Prediction of enantioselectivity in thiol addition to imines catalyzed by chiral phosphoric acids. (26th February 2022)

• Record Type: Journal Article
• Authors: Yu, Xinliang
• Is Part Of: Journal of physical organic chemistry. Volume 35:Number 6(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-02-26
• Subjects: asymmetric catalysis -- chiral phosphoric acids -- enantioselectivity -- machine learning; Chemistry, Physical organic -- Periodicals; 547.1
• DOI: 10.1002/poc.4338
• Languages: English
• ISSNs: 0894-3230

Abstract

Abstract: Predicting enantioselectivities in asymmetric catalytic reactions through chemometric approach is a challenging area. In this paper, quantitative structure−selectivity relationship (QSSR) models were successfully developed for thiol addition to N ‐acylimines catalyzed by chiral phosphoric acids. Ten Dragon molecular descriptors calculated from thiols and phosphoric acid catalysts were used to correlate with 1075 enantioselectivities ΔΔG . Machine learning algorithms, support vector machine (SVM) and random forest (RF), were adopted to build QSSRs after descriptor subset selection based on the multiple linear regression technique. The SVM and RF models, respectively, have coefficient of determination R 2 of 0.925 and 0.944 for the training set, and of 0.837 and 0.851 for the test set. Both SVM and RF models were subjected to internal and external validation and estimation in prediction ability and systematic error. Abstract : This paper reported quantitative structure−selectivity relationship models of enantioselectivities ΔