scholarly journals Data-driven catalyst optimization for stereodivergent asymmetric synthesis of α-allyl carboxylic acids by iridium/boron hybrid catalysis

2021 ◽  
Author(s):  
Hongyu Chen ◽  
Shigeru Yamaguchi ◽  
Yuya Morita ◽  
Hiroyasu Nakao ◽  
Xiang-Ning Zhai ◽  
...  
Keyword(s):  
Asymmetric Synthesis ◽  
Carboxylic Acids ◽  
Asymmetric Catalysis ◽  
Catalyst Design ◽  
Molecular Structures ◽  
Data Driven ◽  
Iridium Catalysts ◽  
Structural Modifications ◽  
Molecular Catalysis ◽  
Catalyst Systems

Abstract Asymmetric catalysis enabling divergent control of multiple stereocenters remains challenging in synthetic organic chemistry. While machine learning-based optimization of molecular catalysis is an emerging approach, data-driven catalyst design to achieve stereodivergent asymmetric synthesis producing multiple reaction outcomes, such as constitutional selectivity, diastereoselectivity, and enantioselectivity, is unprecedented. Here, we report the straightforward identification of asymmetric two-component iridium/boron hybrid catalyst systems for α-C-allylation of carboxylic acids. Structural optimization of the chiral ligands for iridium catalysts was driven by molecular field-based regression analysis with a dataset containing overall 32 molecular structures. The catalyst systems enabled selective access to all the possible isomers of chiral carboxylic acids bearing contiguous stereocenters. This stereodivergent asymmetric catalysis is applicable to late-stage structural modifications of drugs and their derivatives.

scholarly journals Data-Driven Catalyst Optimization for Stereodivergent Asymmetric Synthesis of α-Allyl Carboxylic Acids by Iridium/boron Hybrid Catalysis

2021 ◽  
Author(s):  
Hongyu Chen ◽  
Shigeru Yamaguchi ◽  
Yuya Morita ◽  
Hiroyasu Nakao ◽  
Xiangning Zhai ◽  
...  
Keyword(s):  
Asymmetric Synthesis ◽  
Carboxylic Acids ◽  
Asymmetric Catalysis ◽  
Catalyst Design ◽  
Molecular Structures ◽  
Data Driven ◽  
Iridium Catalysts ◽  
Structural Modifications ◽  
Molecular Catalysis ◽  
Catalyst Systems

Asymmetric catalysis enabling divergent control of multiple stereocenters remains challenging in synthetic organic chemistry. While machine learning-based optimization of molecular catalysis is an emerging approach, data-driven catalyst design to achieve stereodivergent asymmetric synthesis producing multiple reaction outcomes, such as constitutional selectivity, diastereoselectivity, and enantioselectivity, is unprecedented. Here, we report the straightforward identification of asymmetric two-component iridium/boron hybrid catalyst systems for α-C-allylation of carboxylic acids. Structural optimization of the chiral ligands for iridium catalysts was driven by molecular field-based regression analysis with a dataset containing overall 32 molecular structures. The catalyst systems enabled selective access to all the possible isomers of chiral carboxylic acids bearing contiguous stereocenters. This stereodivergent asymmetric catalysis is applicable to late-stage structural modifications of drugs and their derivatives.

scholarly journals Data-Driven Catalyst Optimization for Stereodivergent Asymmetric Synthesis of α-Allyl Carboxylic Acids by Iridium/boron Hybrid Catalysis

2021 ◽  
Author(s):  
Hongyu Chen ◽  
Shigeru Yamaguchi ◽  
Yuya Morita ◽  
Hiroyasu Nakao ◽  
Xiangning Zhai ◽  
...  
Keyword(s):  
Asymmetric Synthesis ◽  
Carboxylic Acids ◽  
Asymmetric Catalysis ◽  
Catalyst Design ◽  
Molecular Structures ◽  
Data Driven ◽  
Iridium Catalysts ◽  
Structural Modifications ◽  
Molecular Catalysis ◽  
Catalyst Systems

