Facial Selectivity in the Diels-Alder Reactions of 2,2-Disubstituted Cyclopent-4-ene-1,3-dione Derivatives and a Computational Examination of the Facial Selectivity of the Diels-Alder Reactions of Structurally Related Dienes and Dienophiles

Computational Examination of (4 + 3) versus (3 + 2) Cycloaddition in the Interception of Nazarov Reactions of Allenyl Vinyl Ketones by Dienes

A computational examination of the tandem Nazarov/cycloaddition process involving an allenyl vinyl ketone with a diene has been carried out using the ωB97X-D/6-311++G(d,p)//ωB97X-D/6-31+G(d,p) method with solvation modeled by SMD-PCM. The barrier for the initial Lewis acid mediated Nazarov reaction, which provided the intermediate cyclic oxylallyl cation, was higher than that for any subsequent cycloaddition. The barrier for the first step of a subsequent stepwise reaction did not vary much with the diene, and the lowest barrier was with the diene in its s-trans conformation. Stepwise formation of a (4 + 3) cycloaddition product was not energetically feasible, but (3 + 2) cycloaddition products could have been produced through low energy pathways. The barrier for a concerted (4 + 3) cycloaddition did depend upon the diene, which was always in an s-cis geometry. The barriers for the compact and the extended geometries for the transition states of (4 + 3) cycloadditions were not much different.

Quantitative structure-activation barrier relationship modeling for Diels-Alder ligations utilizing quantum chemical structural descriptors

Background

In the present study, we show the correlation of quantum chemical structural descriptors with the activation barriers of the Diels-Alder ligations. A set of 72 non-catalysed Diels-Alder reactions were subjected to quantitative structure-activation barrier relationship (QSABR) under the framework of theoretical quantum chemical descriptors calculated solely from the structures of diene and dienophile reactants. Experimental activation barrier data were obtained from literature. Descriptors were computed using Hartree-Fock theory using 6-31G(d) basis set as implemented in Gaussian 09 software.

Results

Variable selection and model development were carried out by stepwise multiple linear regression methodology. Predictive performance of the quantitative structure-activation barrier relationship (QSABR) model was assessed by training and test set concept and by calculating leave-one-out cross-validated Q² and predictive R² values. The QSABR model can explain and predict 86.5% and 80% of the variances, respectively, in the activation energy barrier training data. Alternatively, a neural network model based on back propagation of errors was developed to assess the nonlinearity of the sought correlations between theoretical descriptors and experimental reaction barriers.

Conclusions

A reasonable predictability for the activation barrier of the test set reactions was obtained, which enabled an exploration and interpretation of the significant variables responsible for Diels-Alder interaction between dienes and dienophiles. Thus, studies in the direction of QSABR modelling that provide efficient and fast prediction of activation barriers of the Diels-Alder reactions turn out to be a meaningful alternative to transition state theory based computation.