic exchange of the nitrogen atom. Key to the success of this transformation is the formation of an isolable 15N-succinyl intermediate, which undergoes elimination to give the isotopically labeled heterocycle. These transformations occur under mild conditions in high chemical and isotopic yields.
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Affiliation(s)
- G Logan Bartholomew
- Department of Chemistry, University of California, Berkeley, Berkeley, California 94720, United States
| | - Samantha L Kraus
- Department of Chemistry, University of California, Berkeley, Berkeley, California 94720, United States
| | - Lucas J Karas
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Filippo Carpaneto
- Department of Chemistry, University of California, Berkeley, Berkeley, California 94720, United States
| | - Raffeal Bennett
- Discovery Analytical Research, Merck & Co., Inc., Boston, Massachusetts 02115, United States
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Charles S Yeung
- Discovery Chemistry, Merck & Co., Inc., Boston, Massachusetts 02115, United States
| | - Richmond Sarpong
- Department of Chemistry, University of California, Berkeley, Berkeley, California 94720, United States
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5
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Akana ME, Tcyrulnikov S, Akana-Schneider BD, Reyes GP, Monfette S, Sigman MS, Hansen EC, Weix DJ. Computational Methods Enable the Prediction of Improved Catalysts for Nickel-Catalyzed Cross-Electrophile Coupling. J Am Chem Soc 2024; 146:3043-3051. [PMID: 38276910 DOI: 10.1021/jacs.3c09554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2024]
Abstract
Cross-electrophile coupling has emerged as an attractive and efficient method for the synthesis of C(sp2)-C(sp3) bonds. These reactions are most often catalyzed by nickel complexes of nitrogenous ligands, especially 2,2'-bipyridines. Precise prediction, selection, and design of optimal ligands remains challenging, despite significant increases in reaction scope and mechanistic understanding. Molecular parameterization and statistical modeling provide a path to the development of improved bipyridine ligands that will enhance the selectivity of existing reactions and broaden the scope of electrophiles that can be coupled. Herein, we describe the generation of a computational ligand library, correlation of observed reaction outcomes with features of the ligands, and the in silico design of improved bipyridine ligands for Ni-catalyzed cross-electrophile coupling. The new nitrogen-substituted ligands display a 5-fold increase in selectivity for product formation versus homodimerization when compared to the current state of the art. This increase in selectivity and yield was general for several cross-electrophile couplings, including the challenging coupling of an aryl chloride with an N-alkylpyridinium salt.
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Affiliation(s)
- Michelle E Akana
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Sergei Tcyrulnikov
- Chemical Research and Development, Pfizer Worldwide Research and Development, Groton, Connecticut 06340, United States
| | - Brett D Akana-Schneider
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Giselle P Reyes
- Chemical Research and Development, Pfizer Worldwide Research and Development, Groton, Connecticut 06340, United States
| | - Sebastien Monfette
- Chemical Research and Development, Pfizer Worldwide Research and Development, Groton, Connecticut 06340, United States
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Eric C Hansen
- Chemical Research and Development, Pfizer Worldwide Research and Development, Groton, Connecticut 06340, United States
| | - Daniel J Weix
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
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6
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Samha MH, Karas LJ, Vogt DB, Odogwu EC, Elward J, Crawford JM, Steves JE, Sigman MS. Predicting success in Cu-catalyzed C-N coupling reactions using data science. Sci Adv 2024; 10:eadn3478. [PMID: 38232169 PMCID: PMC10793951 DOI: 10.1126/sciadv.adn3478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 12/18/2023] [Indexed: 01/19/2024]
Abstract
Data science is assuming a pivotal role in guiding reaction optimization and streamlining experimental workloads in the evolving landscape of synthetic chemistry. A discipline-wide goal is the development of workflows that integrate computational chemistry and data science tools with high-throughput experimentation as it provides experimentalists the ability to maximize success in expensive synthetic campaigns. Here, we report an end-to-end data-driven process to effectively predict how structural features of coupling partners and ligands affect Cu-catalyzed C-N coupling reactions. The established workflow underscores the limitations posed by substrates and ligands while also providing a systematic ligand prediction tool that uses probability to assess when a ligand will be successful. This platform is strategically designed to confront the intrinsic unpredictability frequently encountered in synthetic reaction deployment.
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Affiliation(s)
- Mohammad H. Samha
- Department of Chemistry, University of Utah, 315 S. 1400 E., Salt Lake City, UT 84112, USA
| | - Lucas J. Karas
- Department of Chemistry, University of Utah, 315 S. 1400 E., Salt Lake City, UT 84112, USA
| | - David B. Vogt
- Department of Chemistry, University of Utah, 315 S. 1400 E., Salt Lake City, UT 84112, USA
| | - Emmanuel C. Odogwu
- Department of Chemistry, University of Utah, 315 S. 1400 E., Salt Lake City, UT 84112, USA
| | - Jennifer Elward
- Molecular Design, GlaxoSmithKline, 1250 S. Collegeville Rd., Collegeville, PA 19426, USA
| | - Jennifer M. Crawford
- Drug Substance Development, GlaxoSmithKline, 1250 S. Collegeville Rd., Collegeville, PA 19426, USA
| | - Janelle E. Steves
- Drug Substance Development, GlaxoSmithKline, 1250 S. Collegeville Rd., Collegeville, PA 19426, USA
| | - Matthew S. Sigman
- Department of Chemistry, University of Utah, 315 S. 1400 E., Salt Lake City, UT 84112, USA
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7
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Souza L, Miller BR, Cammarota RC, Lo A, Lopez I, Shiue YS, Bergstrom BD, Dishman SN, Fettinger JC, Sigman MS, Shaw JT. Deconvoluting Nonlinear Catalyst-Substrate Effects in the Intramolecular Dirhodium-Catalyzed C-H Insertion of Donor/Donor Carbenes Using Data Science Tools. ACS Catal 2024; 14:104-115. [PMID: 38205021 PMCID: PMC10775150 DOI: 10.1021/acscatal.3c04256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 11/09/2023] [Accepted: 11/10/2023] [Indexed: 01/12/2024]
Abstract
Interactions between catalysts and substrates can be highly complex and dynamic, often complicating the development of models to either predict or understand such processes. A dirhodium(II)-catalyzed C-H insertion of donor/donor carbenes into 2-alkoxybenzophenone substrates to form benzodihydrofurans was selected as a model system to explore nonlinear methods to achieve a mechanistic understanding. We found that the application of traditional methods of multivariate linear regression (MLR) correlating DFT-derived descriptors of catalysts and substrates leads to poorly performing models. This inspired the introduction of nonlinear descriptor relationships into modeling by applying the sure independence screening and sparsifying operator (SISSO) algorithm. Based on SISSO-generated descriptors, a high-performing MLR model was identified that predicts external validation points well. Mechanistic interpretation was aided by the deconstruction of feature relationships using chemical space maps, decision trees, and linear descriptors. Substrates were found to have a strong dependence on steric effects for determining their innate cyclization selectivity preferences. Catalyst reactive site features can then be matched to product features to tune or override the resultant diastereoselectivity within the substrate-dictated ranges. This case study presents a method for understanding complex interactions often encountered in catalysis by using nonlinear modeling methods and linear deconvolution by pattern recognition.
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Affiliation(s)
- Lucas
W. Souza
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Beck R. Miller
- Department
of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Ryan C. Cammarota
- Department
of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Anna Lo
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Ixchel Lopez
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Yuan-Shin Shiue
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Benjamin D. Bergstrom
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Sarah N. Dishman
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - James C. Fettinger
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Matthew S. Sigman
- Department
of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Jared T. Shaw
- Department
of Chemistry, University of California, Davis, California 95616, United States
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8
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Raghavan P, Haas BC, Ruos ME, Schleinitz J, Doyle AG, Reisman SE, Sigman MS, Coley CW. Dataset Design for Building Models of Chemical Reactivity. ACS Cent Sci 2023; 9:2196-2204. [PMID: 38161380 PMCID: PMC10755851 DOI: 10.1021/acscentsci.3c01163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 11/06/2023] [Accepted: 11/15/2023] [Indexed: 01/03/2024]
Abstract
Models can codify our understanding of chemical reactivity and serve a useful purpose in the development of new synthetic processes via, for example, evaluating hypothetical reaction conditions or in silico substrate tolerance. Perhaps the most determining factor is the composition of the training data and whether it is sufficient to train a model that can make accurate predictions over the full domain of interest. Here, we discuss the design of reaction datasets in ways that are conducive to data-driven modeling, emphasizing the idea that training set diversity and model generalizability rely on the choice of molecular or reaction representation. We additionally discuss the experimental constraints associated with generating common types of chemistry datasets and how these considerations should influence dataset design and model building.
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Affiliation(s)
- Priyanka Raghavan
- Department
of Chemical Engineering, Massachusetts Institute
of Technology, Cambridge, Massachusetts 02139, United States
| | - Brittany C. Haas
- Department
of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Madeline E. Ruos
- Department
of Chemistry & Biochemistry, University
of California, Los Angeles, Los Angeles, California 90095, United States
| | - Jules Schleinitz
- Division
of Chemistry and Chemical Engineering, California
Institute of Technology, Pasadena, California 91125, United States
| | - Abigail G. Doyle
- Department
of Chemistry & Biochemistry, University
of California, Los Angeles, Los Angeles, California 90095, United States
| | - Sarah E. Reisman
- Division
of Chemistry and Chemical Engineering, California
Institute of Technology, Pasadena, California 91125, United States
| | - Matthew S. Sigman
- Department
of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Connor W. Coley
- Department
of Chemical Engineering, Massachusetts Institute
of Technology, Cambridge, Massachusetts 02139, United States
- Department
of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
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9
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Pancoast AR, McCormack SL, Galinat S, Walser-Kuntz R, Jett BM, Sanford MS, Sigman MS. Data science enabled discovery of a highly soluble 2,2'-bipyrimidine anolyte for application in a flow battery. Chem Sci 2023; 14:13734-13742. [PMID: 38075655 PMCID: PMC10699568 DOI: 10.1039/d3sc04084d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Accepted: 11/01/2023] [Indexed: 02/12/2024] Open
Abstract
Development of non-aqueous redox flow batteries as a viable energy storage solution relies upon the identification of soluble charge carriers capable of storing large amounts of energy over extended time periods. A combination of metrics including number of electrons stored per molecule, redox potential, stability, and solubility of the charge carrier impact performance. In this context, we recently reported a 2,2'-bipyrimidine charge carrier that stores two electrons per molecule with reduction near -2.0 V vs. Fc/Fc+ and high stability. However, these first-generation derivatives showed a modest solubility of 0.17 M (0.34 M e-). Seeking to improve solubility without sacrificing stability, we harnessed the synthetic modularity of this scaffold to design a library of sixteen candidates. Using computed molecular descriptors and a single node decision tree, we found that minimization of the solvent accessible surface area (SASA) can be used to predict derivatives with enhanced solubility. This parameter was used in combination with a heatmap describing stability to de-risk a virtual screen that ultimately identified a 2,2'-bipyrimidine with significantly increased solubility and good stability metrics in the reduced states. This molecule was paired with a cyclopropenium catholyte in a prototype all-organic redox flow battery, achieving a cell potential up to 3 V.
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Affiliation(s)
- Adam R Pancoast
- Department of Chemistry, University of Utah 315 South 1400 East Salt Lake City Utah 84112 USA
- Joint Center for Energy Storage Research 9700 S. Cass Avenue Argonne Illinois 60439 USA
| | - Sara L McCormack
- Department of Chemistry, University of Utah 315 South 1400 East Salt Lake City Utah 84112 USA
- Joint Center for Energy Storage Research 9700 S. Cass Avenue Argonne Illinois 60439 USA
| | - Shelby Galinat
- Department of Chemistry, University of Utah 315 South 1400 East Salt Lake City Utah 84112 USA
| | - Ryan Walser-Kuntz
- Department of Chemistry, University of Michigan, 930 North University Avenue Ann Arbor Michigan 48109 USA
- Joint Center for Energy Storage Research 9700 S. Cass Avenue Argonne Illinois 60439 USA
| | - Brianna M Jett
- Department of Chemistry, University of Michigan, 930 North University Avenue Ann Arbor Michigan 48109 USA
- Joint Center for Energy Storage Research 9700 S. Cass Avenue Argonne Illinois 60439 USA
| | - Melanie S Sanford
- Department of Chemistry, University of Michigan, 930 North University Avenue Ann Arbor Michigan 48109 USA
- Joint Center for Energy Storage Research 9700 S. Cass Avenue Argonne Illinois 60439 USA
| | - Matthew S Sigman
- Department of Chemistry, University of Utah 315 South 1400 East Salt Lake City Utah 84112 USA
- Department of Chemistry, University of Michigan, 930 North University Avenue Ann Arbor Michigan 48109 USA
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10
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Jett B, Flynn A, Sigman MS, Sanford MS. Identifying structure-function relationships to modulate crossover in nonaqueous redox flow batteries. J Mater Chem A Mater 2023; 11:22288-22294. [PMID: 38213509 PMCID: PMC10783818 DOI: 10.1039/d3ta02633g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/13/2024]
Abstract
Nonaqueous redox flow batteries (NARFBs) offer a promising solution for large-scale storage of renewable energy. However, crossover of redox active molecules between the two sides of the cell is a major factor limiting their development, as most selective separators are designed for deployment in water, rather than organic solvents. This report describes a systematic investigation of the crossover rates of redox active organic molecules through an anion exchange separator under RFB-relevant non-aqueous conditions (in acetonitrile/KPF6) using a combination of experimental and computational methods. A structurally diverse set of neutral and cationic molecules was selected, and their rates of crossover were determined experimentally with the organic solvent-compatible anion exchange separator Fumasep FAP-375-PP. The resulting data were then fit to various descriptors of molecular size, charge, and hydrophobicity (overall charge, solution diffusion coefficient, globularity, dynamic volume, dynamic surface area, clogP). This analysis resulted in multiple statistical models of crossover rates for this separator. These models were then used to predict tether groups that dramatically slow the crossover of small organic molecules in this system.
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Affiliation(s)
- Brianna Jett
- Department of Chemistry, University of Michigan, 930N University Ave, Ann Arbor, MI 48109, USA
- Joint Center for Energy Storage Research, 9700 S. Cass Avenue, Argonne, Illinois 60439, USA
| | - Autumn Flynn
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, USA
- Joint Center for Energy Storage Research, 9700 S. Cass Avenue, Argonne, Illinois 60439, USA
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, USA
- Joint Center for Energy Storage Research, 9700 S. Cass Avenue, Argonne, Illinois 60439, USA
| | - Melanie S Sanford
- Department of Chemistry, University of Michigan, 930N University Ave, Ann Arbor, MI 48109, USA
- Joint Center for Energy Storage Research, 9700 S. Cass Avenue, Argonne, Illinois 60439, USA
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11
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Morack T, Myers TE, Karas LJ, Hardy MA, Mercado BQ, Sigman MS, Miller SJ. An Asymmetric Aromatic Finkelstein Reaction: A Platform for Remote Diarylmethane Desymmetrization. J Am Chem Soc 2023; 145:22322-22328. [PMID: 37788150 PMCID: PMC10591928 DOI: 10.1021/jacs.3c08727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
A first-of-its-kind enantioselective aromatic Finkelstein reaction is disclosed for the remote desymmetrization of diarylmethanes. The reaction operates through a copper-catalyzed C-I bond-forming event, and high levels of enantioselectivity are achieved through the deployment of a tailored guanidinylated peptide ligand. Strategic use of transition-metal-mediated reactions enables the chemoselective modification of the aryl iodide products; thus, the synthesis of a diverse set of otherwise difficult-to-access diarylmethanes with excellent levels of selectivity is realized from a common intermediate. A mixed experimental/computational analysis of steric parameters and substrate conformations identifies the importance of remote conformational effects as a key to achieving high enantioselectivity in this desymmetrization reaction.
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Affiliation(s)
- Tobias Morack
- Department of Chemistry, Yale University, New Haven, Connecticut 06520-8107, United States
| | - Tyler E. Myers
- Department of Chemistry, Yale University, New Haven, Connecticut 06520-8107, United States
| | - Lucas J. Karas
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Melissa A. Hardy
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Brandon Q. Mercado
- Department of Chemistry, Yale University, New Haven, Connecticut 06520-8107, United States
| | - Matthew S. Sigman
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Scott J. Miller
- Department of Chemistry, Yale University, New Haven, Connecticut 06520-8107, United States
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12
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van Dijk L, Haas BC, Lim NK, Clagg K, Dotson JJ, Treacy SM, Piechowicz KA, Roytman VA, Zhang H, Toste FD, Miller SJ, Gosselin F, Sigman MS. Data Science-Enabled Palladium-Catalyzed Enantioselective Aryl-Carbonylation of Sulfonimidamides. J Am Chem Soc 2023; 145:20959-20967. [PMID: 37656964 DOI: 10.1021/jacs.3c06674] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/03/2023]
Abstract
New methods for the general asymmetric synthesis of sulfonimidamides are of great interest due to their applications in medicinal chemistry, agrochemical discovery, and academic research. We report a palladium-catalyzed cross-coupling method for the enantioselective aryl-carbonylation of sulfonimidamides. Using data science techniques, a virtual library of calculated bisphosphine ligand descriptors was used to guide reaction optimization by effectively sampling the catalyst chemical space. The optimized conditions identified using this approach provided the desired product in excellent yield and enantioselectivity. As the next step, a data science-driven strategy was also used to explore a diverse set of aryl and heteroaryl iodides, providing key information about the scope and limitations of the method. Furthermore, we tested a range of racemic sulfonimidamides for compatibility of this coupling partner. The developed method offers a general and efficient strategy for accessing enantioenriched sulfonimidamides, which should facilitate their application in industrial and academic settings.
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Affiliation(s)
- Lucy van Dijk
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Brittany C Haas
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Ngiap-Kie Lim
- Department of Small Molecule Process Chemistry, Genentech, Inc., South San Francisco, California 94080, United States
| | - Kyle Clagg
- Department of Small Molecule Process Chemistry, Genentech, Inc., South San Francisco, California 94080, United States
| | - Jordan J Dotson
- Department of Small Molecule Process Chemistry, Genentech, Inc., South San Francisco, California 94080, United States
| | - Sean M Treacy
- Department of Chemistry, University of California, Berkeley, California 94720, United States
| | - Katarzyna A Piechowicz
- Department of Small Molecule Process Chemistry, Genentech, Inc., South San Francisco, California 94080, United States
| | - Vladislav A Roytman
- Department of Chemistry, University of California, Berkeley, California 94720, United States
| | - Haiming Zhang
- Department of Small Molecule Process Chemistry, Genentech, Inc., South San Francisco, California 94080, United States
| | - F Dean Toste
- Department of Chemistry, University of California, Berkeley, California 94720, United States
| | - Scott J Miller
- Department of Chemistry, Yale University, New Haven, Connecticut 06511, United States
| | - Francis Gosselin
- Department of Small Molecule Process Chemistry, Genentech, Inc., South San Francisco, California 94080, United States
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
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13
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Clements HD, Flynn AR, Nicholls BT, Grosheva D, Lefave SJ, Merriman MT, Hyster TK, Sigman MS. Using Data Science for Mechanistic Insights and Selectivity Predictions in a Non-Natural Biocatalytic Reaction. J Am Chem Soc 2023; 145:17656-17664. [PMID: 37530568 PMCID: PMC10602048 DOI: 10.1021/jacs.3c03639] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/03/2023]
Abstract
The study of non-natural biocatalytic transformations relies heavily on empirical methods, such as directed evolution, for identifying improved variants. Although exceptionally effective, this approach provides limited insight into the molecular mechanisms behind the transformations and necessitates multiple protein engineering campaigns for new reactants. To address this limitation, we disclose a strategy to explore the biocatalytic reaction space and garner insight into the molecular mechanisms driving enzymatic transformations. Specifically, we explored the selectivity of an "ene"-reductase, GluER-T36A, to create a data-driven toolset that explores reaction space and rationalizes the observed and predicted selectivities of substrate/mutant combinations. The resultant statistical models related structural features of the enzyme and substrate to selectivity and were used to effectively predict selectivity in reactions with out-of-sample substrates and mutants. Our approach provided a deeper understanding of enantioinduction by GluER-T36A and holds the potential to enhance the virtual screening of enzyme mutants.
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Affiliation(s)
- Hanna D Clements
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Autumn R Flynn
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Bryce T Nicholls
- Department of Chemistry and Chemical Biology, Cornell University, 122 Baker Laboratory, Ithaca, New York 14853, United States
| | - Daria Grosheva
- Department of Chemistry and Chemical Biology, Cornell University, 122 Baker Laboratory, Ithaca, New York 14853, United States
| | - Sarah J Lefave
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Morgan T Merriman
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Todd K Hyster
- Department of Chemistry and Chemical Biology, Cornell University, 122 Baker Laboratory, Ithaca, New York 14853, United States
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
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14
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Liles JP, Rouget-Virbel C, Wahlman JLH, Rahimoff R, Crawford JM, Medlin A, O’Connor V, Li J, Roytman VA, Toste FD, Sigman MS. Data Science Enables the Development of a New Class of Chiral Phosphoric Acid Catalysts. Chem 2023; 9:1518-1537. [PMID: 37519827 PMCID: PMC10373836 DOI: 10.1016/j.chempr.2023.02.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/01/2023]
Abstract
The widespread success of BINOL-chiral phosphoric acids (CPAs) has led to the development of several high molecular weight, sterically encumbered variants. Herein, we disclose an alternative, minimalistic chiral phosphoric acid backbone incorporating only a single instance of point chirality. Data science techniques were used to select a diverse training set of catalysts, which were benchmarked against the transfer hydrogenation of an 8-aminoquinoline. Using a univariate classification algorithm and multivariate linear regression, key catalyst features necessary for high levels of selectivity were deconvoluted, revealing a simple catalyst model capable of predicting selectivity for out-of-set catalysts. This workflow enabled extrapolation to a catalyst providing higher selectivity than both reported peptide-type and BINOL-type catalysts (up to 95:5 er). These techniques were then successfully applied towards two additional transforms. Taken together, these examples illustrate the power of combining rational design with data science (ab initio) to efficiently explore reactivity during catalyst development.