Asymmetric catalysis enabling divergent control of multiple stereocenters remains challenging in synthetic organic chemistry. While machine learning-based optimization of molecular catalysis is an emerging approach, data-driven catalyst design to achieve stereodivergent asymmetric synthesis producing multiple reaction outcomes, such as constitutional selectivity, diastereoselectivity, and enantioselectivity, is unprecedented. Here, we report the straightforward identification of asymmetric two-component iridium/boron hybrid catalyst systems for α-C-allylation of carboxylic acids. Structural optimization of the chiral ligands for iridium catalysts was driven by molecular field-based regression analysis with a dataset containing overall 32 molecular structures. The catalyst systems enabled selective access to all the possible isomers of chiral carboxylic acids bearing contiguous stereocenters. This stereodivergent asymmetric catalysis is applicable to late-stage structural modifications of drugs and their derivatives.

Iterative Supervised Principal Component Analysis-Driven Ligand Design for Regioselective Ti-Catalyzed Pyrrole Synthesis

2020 ◽  
Author(s):  
Xin Yi See ◽  
Benjamin Reiner ◽  
Xuelan Wen ◽  
T. Alexander Wheeler ◽  
Channing Klein ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
De Novo ◽  
Principal Component ◽  
Component Analysis ◽  
Catalyst Design ◽  
Data Driven ◽  
Initial Reaction ◽  
Training Set ◽  
Reaction Conditions ◽  
Component Loadings

<div> <div> <div> <p>Herein, we describe the use of iterative supervised principal component analysis (ISPCA) in de novo catalyst design. The regioselective synthesis of 2,5-dimethyl-1,3,4-triphenyl-1H- pyrrole (C) via Ti- catalyzed formal [2+2+1] cycloaddition of phenyl propyne and azobenzene was targeted as a proof of principle. The initial reaction conditions led to an unselective mixture of all possible pyrrole regioisomers. ISPCA was conducted on a training set of catalysts, and their performance was regressed against the scores from the top three principal components. Component loadings from this PCA space along with k-means clustering were used to inform the design of new test catalysts. The selectivity of a prospective test set was predicted in silico using the ISPCA model, and only optimal candidates were synthesized and tested experimentally. This data-driven predictive-modeling workflow was iterated, and after only three generations the catalytic selectivity was improved from 0.5 (statistical mixture of products) to over 11 (> 90% C) by incorporating 2,6-dimethyl- 4-(pyrrolidin-1-yl)pyridine as a ligand. The successful development of a highly selective catalyst without resorting to long, stochastic screening processes demonstrates the inherent power of ISPCA in de novo catalyst design and should motivate the general use of ISPCA in reaction development. </p> </div> </div> </div>

Carbonyl catalysis enables a biomimetic asymmetric Mannich reaction

Science ◽  
2018 ◽  
Vol 360 (6396) ◽  
pp. 1438-1442 ◽  
Author(s):  
Jianfeng Chen ◽  
Xing Gong ◽  
Jianyu Li ◽  
Yingkun Li ◽  
Jiguo Ma ◽  
...  
Keyword(s):  
Asymmetric Synthesis ◽  
High Activity ◽  
Asymmetric Catalysis ◽  
Carbonyl Group ◽  
Mannich Reaction ◽  
Primary Amine ◽  
Chiral Amines ◽  
Carbonyl Groups ◽  
Diphenylphosphinyl Imines

Chiral amines are widely used as catalysts in asymmetric synthesis to activate carbonyl groups for α-functionalization. Carbonyl catalysis reverses that strategy by using a carbonyl group to activate a primary amine. Inspired by biological carbonyl catalysis, which is exemplified by reactions of pyridoxal-dependent enzymes, we developed an N-quaternized pyridoxal catalyst for the asymmetric Mannich reaction of glycinate with aryl N-diphenylphosphinyl imines. The catalyst exhibits high activity and stereoselectivity, likely enabled by enzyme-like cooperative bifunctional activation of the substrates. Our work demonstrates the catalytic utility of the pyridoxal moiety in asymmetric catalysis.

