Optimal Heck Cross‐Coupling Catalysis: A Pseudo‐Pharmaceutical Approach

Burello, Enrico; Rothenberg, Gadi

doi:10.1002/adsc.200303141

Cited by 41 publications

(33 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The PCA and PLS treatment of this dataset is described in detail in our previous paper. [9] Regression Analysis Two different regression methods were used in this study: artificial neural networks (ANN) and multiple linear regression analyses. [7] ANNs attempt to mimic the fault-tolerance and capacity to learn of biological neural systems by modeling the low-level structure of the brain.…”

Section: Experimental Section -Computational Methodsmentioning

confidence: 99%

“…[6 -8] Recently, we examined the application of the QSAR approach to a set of literature data of Heck cross-coupling reactions. [9] Although the reaction mechanism is reasonably well understood, the complexity of the data and the predominance of non-linear effects precluded a full analysis with classical linear methods. Nevertheless, we demonstrated that useful knowledge can be extracted regarding the activity of ligands and solvents.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Combinatorial Explosion in Homogeneous Catalysis: Screening 60,000 Cross‐Coupling Reactions

2004

Self Cite

View full text Add to dashboard Cite

A new approach to the selection of Heck cross-coupling catalysts and reaction conditions is presented, based on a quantitative structure-activity relationship (QSAR) descriptor set that is coupled to linear and non-linear analysis models. A set of steric and electronic descriptors is defined and calculated. The correlations between ligands, substrates, catalyst precursors and reaction conditions in a dataset of 412 Heck reactions are then analyzed using artificial neural networks, classification tree methods, and linear models. The regression and classification models are powerful, with prediction confidence levels as high as 93%. These models are then used to predict the performance (turnover numbers and turnover frequencies) of 60,000 combinations of virtual catalysts and reaction conditions in silico. Furthermore, the models are used to pinpoint mechanistic effects, in this case the important role that small palladium clusters play in Heck cross-coupling. The pros and cons of linear and non-linear models and the application of this approach to the selection of new experiments in high-throughput systems are discussed.

show abstract

Section: Experimental Section -Computational Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Combinatorial Explosion in Homogeneous Catalysis: Screening 60,000 Cross‐Coupling Reactions

2004

Self Cite

View full text Add to dashboard Cite

show abstract

“…The advantage is that the relationship between spaces B and C can be quantified using QSAR and quantitative structureproperty relationship (QSPR) models. [10,11] Note that space B contains molecular descriptor values, rather than structures, but these are related directly to the structures, as we showed recently for the cases of monodentate complexes in Pd-catalysed Heck reactions, [12,13] and bidentate complexes in Ni-catalysed hydrocyanation. [14] Therefore, if one can generate a sufficiently large number of sufficiently diverse structures in space A, and link the spaces A and B, one should be able to predict the relevant figures of merit in space C using QSAR/ QSPR descriptor models.…”

Section: Theory Defining the Catalyst Spacementioning

confidence: 83%

Design and Assembly of Virtual Homogeneous Catalyst Libraries –Towards in silico Catalyst Optimisation

et al. 2006

Self Cite

View full text Add to dashboard Cite

An alternative top-down concept for searching for homogeneous catalysts is introduced. In this approach, three multi-dimensional spaces are considered. These represent the catalysts, the descriptor values (e.g., cone angle, lipophilicity indices), and the figures of merit (e.g., turnover frequency, enantiomeric excess, or product selectivity), respectively. By generating and connecting these spaces, it is possible to screen virtual catalyst libraries and indicate regions in the catalyst space where good catalysts are likely to be found. The generation of the catalyst space from simple building blocks is presented and the application of this approach is demonstrated for two cases: predicting the bite angle in a library of 600 ligandRh complexes, and predicting the linear : branched aldehyde product ratio that these 600 catalysts would give in the hydroformylation of 1-octene. In the latter case, the model is first trained on a set of 39 octene hydroformylation reactions. The limitations and applications of this concept are discussed.

show abstract

“…[11] Here we introduce an additional parameter, the variable importance (VIP), to estimate the contribution of each descriptor in the PLS model. PLS modelling is a simultaneous projection of the variables matrix X and the figures of merit matrix Y on lower-dimensional hyper-planes.…”

Section: Methodsmentioning

confidence: 99%

“…[11] This model was used to preselect candidates from large virtual libraries of monodentate ligands. [13] In this paper, we extend the work to reactions catalysed by bidentate ligands, presenting descriptor models for nickel-catalysed hydrocyanation.…”

Section: Introductionmentioning

confidence: 99%

Ligand Descriptor Analysis in Nickel‐Catalysed Hydrocyanation: A Combined Experimental and Theoretical Study

Burello

Marion²,

Galland³

et al. 2005

Adv Synth Catal

Self Cite

View full text Add to dashboard Cite

The problem of choosing the right chelating ligand for a homogeneously catalysed reaction is outlined. A model is introduced that combines mechanistic information and ligand descriptors. This model is used together with automated synthesis tools to study the structure-activity relationship in a diverse set of forty-two ligands, and extract information on active regions in the catalyst space. The concept is demonstrated on nickel-catalysed hydrocyanation, using bidentate phosphine and phosphite ligands. The charge at the ligating atoms, the rigidity of the molecules, the steric crowding around the Ni atom, and the bite angle are found to be the most important descriptors. A comparison is made with literature hydrocyanation data and approaches for designing new homogeneous catalysts are discussed.

show abstract

Optimal Heck Cross‐Coupling Catalysis: A Pseudo‐Pharmaceutical Approach

Cited by 41 publications

References 40 publications

Combinatorial Explosion in Homogeneous Catalysis: Screening 60,000 Cross‐Coupling Reactions

Combinatorial Explosion in Homogeneous Catalysis: Screening 60,000 Cross‐Coupling Reactions

Design and Assembly of Virtual Homogeneous Catalyst Libraries –Towards in silico Catalyst Optimisation

Ligand Descriptor Analysis in Nickel‐Catalysed Hydrocyanation: A Combined Experimental and Theoretical Study

Contact Info

Product

Resources

About