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Affiliation(s)
- Jordan P. Liles
- Department of Chemistry, University of Utah, 315 S 1400 E, Salt Lake City, UT, 84112, USA
| | | | - Julie L. H. Wahlman
- Department of Chemistry, University of Utah, 315 S 1400 E, Salt Lake City, UT, 84112, USA
| | - Rene Rahimoff
- College of Chemistry, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Jennifer M. Crawford
- Department of Chemistry, University of Utah, 315 S 1400 E, Salt Lake City, UT, 84112, USA
| | - Abby Medlin
- College of Chemistry, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Veronica O’Connor
- Department of Chemistry, University of Utah, 315 S 1400 E, Salt Lake City, UT, 84112, USA
| | - Junqi Li
- College of Chemistry, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Vladislav A. Roytman
- College of Chemistry, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - F. Dean Toste
- College of Chemistry, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Matthew S. Sigman
- Department of Chemistry, University of Utah, 315 S 1400 E, Salt Lake City, UT, 84112, USA
- Lead contact
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15
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Ortiz KG, Dotson JJ, Robinson DJ, Sigman MS, Karimov RR. Catalyst-Controlled Enantioselective and Regiodivergent Addition of Aryl Boron Nucleophiles to N-Alkyl Nicotinate Salts. J Am Chem Soc 2023; 145:11781-11788. [PMID: 37205733 PMCID: PMC10363019 DOI: 10.1021/jacs.3c03048] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Dihydropyridines are versatile building blocks for the synthesis of pyridines, tetrahydropyridines, and piperidines. Addition of nucleophiles to activated pyridinium salts allows synthesis of 1,2-, 1,4-, or 1,6-dihydropyridines; however, this process often leads to a mixture of constitutional isomers. Catalyst-controlled regioselective addition of nucleophiles to pyridiniums has the potential to solve this problem. Herein, we report that the regioselective addition of boron-based nucleophiles to pyridinium salts can be accomplished by the choice of a Rh catalyst.
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Affiliation(s)
- Kacey G Ortiz
- Department of Chemistry and Biochemistry, Auburn University, Auburn, Alabama 36849, United States
| | - Jordan J Dotson
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Donovan J Robinson
- Department of Chemistry and Biochemistry, Auburn University, Auburn, Alabama 36849, United States
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Rashad R Karimov
- Department of Chemistry and Biochemistry, Auburn University, Auburn, Alabama 36849, United States
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16
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Rein J, Rozema SD, Langner OC, Zacate SB, Hardy MA, Siu JC, Mercado BQ, Sigman MS, Miller SJ, Lin S. Generality-oriented optimization of enantioselective aminoxyl radical catalysis. Science 2023; 380:706-712. [PMID: 37200427 DOI: 10.1126/science.adf6177] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 03/29/2023] [Indexed: 05/20/2023]
Abstract
Catalytic enantioselective methods that are generally applicable to a broad range of substrates are rare. We report a strategy for the oxidative desymmetrization of meso-diols predicated on a nontraditional catalyst optimization protocol by using a panel of screening substrates rather than a singular model substrate. Critical to this approach was rational modulation of a peptide sequence in the catalyst incorporating a distinct aminoxyl-based active residue. A general catalyst emerged, providing high selectivity in the delivery of enantioenriched lactones across a broad range of diols, while also achieving up to ~100,000 turnovers.
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Affiliation(s)
- Jonas Rein
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853, USA
| | - Soren D Rozema
- Department of Chemistry, Yale University, New Haven, CT 06520, USA
| | - Olivia C Langner
- Department of Chemistry, Yale University, New Haven, CT 06520, USA
| | - Samson B Zacate
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853, USA
| | - Melissa A Hardy
- Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA
| | - Juno C Siu
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853, USA
| | | | - Matthew S Sigman
- Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA
| | - Scott J Miller
- Department of Chemistry, Yale University, New Haven, CT 06520, USA
| | - Song Lin
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853, USA
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17
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Rein J, Meinhardt JM, Hofstra Wahlman JL, Sigman MS, Lin S. A Physical Organic Approach towards Statistical Modeling of Tetrazole and Azide Decomposition. Angew Chem Int Ed Engl 2023; 62:e202218213. [PMID: 36823344 PMCID: PMC10079611 DOI: 10.1002/anie.202218213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 02/17/2023] [Accepted: 02/20/2023] [Indexed: 02/25/2023]
Abstract
Nitrogen atom-rich heterocycles and organic azides have found extensive use in many sectors of modern chemistry from drug discovery to energetic materials. The prediction and understanding of their energetic properties are thus key to the safe and effective application of these compounds. In this work, we disclose the use of multivariate linear regression modeling for the prediction of the decomposition temperature and impact sensitivity of structurally diverse tetrazoles and organic azides. We report a data-driven approach for property prediction featuring a collection of quantum mechanical parameters and computational workflows. The statistical models reported herein carry predictive accuracy as well as chemical interpretability. Model validation was successfully accomplished via tetrazole test sets with parameters generated exclusively in silico. Mechanistic analysis of the statistical models indicated distinct divergent pathways of thermal and impact-initiated decomposition.
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Affiliation(s)
- Jonas Rein
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853, USA
| | - Jonathan M Meinhardt
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853, USA
| | | | - Matthew S Sigman
- Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA
| | - Song Lin
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853, USA
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18
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Tang T, Hazra A, Min DS, Williams WL, Jones E, Doyle AG, Sigman MS. Interrogating the Mechanistic Features of Ni(I)-Mediated Aryl Iodide Oxidative Addition Using Electroanalytical and Statistical Modeling Techniques. J Am Chem Soc 2023:10.1021/jacs.3c01726. [PMID: 37014945 PMCID: PMC10548350 DOI: 10.1021/jacs.3c01726] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/06/2023]
Abstract
While the oxidative addition of Ni(I) to aryl iodides has been commonly proposed in catalytic methods, an in-depth mechanistic understanding of this fundamental process is still lacking. Herein, we describe a detailed mechanistic study of the oxidative addition process using electroanalytical and statistical modeling techniques. Electroanalytical techniques allowed rapid measurement of the oxidative addition rates for a diverse set of aryl iodide substrates and four classes of catalytically relevant complexes (Ni(MeBPy), Ni(MePhen), Ni(Terpy), and Ni(BPP)). With >200 experimental rate measurements, we were able to identify essential electronic and steric factors impacting the rate of oxidative addition through multivariate linear regression models. This has led to a classification of oxidative addition mechanisms, either through a three-center concerted or halogen-atom abstraction pathway based on the ligand type. A global heat map of predicted oxidative addition rates was created and shown applicable to a better understanding of the reaction outcome in a case study of a Ni-catalyzed coupling reaction.
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Affiliation(s)
- Tianhua Tang
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Avijit Hazra
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Daniel S. Min
- Department of Chemistry and Biochemistry, University of California, Los Angeles, California 90095, United States
| | - Wendy L. Williams
- Department of Chemistry and Biochemistry, University of California, Los Angeles, California 90095, United States
- Department of Chemistry, Princeton University, Princeton, New Jersey 08544, United States
| | - Eli Jones
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Abigail G. Doyle
- Department of Chemistry and Biochemistry, University of California, Los Angeles, California 90095, United States
| | - Matthew S. Sigman
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
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19
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Rein J, Meinhardt JM, Hofstra Wahlman JL, Sigman MS, Lin S. A Physical Organic Approach towards Statistical Modeling of Tetrazole and Azide Decomposition. Angew Chem Int Ed Engl 2023. [DOI: 10.1002/ange.202218213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Affiliation(s)
- Jonas Rein
- Cornell University Chemistry and Chemical Biology 14853 Ithaca UNITED STATES
| | | | | | | | - Song Lin
- Cornell University Chemistry and Chemical Biology 360B Spencer T. Olin Research Wing 14853 Ithaca UNITED STATES
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20
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Dotson JJ, van Dijk L, Timmerman JC, Grosslight S, Walroth RC, Gosselin F, Püntener K, Mack KA, Sigman MS. Data-Driven Multi-Objective Optimization Tactics for Catalytic Asymmetric Reactions Using Bisphosphine Ligands. J Am Chem Soc 2023; 145:110-121. [PMID: 36574729 DOI: 10.1021/jacs.2c08513] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Optimization of the catalyst structure to simultaneously improve multiple reaction objectives (e.g., yield, enantioselectivity, and regioselectivity) remains a formidable challenge. Herein, we describe a machine learning workflow for the multi-objective optimization of catalytic reactions that employ chiral bisphosphine ligands. This was demonstrated through the optimization of two sequential reactions required in the asymmetric synthesis of an active pharmaceutical ingredient. To accomplish this, a density functional theory-derived database of >550 bisphosphine ligands was constructed, and a designer chemical space mapping technique was established. The protocol used classification methods to identify active catalysts, followed by linear regression to model reaction selectivity. This led to the prediction and validation of significantly improved ligands for all reaction outputs, suggesting a general strategy that can be readily implemented for reaction optimizations where performance is controlled by bisphosphine ligands.
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Affiliation(s)
- Jordan J Dotson
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Lucy van Dijk
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Jacob C Timmerman
- Department of Small Molecule Process Chemistry, Genentech, Inc., South San Francisco, California 94080, United States
| | - Samantha Grosslight
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Richard C Walroth
- Department of Small Molecule Process Chemistry, Genentech, Inc., South San Francisco, California 94080, United States
| | - Francis Gosselin
- Department of Small Molecule Process Chemistry, Genentech, Inc., South San Francisco, California 94080, United States
| | - Kurt Püntener
- Synthetic Molecules Technical Development, Process Chemistry & Catalysis, F. Hoffmann-La Roche Limited, CH-4070 Basel, Switzerland
| | - Kyle A Mack
- Department of Small Molecule Process Chemistry, Genentech, Inc., South San Francisco, California 94080, United States
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
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21
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Samha MH, Wahlman JLH, Read JA, Werth J, Jacobsen EN, Sigman MS. Exploring Structure-Function Relationships of Aryl Pyrrolidine-Based Hydrogen-Bond Donors in Asymmetric Catalysis Using Data-Driven Techniques. ACS Catal 2022; 12:14836-14845. [PMID: 36816226 PMCID: PMC9937582 DOI: 10.1021/acscatal.2c04824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Hydrogen bond-based organocatalysts rely on networks of attractive noncovalent interactions (NCIs) to impart enantioselectivity. As a specific example, aryl pyrrolidine substituted urea, thiourea, and squaramide organocatalysts function cooperatively through hydrogen bonding and difficult-to-predict NCIs as a function of the reaction partners. To uncover the synergistic effect of the structural components of this catalyst class, we applied data science tools to study various model reactions using a derivatized, aryl pyrrolidine-based, hydrogen-bond donor (HBD) catalyst library. Through a combination of experimentally collected data and data mined from previous reports, statistical models were constructed, illuminating the general features necessary for high enantioselectivity. A distinct dependence on the identity of the electrophilic reaction partner and HBD catalyst is observed, suggesting that a general interaction is conserved throughout the reactions analyzed. The resulting models also demonstrate predictive capability by the successful improvement of a previously reported reaction using out-of-sample reaction components. Overall, this study highlights the power of data science in exploring mechanistic hypotheses in asymmetric HBD catalysis and provides a prediction platform applicable in future reaction optimization.