Molecular Structures of Ten Ionic Hydrogen Bond-mediated Anhydrous tert-butylammonium Salts From Different Carboxylic Acids

2021 ◽  
pp. 131917
Author(s):  
Xuejuan Yang ◽  
Yanhong Zhu ◽  
Xinlei Chen ◽  
Xingjun Gao ◽  
Shouwen Jin ◽  
...  
Keyword(s):  
Hydrogen Bond ◽  
Carboxylic Acids ◽  
Molecular Structures

scholarly journals Late-Stage β-C(sp3)–H Deuteration of Carboxylic Acids

2021 ◽  
Author(s):  
Alexander Uttry ◽  
Sourjya Mal ◽  
Manuel van Gemmeren
Keyword(s):  
Carboxylic Acid ◽  
Carboxylic Acids ◽  
Late Stage ◽  
Bioactive Molecules ◽  
Wide Range ◽  
Catalyst Systems ◽  
First Time

Carboxylic acid moieties are highly abundant in bioactive molecules. In this study we describe the late-stage β-C(sp<sup>3</sup>)–H deuteration of free carboxylic acids. Based on our finding that the C–H activation with our catalyst systems is reversible, the de-deuteration process was first optimized. The resulting conditions involve ethylenediamine-based ligands, which, amongst other positions, for the first time enables the functionalization of non-activated methylene β-C(sp<sup>3</sup>)–H bonds and can be used to achieve the desired deuteration when using a deuterated solvent. The reported method allows for the functionalization of a wide range of free carboxylic acids with diverse substitution patterns, as well as the late-stage deuteration of bioactive molecules and related frameworks.

scholarly journals ChemSpaX: Exploration of Chemical Space by Automated Functionalization of Molecular Scaffold

2021 ◽  
Author(s):  
Adarsh Kalikadien ◽  
Evgeny A. Pidko ◽  
Vivek Sinha
Keyword(s):  
Force Field ◽  
High Throughput ◽  
High Throughput Screening ◽  
Chemical Space ◽  
Space Exploration ◽  
Molecular Structures ◽  
Data Driven ◽  
Pincer Complexes ◽  
Cobalt Porphyrin ◽  
Input Structure

<div>Local chemical space exploration of an experimentally synthesized material can be done by making slight structural</div><div>variations of the synthesized material. This generation of many molecular structures with reasonable quality,</div><div>that resemble an existing (chemical) purposeful material, is needed for high-throughput screening purposes in</div><div>material design. Large databases of geometry and chemical properties of transition metal complexes are not</div><div>readily available, although these complexes are widely used in homogeneous catalysis. A Python-based workflow,</div><div>ChemSpaX, that is aimed at automating local chemical space exploration for any type of molecule, is introduced.</div><div>The overall computational workflow of ChemSpaX is explained in more detail. ChemSpaX uses 3D information,</div><div>to place functional groups on an input structure. For example, the input structure can be a catalyst for which one</div><div>wants to use high-throughput screening to investigate if the catalytic activity can be improved. The newly placed</div><div>substituents are optimized using a computationally cheap force-field optimization method. After placement of</div><div>new substituents, higher level optimizations using xTB or DFT instead of force-field optimization are also possible</div><div>in the current workflow. In representative applications of ChemSpaX, it is shown that the structures generated by</div><div>ChemSpaX have a reasonable quality for usage in high-throughput screening applications. Representative applications</div><div>of ChemSpaX are shown by investigating various adducts on functionalized Mn-based pincer complexes,</div><div>hydrogenation of Ru-based pincer complexes, functionalization of cobalt porphyrin complexes and functionalization</div><div>of a bipyridyl functionalized cobalt-porphyrin trapped in a M2L4 type cage complex. Descriptors such as</div><div>the Gibbs free energy of reaction and HOMO-LUMO gap, that can be used in data-driven design and discovery</div><div>of catalysts, were selected and studied in more detail for the selected use cases. The relatively fast GFN2-xTB</div><div>method was used to calculate these descriptors and a comparison was done against DFT calculated descriptors.</div><div>ChemSpaX is open-source and aims to bolster the efforts of the scientific community towards data-driven material</div><div>discovery.</div>

Sign in / Sign up

Export Citation Format

Share Document