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Affiliation(s)
- Mohammad H. Samha
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Julie L. H. Wahlman
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Jacquelyne A. Read
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States; Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Jacob Werth
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Eric N. Jacobsen
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Matthew S. Sigman
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
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22
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Nistanaki SK, Williams CG, Wigman B, Wong JJ, Haas BC, Popov S, Werth J, Sigman MS, Houk KN, Nelson HM. Catalytic asymmetric C-H insertion reactions of vinyl carbocations. Science 2022; 378:1085-1091. [PMID: 36480623 PMCID: PMC9993429 DOI: 10.1126/science.ade5320] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
From the preparation of pharmaceuticals to enzymatic construction of natural products, carbocations are central to molecular synthesis. Although these reactive intermediates are engaged in stereoselective processes in nature, exerting enantiocontrol over carbocations with synthetic catalysts remains challenging. Many resonance-stabilized tricoordinated carbocations, such as iminium and oxocarbenium ions, have been applied in catalytic enantioselective reactions. However, their dicoordinated counterparts (aryl and vinyl carbocations) have not, despite their emerging utility in chemical synthesis. We report the discovery of a highly enantioselective vinyl carbocation carbon-hydrogen (C-H) insertion reaction enabled by imidodiphosphorimidate organocatalysts. Active site confinement featured in this catalyst class not only enables effective enantiocontrol but also expands the scope of vinyl cation C-H insertion chemistry, which broadens the utility of this transition metal-free C(sp3)-H functionalization platform.
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Affiliation(s)
- Sepand K Nistanaki
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Chloe G Williams
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Benjamin Wigman
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Jonathan J Wong
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Brittany C Haas
- Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA
| | - Stasik Popov
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Jacob Werth
- Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA
| | - K N Houk
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Hosea M Nelson
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
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23
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Xu J, Grosslight S, Mack KA, Nguyen SC, Clagg K, Lim NK, Timmerman JC, Shen J, White NA, Sirois LE, Han C, Zhang H, Sigman MS, Gosselin F. Atroposelective Negishi Coupling Optimization Guided by Multivariate Linear Regression Analysis: Asymmetric Synthesis of KRAS G12C Covalent Inhibitor GDC-6036. J Am Chem Soc 2022; 144:20955-20963. [DOI: 10.1021/jacs.2c09917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Jie Xu
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Samantha Grosslight
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Kyle A. Mack
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Sierra C. Nguyen
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Kyle Clagg
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Ngiap-Kie Lim
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Jacob C. Timmerman
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Jeff Shen
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Nicholas A. White
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Lauren E. Sirois
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Chong Han
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Haiming Zhang
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Matthew S. Sigman
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Francis Gosselin
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
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24
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Kelly SP, Shende VV, Flynn AR, Dan Q, Ye Y, Smith JL, Tsukamoto S, Sigman MS, Sherman DH. Data Science-Driven Analysis of Substrate-Permissive Diketopiperazine Reverse Prenyltransferase NotF: Applications in Protein Engineering and Cascade Biocatalytic Synthesis of (-)-Eurotiumin A. J Am Chem Soc 2022; 144:19326-19336. [PMID: 36223664 PMCID: PMC9831672 DOI: 10.1021/jacs.2c06631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Prenyltransfer is an early-stage carbon-hydrogen bond (C-H) functionalization prevalent in the biosynthesis of a diverse array of biologically active bacterial, fungal, plant, and metazoan diketopiperazine (DKP) alkaloids. Toward the development of a unified strategy for biocatalytic construction of prenylated DKP indole alkaloids, we sought to identify and characterize a substrate-permissive C2 reverse prenyltransferase (PT). As the first tailoring event within the biosynthesis of cytotoxic notoamide metabolites, PT NotF catalyzes C2 reverse prenyltransfer of brevianamide F. Solving a crystal structure of NotF (in complex with native substrate and prenyl donor mimic dimethylallyl S-thiolodiphosphate (DMSPP)) revealed a large, solvent-exposed active site, intimating NotF may possess a significantly broad substrate scope. To assess the substrate selectivity of NotF, we synthesized a panel of 30 sterically and electronically differentiated tryptophanyl DKPs, the majority of which were selectively prenylated by NotF in synthetically useful conversions (2 to >99%). Quantitative representation of this substrate library and development of a descriptive statistical model provided insight into the molecular origins of NotF's substrate promiscuity. This approach enabled the identification of key substrate descriptors (electrophilicity, size, and flexibility) that govern the rate of NotF-catalyzed prenyltransfer, and the development of an "induced fit docking (IFD)-guided" engineering strategy for improved turnover of our largest substrates. We further demonstrated the utility of NotF in tandem with oxidative cyclization using flavin monooxygenase, BvnB. This one-pot, in vitro biocatalytic cascade enabled the first chemoenzymatic synthesis of the marine fungal natural product, (-)-eurotiumin A, in three steps and 60% overall yield.
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Affiliation(s)
- Samantha P. Kelly
- Life Sciences Institute, University of Michigan, Ann Arbor, MI 48109, USA.,Program in Chemical Biology, University of Michigan, Ann Arbor, MI 48109, USA.,These authors contributed equally: Samantha P. Kelly, Vikram V. Shende
| | - Vikram V. Shende
- Life Sciences Institute, University of Michigan, Ann Arbor, MI 48109, USA.,Program in Chemical Biology, University of Michigan, Ann Arbor, MI 48109, USA.,These authors contributed equally: Samantha P. Kelly, Vikram V. Shende
| | - Autumn R. Flynn
- Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA
| | - Qingyun Dan
- Life Sciences Institute, University of Michigan, Ann Arbor, MI 48109, USA.,Department of Biological Chemistry, University of Michigan, Ann Arbor, MI 48109, USA
| | - Ying Ye
- Life Sciences Institute, University of Michigan, Ann Arbor, MI 48109, USA
| | - Janet L. Smith
- Life Sciences Institute, University of Michigan, Ann Arbor, MI 48109, USA.,Department of Biological Chemistry, University of Michigan, Ann Arbor, MI 48109, USA
| | - Sachiko Tsukamoto
- Graduate School of Pharmaceutical Sciences, Kumamoto University, 5-1 Oe-honmachi, Kumamoto 862-0973, Japan
| | - Matthew S. Sigman
- Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA
| | - David H. Sherman
- Life Sciences Institute, University of Michigan, Ann Arbor, MI 48109, USA.,Department of Medicinal Chemistry, University of Michigan, Ann Arbor, MI 48109, USA.,Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI 48109, USA
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25
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Tang T, Jones E, Wild T, Hazra A, Minteer SD, Sigman MS. Investigating Oxidative Addition Mechanisms of Allylic Electrophiles with Low-Valent Ni/Co Catalysts Using Electroanalytical and Data Science Techniques. J Am Chem Soc 2022; 144:20056-20066. [PMID: 36265077 DOI: 10.1021/jacs.2c09120] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
The catalysis by a π-allyl-Co/Ni complex has drawn significant attention recently due to its distinct reactivity in reductive Co/Ni-catalyzed allylation reactions. Despite significant success in reaction development, the critical oxidative addition mechanism to form the π-allyl-Co/Ni complex remains unclear. Herein, we present a study to investigate this process with four catalysis-relevant complexes: Co(MeBPy)Br2, Co(MePhen)Br2, Ni(MeBPy)Br2, and Ni(MePhen)Br2. Enabled by an electroanalytical platform, Co(I)/Ni(I) species were found responsible for the oxidative addition of allyl acetate. Kinetic features of different substrates were characterized through linear free-energy relationship (Hammett-type) studies, statistical modeling, and a DFT computational study. In this process, a coordination-ionization-type transition state was proposed, sharing a similar feature with Pd(0)-mediated oxidative addition in Tsuji-Trost reactions. Computational and ligand structural analysis studies support this mechanism, which should provide key information for next-generation catalyst development.
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Affiliation(s)
- Tianhua Tang
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Eli Jones
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Thérèse Wild
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Avijit Hazra
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Shelley D Minteer
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
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26
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Xu EY, Werth J, Roos CB, Bendelsmith AJ, Sigman MS, Knowles RR. Noncovalent Stabilization of Radical Intermediates in the Enantioselective Hydroamination of Alkenes with Sulfonamides. J Am Chem Soc 2022; 144:18948-18958. [PMID: 36197450 PMCID: PMC9668373 DOI: 10.1021/jacs.2c07099] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Noncovalent interactions (NCIs) are critical elements of molecular recognition in a wide variety of chemical contexts. While NCIs have been studied extensively for closed-shell molecules and ions, very little is understood about the structures and properties of NCIs involving free radical intermediates. In this report, we describe a detailed mechanistic study of the enantioselective radical hydroamination of alkenes with sulfonamides and present evidence suggesting that the basis for asymmetric induction in this process arises from attractive NCIs between a neutral sulfonamidyl radical intermediate and a chiral phosphoric acid (CPA). We describe experimental, computational, and data science-based evidence that identifies the specific radical NCIs that form the basis for the enantioselectivity. Kinetic studies support that C-N bond formation determines the enantioselectivity. Density functional theory investigations revealed the importance of both strong H-bonding between the CPA and the N-centered radical and a network of aryl-based NCIs that serve to stabilize the favored diastereomeric transition state. The contributions of these specific aryl-based NCIs to the selectivity were further confirmed through multivariate linear regression analysis by comparing the measured enantioselectivity to computed descriptors. These results highlight the power of NCIs to enable high levels of enantioselectivity in reactions involving uncharged open-shell intermediates and expand our understanding of radical-molecule interactions.
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Affiliation(s)
- Eve Y. Xu
- Department of Chemistry, Princeton University, Princeton, New Jersey, 08544, United States
| | - Jacob Werth
- Department of Chemistry, University of Utah, Salt Lake City, Utah, 84112, United States
| | - Casey B. Roos
- Department of Chemistry, Princeton University, Princeton, New Jersey, 08544, United States
| | - Andrew J. Bendelsmith
- Department of Chemistry, Princeton University, Princeton, New Jersey, 08544, United States
| | - Matthew S. Sigman
- Department of Chemistry, University of Utah, Salt Lake City, Utah, 84112, United States
| | - Robert R. Knowles
- Department of Chemistry, Princeton University, Princeton, New Jersey, 08544, United States
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27
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Boni YT, Cammarota RC, Liao K, Sigman MS, Davies HML. Leveraging Regio- and Stereoselective C(sp 3)-H Functionalization of Silyl Ethers to Train a Logistic Regression Classification Model for Predicting Site-Selectivity Bias. J Am Chem Soc 2022; 144:15549-15561. [PMID: 35977100 DOI: 10.1021/jacs.2c04383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The C-H functionalization of silyl ethers via carbene-induced C-H insertion represents an efficient synthetic disconnection strategy. In this work, site- and stereoselective C(sp3)-H functionalization at α, γ, δ, and even more distal positions to the siloxy group has been achieved using donor/acceptor carbene intermediates. By exploiting the predilections of Rh2(R-TCPTAD)4 and Rh2(S-2-Cl-5-BrTPCP)4 catalysts to target either more electronically activated or more spatially accessible C-H sites, respectively, divergent desired products can be formed with good diastereocontrol and enantiocontrol. Notably, the reaction can also be extended to enable desymmetrization of meso silyl ethers. Leveraging the broad substrate scope examined in this study, we have trained a machine learning classification model using logistic regression to predict the major C-H functionalization site based on intrinsic substrate reactivity and catalyst propensity for overriding it. This model enables prediction of the major product when applying these C-H functionalization methods to a new substrate of interest. Applying this model broadly, we have demonstrated its utility for guiding late-stage functionalization in complex settings and developed an intuitive visualization tool to assist synthetic chemists in such endeavors.
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Affiliation(s)
- Yannick T Boni
- Department of Chemistry, Emory University, 1515 Dickey Drive, Atlanta, Georgia 30322, United States
| | - Ryan C Cammarota
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Kuangbiao Liao
- Department of Chemistry, Emory University, 1515 Dickey Drive, Atlanta, Georgia 30322, United States
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Huw M L Davies
- Department of Chemistry, Emory University, 1515 Dickey Drive, Atlanta, Georgia 30322, United States
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28
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Gensch T, Smith SR, Colacot TJ, Timsina YN, Xu G, Glasspoole BW, Sigman MS. Design and Application of a Screening Set for Monophosphine Ligands in Cross-Coupling. ACS Catal 2022. [DOI: 10.1021/acscatal.2c01970] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Tobias Gensch
- Department of Chemistry, TU Berlin, Straße des 17. Juni 135, Sekr. C2, 10623 Berlin, Germany
| | - Sleight R. Smith
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Thomas J. Colacot
- MilliporeSigma, 6000 N. Teutonia Ave, Milwaukee, Wisconsin 53209, United States
| | - Yam N. Timsina
- MilliporeSigma, 6000 N. Teutonia Ave, Milwaukee, Wisconsin 53209, United States
| | - Guolin Xu
- MilliporeSigma, 6000 N. Teutonia Ave, Milwaukee, Wisconsin 53209, United States
| | - Ben W. Glasspoole
- MilliporeSigma, 6000 N. Teutonia Ave, Milwaukee, Wisconsin 53209, United States
| | - Matthew S. Sigman
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
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29
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Gnaim S, Bauer A, Zhang HJ, Chen L, Gannett C, Malapit CA, Hill DE, Vogt D, Tang T, Daley RA, Hao W, Zeng R, Quertenmont M, Beck WD, Kandahari E, Vantourout JC, Echeverria PG, Abruna HD, Blackmond DG, Minteer SD, Reisman SE, Sigman MS, Baran PS. Cobalt-electrocatalytic HAT for functionalization of unsaturated C-C bonds. Nature 2022; 605:687-695. [PMID: 35614246 DOI: 10.1038/s41586-022-04595-3] [Citation(s) in RCA: 39] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 03/01/2022] [Indexed: 12/23/2022]
Abstract
The study and application of transition metal hydrides (TMHs) has been an active area of chemical research since the early 1960s1, for energy storage, through the reduction of protons to generate hydrogen2,3, and for organic synthesis, for the functionalization of unsaturated C-C, C-O and C-N bonds4,5. In the former instance, electrochemical means for driving such reactivity has been common place since the 1950s6 but the use of stoichiometric exogenous organic- and metal-based reductants to harness the power of TMHs in synthetic chemistry remains the norm. In particular, cobalt-based TMHs have found widespread use for the derivatization of olefins and alkynes in complex molecule construction, often by a net hydrogen atom transfer (HAT)7. Here we show how an electrocatalytic approach inspired by decades of energy storage research can be made use of in the context of modern organic synthesis. This strategy not only offers benefits in terms of sustainability and efficiency but also enables enhanced chemoselectivity and distinct, tunable reactivity. Ten different reaction manifolds across dozens of substrates are exemplified, along with detailed mechanistic insights into this scalable electrochemical entry into Co-H generation that takes place through a low-valent intermediate.
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Affiliation(s)
- Samer Gnaim
- Department of Chemistry, The Scripps Research Institute (TSRI), La Jolla, CA, USA
| | - Adriano Bauer
- Department of Chemistry, The Scripps Research Institute (TSRI), La Jolla, CA, USA
| | - Hai-Jun Zhang
- Department of Chemistry, The Scripps Research Institute (TSRI), La Jolla, CA, USA
| | - Longrui Chen
- Department of Chemistry, The Scripps Research Institute (TSRI), La Jolla, CA, USA
| | - Cara Gannett
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, USA
| | | | - David E Hill
- The Warren and Katharine Schlinger Laboratory for Chemistry and Chemical Engineering, Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA
| | - David Vogt
- Department of Chemistry, University of Utah, Salt Lake City, UT, USA
| | - Tianhua Tang
- Department of Chemistry, University of Utah, Salt Lake City, UT, USA
| | - Ryan A Daley
- Department of Chemistry, The Scripps Research Institute (TSRI), La Jolla, CA, USA
| | - Wei Hao
- Department of Chemistry, The Scripps Research Institute (TSRI), La Jolla, CA, USA
| | - Rui Zeng
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, USA
| | | | - Wesley D Beck
- Department of Chemistry, University of Utah, Salt Lake City, UT, USA
| | - Elya Kandahari
- The Warren and Katharine Schlinger Laboratory for Chemistry and Chemical Engineering, Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Julien C Vantourout
- Department of Chemistry, The Scripps Research Institute (TSRI), La Jolla, CA, USA
| | | | - Hector D Abruna
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, USA.
| | - Donna G Blackmond
- Department of Chemistry, The Scripps Research Institute (TSRI), La Jolla, CA, USA.
| | - Shelley D Minteer
- Department of Chemistry, University of Utah, Salt Lake City, UT, USA.
| | - Sarah E Reisman
- The Warren and Katharine Schlinger Laboratory for Chemistry and Chemical Engineering, Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA.
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, Salt Lake City, UT, USA.
| | - Phil S Baran
- Department of Chemistry, The Scripps Research Institute (TSRI), La Jolla, CA, USA.
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30
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Haas BC, Goetz AE, Bahamonde A, McWilliams JC, Sigman MS. Predicting relative efficiency of amide bond formation using multivariate linear regression. Proc Natl Acad Sci U S A 2022; 119:e2118451119. [PMID: 35412905 PMCID: PMC9169781 DOI: 10.1073/pnas.2118451119] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 02/09/2022] [Indexed: 01/29/2023] Open
Abstract
Amides are ubiquitous in biologically active natural products and commercial drugs. The most common strategy for introducing this functional group is the coupling of a carboxylic acid with an amine, which requires the use of a coupling reagent to facilitate elimination of water. However, the optimal reaction conditions often appear rather arbitrary to the specific reaction. Herein, we report the development of statistical models correlating measured rates to physical organic descriptors to enable the prediction of reaction rates for untested carboxylic acid/amine pairs. The key to the success of this endeavor was the development of an end-to-end data science–based workflow to select a set of coupling partners that are appropriately distributed in chemical space to facilitate statistical model development. By using a parameterization, dimensionality reduction, and clustering protocol, a training set was identified. Reaction rates for a range of carboxylic acid and primary alkyl amine couplings utilizing carbonyldiimidazole (CDI) as the coupling reagent were measured. The collected rates span five orders of magnitude, confirming that the designed training set encompasses a wide range of chemical space necessary for effective model development. Regressing these rates with high-level density functional theory (DFT) descriptors allowed for identification of a statistical model wherein the molecular features of the carboxylic acid are primarily responsible for the observed rates. Finally, out-of-sample amide couplings are used to determine the limitations and effectiveness of the model.
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Affiliation(s)
- Brittany C. Haas
- Department of Chemistry, University of Utah, Salt Lake City, UT 84112
| | - Adam E. Goetz
- Chemical Research and Development, Groton Laboratories, Pfizer Worldwide Research and Development, Groton, CT 06340
| | - Ana Bahamonde
- Department of Chemistry, University of Utah, Salt Lake City, UT 84112
| | - J. Christopher McWilliams
- Chemical Research and Development, Groton Laboratories, Pfizer Worldwide Research and Development, Groton, CT 06340
| | - Matthew S. Sigman
- Department of Chemistry, University of Utah, Salt Lake City, UT 84112
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31
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Akita S, Guo JY, Seidel FW, Sigman MS, Nozaki K. Statistical Analysis of Catalytic Performance in Ethylene/Methyl Acrylate Copolymerization Using Palladium/Phosphine-Sulfonate Catalysts. Organometallics 2022. [DOI: 10.1021/acs.organomet.2c00066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Shumpei Akita
- Department of Chemistry and Biotechnology, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
| | - Jing-Yao Guo
- Department of Chemistry, College of Science, The University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Falk W. Seidel
- Department of Chemistry and Biotechnology, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
| | - Matthew S. Sigman
- Department of Chemistry, College of Science, The University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Kyoko Nozaki
- Department of Chemistry and Biotechnology, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
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32
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Tang T, Friede NC, Minteer SD, Sigman MS. Comparing Halogen Atom Abstraction Kinetics for Mn(I), Fe(I), Co(I), and Ni(I) Complexes by Combining Electroanalytical and Statistical Modeling. European J Org Chem 2022. [DOI: 10.1002/ejoc.202200064] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
| | | | - Shelley D. Minteer
- The University of Utah Department of Chemistry 315 S 1400 E Room 2020 84112 Salt Lake City UNITED STATES
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33
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Affiliation(s)
- Jennifer M. Crawford
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Tobias Gensch
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Matthew S. Sigman
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Jennifer M. Elward
- Molecular Design, GlaxoSmithKline, 1250 S. Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Janelle E. Steves
- Chemical Development, GlaxoSmithKline, 1250 S. Collegeville Road, Collegeville, Pennsylvania 19426, United States
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34
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Gensch T, Dos Passos Gomes G, Friederich P, Peters E, Gaudin T, Pollice R, Jorner K, Nigam A, Lindner-D'Addario M, Sigman MS, Aspuru-Guzik A. A Comprehensive Discovery Platform for Organophosphorus Ligands for Catalysis. J Am Chem Soc 2022; 144:1205-1217. [PMID: 35020383 DOI: 10.1021/jacs.1c09718] [Citation(s) in RCA: 53] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The design of molecular catalysts typically involves reconciling multiple conflicting property requirements, largely relying on human intuition and local structural searches. However, the vast number of potential catalysts requires pruning of the candidate space by efficient property prediction with quantitative structure-property relationships. Data-driven workflows embedded in a library of potential catalysts can be used to build predictive models for catalyst performance and serve as a blueprint for novel catalyst designs. Herein we introduce kraken, 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. We demonstrate the application of kraken to systematically explore the property space of organophosphorus ligands and how existing data sets in catalysis can be used to accelerate ligand selection during reaction optimization.
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Affiliation(s)
- Tobias Gensch
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States.,Department of Chemistry, TU Berlin, Straße des 17. Juni 135, Sekr. C2, 10623 Berlin, Germany
| | - Gabriel Dos Passos Gomes
- Chemical Physics Theory Group, Department of Chemistry, University of Toronto, 80 St. George St., Toronto, Ontario M5S 3H6, Canada.,Department of Computer Science, University of Toronto, 214 College St., Toronto, Ontario M5T 3A1, Canada.,Vector Institute for Artificial Intelligence, 661 University Ave. Suite 710, Toronto, Ontario M5G 1M1, Canada
| | - Pascal Friederich
- Chemical Physics Theory Group, Department of Chemistry, University of Toronto, 80 St. George St., Toronto, Ontario M5S 3H6, Canada.,Department of Computer Science, University of Toronto, 214 College St., Toronto, Ontario M5T 3A1, Canada.,Institute of Nanotechnology, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
| | - Ellyn Peters
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Théophile Gaudin
- Department of Computer Science, University of Toronto, 214 College St., Toronto, Ontario M5T 3A1, Canada.,IBM Research Zurich, Säumerstrasse 4, 8803 Rüschlikon, Switzerland
| | - Robert Pollice
- Chemical Physics Theory Group, Department of Chemistry, University of Toronto, 80 St. George St., Toronto, Ontario M5S 3H6, Canada.,Department of Computer Science, University of Toronto, 214 College St., Toronto, Ontario M5T 3A1, Canada
| | - Kjell Jorner
- Chemical Physics Theory Group, Department of Chemistry, University of Toronto, 80 St. George St., Toronto, Ontario M5S 3H6, Canada.,Department of Computer Science, University of Toronto, 214 College St., Toronto, Ontario M5T 3A1, Canada.,Early Chemical Development, Pharmaceutical Sciences, R&D, AstraZeneca, Macclesfield K10 2NA, United Kingdom
| | - AkshatKumar Nigam
- Chemical Physics Theory Group, Department of Chemistry, University of Toronto, 80 St. George St., Toronto, Ontario M5S 3H6, Canada.,Department of Computer Science, University of Toronto, 214 College St., Toronto, Ontario M5T 3A1, Canada
| | - Michael Lindner-D'Addario
- Chemical Physics Theory Group, Department of Chemistry, University of Toronto, 80 St. George St., Toronto, Ontario M5S 3H6, Canada.,Department of Computer Science, University of Toronto, 214 College St., Toronto, Ontario M5T 3A1, Canada
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Alán Aspuru-Guzik
- Chemical Physics Theory Group, Department of Chemistry, University of Toronto, 80 St. George St., Toronto, Ontario M5S 3H6, Canada.,Department of Computer Science, University of Toronto, 214 College St., Toronto, Ontario M5T 3A1, Canada.,Vector Institute for Artificial Intelligence, 661 University Ave. Suite 710, Toronto, Ontario M5G 1M1, Canada.,Lebovic Fellow, Canadian Institute for Advanced Research (CIFAR), 661 University Ave., Toronto, Ontario M5G, Canada
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35
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Cammarota RC, Liu W, Bacsa J, Davies HML, Sigman MS. Mechanistically Guided Workflow for Relating Complex Reactive Site Topologies to Catalyst Performance in C–H Functionalization Reactions. J Am Chem Soc 2022; 144:1881-1898. [DOI: 10.1021/jacs.1c12198] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Ryan C. Cammarota
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - Wenbin Liu
- Department of Chemistry, Emory University, 1515 Dickey Drive, Atlanta, Georgia 30322, United States
| | - John Bacsa
- Department of Chemistry, Emory University, 1515 Dickey Drive, Atlanta, Georgia 30322, United States
| | - Huw M. L. Davies
- Department of Chemistry, Emory University, 1515 Dickey Drive, Atlanta, Georgia 30322, United States
| | - Matthew S. Sigman
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
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36
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Yan Y, Vogt DB, Vaid TP, Sigman MS, Sanford MS. Development of High Energy Density Diaminocyclopropenium‐Phenothiazine Hybrid Catholytes for Non‐Aqueous Redox Flow Batteries. Angew Chem Int Ed Engl 2021. [DOI: 10.1002/ange.202111939] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Yichao Yan
- Department of Chemistry University of Michigan 930 North University Avenue Ann Arbor MI 48109 USA
- Joint Center for Energy Storage Research (JCESR) 9700 South Cass Avenue Argonne IL 60439 USA
| | - David B. Vogt
- Department of Chemistry University of Utah 315 South 1400 East Salt Lake City UT 84112 USA
- Joint Center for Energy Storage Research (JCESR) 9700 South Cass Avenue Argonne IL 60439 USA
| | - Thomas P. Vaid
- Department of Chemistry University of Michigan 930 North University Avenue Ann Arbor MI 48109 USA
- Joint Center for Energy Storage Research (JCESR) 9700 South Cass Avenue Argonne IL 60439 USA
| | - Matthew S. Sigman
- Department of Chemistry University of Utah 315 South 1400 East Salt Lake City UT 84112 USA
- Joint Center for Energy Storage Research (JCESR) 9700 South Cass Avenue Argonne IL 60439 USA
| | - Melanie S. Sanford
- Department of Chemistry University of Michigan 930 North University Avenue Ann Arbor MI 48109 USA
- Joint Center for Energy Storage Research (JCESR) 9700 South Cass Avenue Argonne IL 60439 USA
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37
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Zell D, Kingston C, Jermaks J, Smith SR, Seeger N, Wassmer J, Sirois LE, Han C, Zhang H, Sigman MS, Gosselin F. Stereoconvergent and -divergent Synthesis of Tetrasubstituted Alkenes by Nickel-Catalyzed Cross-Couplings. J Am Chem Soc 2021; 143:19078-19090. [PMID: 34735129 DOI: 10.1021/jacs.1c08399] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
We report the development of a method to diastereoselectively access tetrasubstituted alkenes via nickel-catalyzed Suzuki-Miyaura cross-couplings of enol tosylates and boronic acid esters. Either diastereomeric product was selectively accessed from a mixture of enol tosylate starting material diastereomers in a convergent reaction by judicious choice of the ligand and reaction conditions. A similar protocol also enabled a divergent synthesis of each product isomer from diastereomerically pure enol tosylates. Notably, high-throughput optimization of the monophosphine ligands was guided by chemical space analysis of the kraken library to ensure a diverse selection of ligands was examined. Stereoelectronic analysis of the results provided insight into the requirements for reactive and selective ligands in this transformation. The synthetic utility of the optimized catalytic system was then probed in the stereoselective synthesis of various tetrasubstituted alkenes, with yields up to 94% and diastereomeric ratios up to 99:1 Z/E and 93:7 E/Z observed. Moreover, a detailed computational analysis and experimental mechanistic studies provided key insights into the nature of the underlying isomerization process impacting selectivity in the cross-coupling.
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Affiliation(s)
- Daniel Zell
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Cian Kingston
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Janis Jermaks
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Sleight R Smith
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Natalie Seeger
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Jana Wassmer
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Lauren E Sirois
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Chong Han
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Haiming Zhang
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Francis Gosselin
- Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
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38
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Dotson JJ, Anslyn EV, Sigman MS. A Data-Driven Approach to the Development and Understanding of Chiroptical Sensors for Alcohols with Remote γ-Stereocenters. J Am Chem Soc 2021; 143:19187-19198. [PMID: 34735763 DOI: 10.1021/jacs.1c09443] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Dynamic covalent chemistry-based sensors have recently emerged as powerful tools to rapidly determine the enantiomeric excess of organic small molecules. While a bevy of sensors have been developed, those for flexible molecules with stereocenters remote to the functional group that binds the chiroptical sensor remain scarce. In this study, we develop an iterative, data-driven workflow to design and analyze a chiroptical sensor capable of assessing challenging acyclic γ-stereogenic alcohols. Following sensor optimization, the mechanism of sensing was probed with a combination of computational parametrization of the sensor molecules, statistical modeling, and high-level density functional theory (DFT) calculations. These were used to elucidate the mechanism of stereochemical recognition and revealed that competing attractive noncovalent interactions (NCIs) determine the overall performance of the sensor. It is anticipated that the data-driven workflows developed herein will be generally applicable to the development and understanding of dynamic covalent and supramolecular sensors.
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Affiliation(s)
- Jordan J Dotson
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Eric V Anslyn
- Department of Chemistry, University of Texas at Austin, Austin, Texas 78712, United States
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
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39
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De Jesus Silva J, Bartalucci N, Jelier B, Grosslight S, Gensch T, Schünemann C, Müller B, Kamer PCJ, Copéret C, Sigman MS, Togni A. Development and Molecular Understanding of a Pd‐Catalyzed Cyanation of Aryl Boronic Acids Enabled by High‐Throughput Experimentation and Data Analysis. Helv Chim Acta 2021. [DOI: 10.1002/hlca.202100200] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Affiliation(s)
- Jordan De Jesus Silva
- Department of Chemistry and Applied Biosciences ETH Zürich Vladimir-Prelog-Weg 1–5 CH-8093 Zürich Switzerland
| | - Niccolò Bartalucci
- Department of Chemistry and Applied Biosciences ETH Zürich Vladimir-Prelog-Weg 1–5 CH-8093 Zürich Switzerland
| | - Benson Jelier
- Department of Chemistry and Applied Biosciences ETH Zürich Vladimir-Prelog-Weg 1–5 CH-8093 Zürich Switzerland
| | - Samantha Grosslight
- Department of Chemistry University of Utah 315 South 1400 East Salt Lake City Utah 84112 United States
| | - Tobias Gensch
- Department of Chemistry University of Utah 315 South 1400 East Salt Lake City Utah 84112 United States
- Department of Chemistry TU Berlin Straße des 17. Juni 135 DE-10623 Berlin Germany
| | - Claas Schünemann
- Leibniz-Institute for Catalysis e. V. Albert-Einstein-Straße 29a DE-18059 Rostock Germany
| | - Bernd Müller
- Leibniz-Institute for Catalysis e. V. Albert-Einstein-Straße 29a DE-18059 Rostock Germany
| | - Paul C. J. Kamer
- Leibniz-Institute for Catalysis e. V. Albert-Einstein-Straße 29a DE-18059 Rostock Germany
| | - Christophe Copéret
- Department of Chemistry and Applied Biosciences ETH Zürich Vladimir-Prelog-Weg 1–5 CH-8093 Zürich Switzerland
| | - Matthew S. Sigman
- Department of Chemistry University of Utah 315 South 1400 East Salt Lake City Utah 84112 United States
| | - Antonio Togni
- Department of Chemistry and Applied Biosciences ETH Zürich Vladimir-Prelog-Weg 1–5 CH-8093 Zürich Switzerland
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40
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Williams W, Zeng L, Gensch T, Sigman MS, Doyle AG, Anslyn EV. The Evolution of Data-Driven Modeling in Organic Chemistry. ACS Cent Sci 2021; 7:1622-1637. [PMID: 34729406 PMCID: PMC8554870 DOI: 10.1021/acscentsci.1c00535] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Indexed: 05/14/2023]
Abstract
Organic chemistry is replete with complex relationships: for example, how a reactant's structure relates to the resulting product formed; how reaction conditions relate to yield; how a catalyst's structure relates to enantioselectivity. Questions like these are at the foundation of understanding reactivity and developing novel and improved reactions. An approach to probing these questions that is both longstanding and contemporary is data-driven modeling. Here, we provide a synopsis of the history of data-driven modeling in organic chemistry and the terms used to describe these endeavors. We include a timeline of the steps that led to its current state. The case studies included highlight how, as a community, we have advanced physical organic chemistry tools with the aid of computers and data to augment the intuition of expert chemists and to facilitate the prediction of structure-activity and structure-property relationships.
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Affiliation(s)
- Wendy
L. Williams
- Department
of Chemistry and Biochemistry, University
of California, Los Angeles, California 90095, United States
- Department
of Chemistry, Princeton University, Princeton, New Jersey 08544, United States
| | - Lingyu Zeng
- Department
of Chemistry, The University of Texas at
Austin, Austin, Texas 78712, United States
| | - Tobias Gensch
- Department
of Chemistry, TU Berlin, Straße des 17. Juni 135, Sekr. C2, 10623 Berlin, Germany
| | - Matthew S. Sigman
- Department
of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Abigail G. Doyle
- Department
of Chemistry and Biochemistry, University
of California, Los Angeles, California 90095, United States
- Department
of Chemistry, Princeton University, Princeton, New Jersey 08544, United States
| | - Eric V. Anslyn
- Department
of Chemistry, The University of Texas at
Austin, Austin, Texas 78712, United States
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41
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Yan Y, Vogt DB, Vaid TP, Sigman MS, Sanford MS. Development of High Energy Density Diaminocyclopropenium-Phenothiazine Hybrid Catholytes for Non-Aqueous Redox Flow Batteries. Angew Chem Int Ed Engl 2021; 60:27039-27045. [PMID: 34672070 DOI: 10.1002/anie.202111939] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Indexed: 11/08/2022]
Abstract
This report describes the design of diaminocyclopropenium-phenothiazine hybrid catholytes for non-aqueous redox flow batteries. The molecules are synthesized in a rapid and modular fashion by appending a diaminocyclopropenium (DAC) substituent to the nitrogen of the phenothiazine. Combining a versatile C-N coupling protocol (which provides access to diverse derivatives) with computation and structure-property analysis enabled the identification of a catholyte that displays stable two-electron cycling at potentials of 0.64 and 1.00 V vs. Fc/Fc+ as well as high solubility in all oxidation states (≥0.45 M in TBAPF6 /MeCN). This catholyte was deployed in a high energy density two-electron RFB, exhibiting >90 % capacity retention over 266 hours of flow cell cycling at >0.5 M electron concentration.
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Affiliation(s)
- Yichao Yan
- Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, MI, 48109, USA.,Joint Center for Energy Storage Research (JCESR), 9700 South Cass Avenue, Argonne, IL, 60439, USA
| | - David B Vogt
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, UT, 84112, USA.,Joint Center for Energy Storage Research (JCESR), 9700 South Cass Avenue, Argonne, IL, 60439, USA
| | - Thomas P Vaid
- Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, MI, 48109, USA.,Joint Center for Energy Storage Research (JCESR), 9700 South Cass Avenue, Argonne, IL, 60439, USA
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, UT, 84112, USA.,Joint Center for Energy Storage Research (JCESR), 9700 South Cass Avenue, Argonne, IL, 60439, USA
| | - Melanie S Sanford
- Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, MI, 48109, USA.,Joint Center for Energy Storage Research (JCESR), 9700 South Cass Avenue, Argonne, IL, 60439, USA
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42
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Newman-Stonebraker SH, Smith SR, Borowski JE, Peters E, Gensch T, Johnson HC, Sigman MS, Doyle AG. Univariate classification of phosphine ligation state and reactivity in cross-coupling catalysis. Science 2021; 374:301-308. [PMID: 34648340 DOI: 10.1126/science.abj4213] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
[Figure: see text].
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Affiliation(s)
| | - Sleight R Smith
- Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA
| | - Julia E Borowski
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
| | - Ellyn Peters
- Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA
| | - Tobias Gensch
- Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA
| | - Heather C Johnson
- Process Research and Development, Merck & Co., Inc., Rahway, NJ 07065, USA
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA
| | - Abigail G Doyle
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
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43
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Yan Y, Robinson SG, Vaid TP, Sigman MS, Sanford MS. Simultaneously Enhancing the Redox Potential and Stability of Multi-Redox Organic Catholytes by Incorporating Cyclopropenium Substituents. J Am Chem Soc 2021; 143:13450-13459. [PMID: 34387084 DOI: 10.1021/jacs.1c07237] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
High redox potential, two-electron organic catholytes for nonaqueous redox flow batteries were developed by appending diaminocyclopropenium (DAC) substituents to phenazine and phenothiazine cores. The parent heterocycles exhibit two partially reversible oxidations at moderate potentials [both at lower than 0.7 V vs ferrocene/ferrocenium (Fc/Fc+)]. The incorporation of DAC substituents has a dual effect on these systems. The DAC groups increase the redox potential of both couples by ∼300 mV while simultaneously rendering the second oxidation (which occurs at 1.20 V vs Fc/Fc+ in the phenothiazine derivative) reversible. The electron-withdrawing nature of the DAC unit is responsible for the increase in redox potential, while the DAC substituents stabilize oxidized forms of the molecules through resonance delocalization of charge and unpaired spin density. These new catholytes were deployed in two-electron redox flow batteries that exhibit voltages of up to 2.0 V and no detectable crossover over 250 cycles.
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Affiliation(s)
- Yichao Yan
- Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, Michigan 48109, United States.,Joint Center for Energy Storage Research (JCESR), 9700 South Cass Avenue, Argonne, Illinois 60439, United States
| | - Sophia G Robinson
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States.,Joint Center for Energy Storage Research (JCESR), 9700 South Cass Avenue, Argonne, Illinois 60439, United States
| | - Thomas P Vaid
- Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, Michigan 48109, United States.,Joint Center for Energy Storage Research (JCESR), 9700 South Cass Avenue, Argonne, Illinois 60439, United States
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States.,Joint Center for Energy Storage Research (JCESR), 9700 South Cass Avenue, Argonne, Illinois 60439, United States
| | - Melanie S Sanford
- Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, Michigan 48109, United States.,Joint Center for Energy Storage Research (JCESR), 9700 South Cass Avenue, Argonne, Illinois 60439, United States
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44
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Griffin JD, Vogt DB, Du Bois J, Sigman MS. Mechanistic Guidance Leads to Enhanced Site-Selectivity in C–H Oxidation Reactions Catalyzed by Ruthenium bis(Bipyridine) Complexes. ACS Catal 2021. [DOI: 10.1021/acscatal.1c02593] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Jeremy D. Griffin
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - David B. Vogt
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
| | - J. Du Bois
- Department of Chemistry, Stanford University, 337 Campus Drive, Stanford, California 94305, United States
| | - Matthew S. Sigman
- Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112, United States
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45
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Abstract
ConspectusAt the heart of synthetic chemistry is the holy grail of predictable catalyst design. In particular, researchers involved in reaction development in asymmetric catalysis have pursued a variety of strategies toward this goal. This is driven by both the pragmatic need to achieve high selectivities and the inability to readily identify why a certain catalyst is effective for a given reaction. While empiricism and intuition have dominated the field of asymmetric catalysis since its inception, enantioselectivity offers a mechanistically rich platform to interrogate catalyst-structure response patterns that explain the performance of a particular catalyst or substrate.In the early stages of an asymmetric reaction development campaign, the overarching mechanism of the reaction, catalyst speciation, the turnover limiting step, and many other details are unknown or posited based on related reactions. Considering the unclear details leading to a successful reaction, initial enantioselectivity data are often used to intuitively guide the ultimate direction of optimization. However, if the conditions of the Curtin-Hammett principle are satisfied, then measured enantioselectivity can be directly connected to the ensemble of diastereomeric transition states (TSs) that lead to the enantiomeric products, and the associated free energy difference between competing TSs (ΔΔG⧧ = -RT ln[(S)/(R)], where (S) and (R) represent the concentrations of the enantiomeric products). We, and others, speculated that this important piece of information can be leveraged to guide reaction optimization in a quantitative way.Although traditional linear free energy relationships (LFERs), such as Hammett plots, have been used to illuminate important mechanistic features, we sought to develop data science derived tools to expand the power of LFERs in order to describe complex reactions frequently encountered in modern asymmetric catalysis. Specifically, we investigated whether enantioselectivity data from a reaction can be quantitatively connected to the attributes of reaction components, such as catalyst and substrate structural features, to harness data for asymmetric catalyst design.In this context, we developed a workflow to relate computationally derived features of reaction components to enantioselectivity using data science tools. The mathematical representation of molecules can incorporate many aspects of a transformation, such as molecular features from substrate, product, catalyst, and proposed transition states. Statistical models relating these features to reaction outputs can be used for various tasks, such as performance prediction of untested molecules. Perhaps most importantly, statistical models can guide the generation of mechanistic hypotheses that are embedded within complex patterns of reaction responses. Overall, merging traditional physical organic experiments with statistical modeling techniques creates a feedback loop that enables both evaluation of multiple mechanistic hypotheses and future catalyst design. In this Account, we highlight the evolution and application of this approach in the context of a collaborative program based on chiral phosphoric acid catalysts (CPAs) in asymmetric catalysis.
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Affiliation(s)
- Jennifer M Crawford
- Department of Chemistry, University of Utah, 315 S. 1400 E., Salt Lake City, Utah 84112, United States
| | - Cian Kingston
- Department of Chemistry, University of Utah, 315 S. 1400 E., Salt Lake City, Utah 84112, United States
| | - F Dean Toste
- Department of Chemistry, University of California, Berkeley, California 94720, United States
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, 315 S. 1400 E., Salt Lake City, Utah 84112, United States
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46
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Abstract
![]()
Herein, we report a reaction that
selectively generates 3-arylpyridine
and quinoline motifs by inserting aryl carbynyl cation equivalents
into pyrrole and indole cores, respectively. By employing α-chlorodiazirines
as thermal precursors to the corresponding chlorocarbenes, the traditional
haloform-based protocol central to the parent Ciamician-Dennstedt
rearrangement can be modified to directly afford 3-(hetero)arylpyridines
and quinolines. Chlorodiazirines are conveniently prepared in a single
step by oxidation of commercially available amidinium salts. Selectivity
as a function of pyrrole substitution pattern was examined, and a
predictive model based on steric effects is put forward, with DFT
calculations supporting a selectivity-determining cyclopropanation
step. Computations surprisingly indicate that the stereochemistry
of cyclopropanation is of little consequence to the subsequent electrocyclic
ring opening that forges the pyridine core, due to a compensatory
homoaromatic stabilization that counterbalances orbital-controlled
torquoselectivity effects. The utility of this skeletal transform
is further demonstrated through the preparation of quinolinophanes
and the skeletal editing of pharmaceutically relevant pyrroles.
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Affiliation(s)
- Balu D Dherange
- Department of Chemistry, University of Chicago, Chicago, Illinois 60637, United States
| | - Patrick Q Kelly
- Department of Chemistry, University of Chicago, Chicago, Illinois 60637, United States
| | - Jordan P Liles
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Mark D Levin
- Department of Chemistry, University of Chicago, Chicago, Illinois 60637, United States
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47
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Christensen M, Yunker LPE, Adedeji F, Häse F, Roch LM, Gensch T, dos Passos Gomes G, Zepel T, Sigman MS, Aspuru-Guzik A, Hein JE. Data-science driven autonomous process optimization. Commun Chem 2021; 4:112. [PMID: 36697524 PMCID: PMC9814253 DOI: 10.1038/s42004-021-00550-x] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 07/14/2021] [Indexed: 01/28/2023] Open
Abstract
Autonomous process optimization involves the human intervention-free exploration of a range process parameters to improve responses such as product yield and selectivity. Utilizing off-the-shelf components, we develop a closed-loop system for carrying out parallel autonomous process optimization experiments in batch. Upon implementation of our system in the optimization of a stereoselective Suzuki-Miyaura coupling, we find that the definition of a set of meaningful, broad, and unbiased process parameters is the most critical aspect of successful optimization. Importantly, we discern that phosphine ligand, a categorical parameter, is vital to determination of the reaction outcome. To date, categorical parameter selection has relied on chemical intuition, potentially introducing bias into the experimental design. In seeking a systematic method for selecting a diverse set of phosphine ligands, we develop a strategy that leverages computed molecular feature clustering. The resulting optimization uncovers conditions to selectively access the desired product isomer in high yield.
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Affiliation(s)
- Melodie Christensen
- grid.17091.3e0000 0001 2288 9830Department of Chemistry, University of British Columbia, Vancouver, BC Canada ,grid.417993.10000 0001 2260 0793Department of Process Research and Development, Merck & Co., Inc., Rahway, NJ USA
| | - Lars P. E. Yunker
- grid.17091.3e0000 0001 2288 9830Department of Chemistry, University of British Columbia, Vancouver, BC Canada
| | - Folarin Adedeji
- grid.417993.10000 0001 2260 0793Department of Process Research and Development, Merck & Co., Inc., Rahway, NJ USA
| | - Florian Häse
- grid.38142.3c000000041936754XDepartment of Chemistry and Chemical Biology, Harvard University, Cambridge, MA USA ,grid.17063.330000 0001 2157 2938Department of Chemistry, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Computer Science, University of Toronto, Toronto, ON Canada ,grid.494618.6Vector Institute for Artificial Intelligence, Toronto, ON Canada ,ChemOS Sàrl, Lausanne, Vaud Switzerland
| | - Loïc M. Roch
- grid.38142.3c000000041936754XDepartment of Chemistry and Chemical Biology, Harvard University, Cambridge, MA USA ,grid.17063.330000 0001 2157 2938Department of Chemistry, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Computer Science, University of Toronto, Toronto, ON Canada ,ChemOS Sàrl, Lausanne, Vaud Switzerland
| | - Tobias Gensch
- grid.223827.e0000 0001 2193 0096Department of Chemistry, University of Utah, Salt Lake City, UT USA
| | - Gabriel dos Passos Gomes
- grid.17063.330000 0001 2157 2938Department of Chemistry, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Computer Science, University of Toronto, Toronto, ON Canada ,grid.494618.6Vector Institute for Artificial Intelligence, Toronto, ON Canada
| | - Tara Zepel
- grid.17091.3e0000 0001 2288 9830Department of Chemistry, University of British Columbia, Vancouver, BC Canada
| | - Matthew S. Sigman
- grid.223827.e0000 0001 2193 0096Department of Chemistry, University of Utah, Salt Lake City, UT USA
| | - Alán Aspuru-Guzik
- grid.38142.3c000000041936754XDepartment of Chemistry and Chemical Biology, Harvard University, Cambridge, MA USA ,grid.17063.330000 0001 2157 2938Department of Chemistry, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Computer Science, University of Toronto, Toronto, ON Canada ,grid.494618.6Vector Institute for Artificial Intelligence, Toronto, ON Canada ,grid.440050.50000 0004 0408 2525Canadian Institute for Advanced Research, Toronto, ON Canada
| | - Jason E. Hein
- grid.17091.3e0000 0001 2288 9830Department of Chemistry, University of British Columbia, Vancouver, BC Canada
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48
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Kulik HJ, Sigman MS. Advancing Discovery in Chemistry with Artificial Intelligence: From Reaction Outcomes to New Materials and Catalysts. Acc Chem Res 2021; 54:2335-2336. [PMID: 34000811 DOI: 10.1021/acs.accounts.1c00232] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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49
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Saito M, Kawamata Y, Meanwell M, Navratil R, Chiodi D, Carlson E, Hu P, Chen L, Udyavara S, Kingston C, Tanwar M, Tyagi S, McKillican BP, Gichinga MG, Schmidt MA, Eastgate MD, Lamberto M, He C, Tang T, Malapit CA, Sigman MS, Minteer SD, Neurock M, Baran PS. N-Ammonium Ylide Mediators for Electrochemical C-H Oxidation. J Am Chem Soc 2021; 143:7859-7867. [PMID: 33983721 DOI: 10.1021/jacs.1c03780] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The site-specific oxidation of strong C(sp3)-H bonds is of uncontested utility in organic synthesis. From simplifying access to metabolites and late-stage diversification of lead compounds to truncating retrosynthetic plans, there is a growing need for new reagents and methods for achieving such a transformation in both academic and industrial circles. One main drawback of current chemical reagents is the lack of diversity with regard to structure and reactivity that prevents a combinatorial approach for rapid screening to be employed. In that regard, directed evolution still holds the greatest promise for achieving complex C-H oxidations in a variety of complex settings. Herein we present a rationally designed platform that provides a step toward this challenge using N-ammonium ylides as electrochemically driven oxidants for site-specific, chemoselective C(sp3)-H oxidation. By taking a first-principles approach guided by computation, these new mediators were identified and rapidly expanded into a library using ubiquitous building blocks and trivial synthesis techniques. The ylide-based approach to C-H oxidation exhibits tunable selectivity that is often exclusive to this class of oxidants and can be applied to real-world problems in the agricultural and pharmaceutical sectors.
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Affiliation(s)
- Masato Saito
- Department of Chemistry, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Yu Kawamata
- Department of Chemistry, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Michael Meanwell
- Department of Chemistry, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Rafael Navratil
- Department of Chemistry, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Debora Chiodi
- Department of Chemistry, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Ethan Carlson
- Department of Chemistry, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Pengfei Hu
- Department of Chemistry, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Longrui Chen
- Department of Chemistry, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Sagar Udyavara
- Department of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, Minnesota 55455, United States
| | - Cian Kingston
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Mayank Tanwar
- Department of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, Minnesota 55455, United States
| | - Sameer Tyagi
- Product Metabolism and Analytical Science, Syngenta Crop Protection, 410 Swing Road, Greensboro, North Carolina 27409, United States
| | - Bruce P McKillican
- Product Metabolism and Analytical Science, Syngenta Crop Protection, 410 Swing Road, Greensboro, North Carolina 27409, United States
| | - Moses G Gichinga
- Product Metabolism and Analytical Science, Syngenta Crop Protection, 410 Swing Road, Greensboro, North Carolina 27409, United States
| | - Michael A Schmidt
- Chemical Process Development, Bristol Myers Squibb, New Brunswick, New Jersey 08903, United States
| | - Martin D Eastgate
- Chemical Process Development, Bristol Myers Squibb, New Brunswick, New Jersey 08903, United States
| | - Massimiliano Lamberto
- Department of Chemistry & Physics, Monmouth University, West Long Branch, New Jersey 07740, United States
| | - Chi He
- Department of Chemistry, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Tianhua Tang
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Christian A Malapit
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Matthew S Sigman
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Shelley D Minteer
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Matthew Neurock
- Department of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, Minnesota 55455, United States
| | - Phil S Baran
- Department of Chemistry, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
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DeLano TJ, Dibrell SE, Lacker CR, Pancoast AR, Poremba KE, Cleary L, Sigman MS, Reisman SE. Nickel-catalyzed asymmetric reductive cross-coupling of α-chloroesters with (hetero)aryl iodides. Chem Sci 2021; 12:7758-7762. [PMID: 34168828 PMCID: PMC8188512 DOI: 10.1039/d1sc00822f] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
An asymmetric reductive cross-coupling of α-chloroesters and (hetero)aryl iodides is reported. This nickel-catalyzed reaction proceeds with a chiral BiOX ligand under mild conditions, affording α-arylesters in good yields and enantioselectivities. The reaction is tolerant of a variety of functional groups, and the resulting products can be converted to pharmaceutically-relevant chiral building blocks. A multivariate linear regression model was developed to quantitatively relate the influence of the α-chloroester substrate and ligand on enantioselectivity. A Ni-catalyzed enantioselective reductive cross-coupling of α-chloroesters and (hetero)aryl iodides is reported. A MLR model was developed to quantitatively relate the influence of the α-chloroester substrate and ligand on enantioselectivity.![]()
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Affiliation(s)
- Travis J DeLano
- The Warren and Katharine Schlinger Laboratory for Chemistry and Chemical Engineering, Division of Chemistry and Chemical Engineering, California Institute of Technology Pasadena California 91125 USA
| | - Sara E Dibrell
- The Warren and Katharine Schlinger Laboratory for Chemistry and Chemical Engineering, Division of Chemistry and Chemical Engineering, California Institute of Technology Pasadena California 91125 USA
| | - Caitlin R Lacker
- The Warren and Katharine Schlinger Laboratory for Chemistry and Chemical Engineering, Division of Chemistry and Chemical Engineering, California Institute of Technology Pasadena California 91125 USA
| | - Adam R Pancoast
- Department of Chemistry, University of Utah 315 South 1400 East Salt Lake City Utah 84112 USA
| | - Kelsey E Poremba
- The Warren and Katharine Schlinger Laboratory for Chemistry and Chemical Engineering, Division of Chemistry and Chemical Engineering, California Institute of Technology Pasadena California 91125 USA
| | - Leah Cleary
- The Warren and Katharine Schlinger Laboratory for Chemistry and Chemical Engineering, Division of Chemistry and Chemical Engineering, California Institute of Technology Pasadena California 91125 USA
| | - Matthew S Sigman
- Department of Chemistry, University of Utah 315 South 1400 East Salt Lake City Utah 84112 USA
| | - Sarah E Reisman
- The Warren and Katharine Schlinger Laboratory for Chemistry and Chemical Engineering, Division of Chemistry and Chemical Engineering, California Institute of Technology Pasadena California 91125 USA
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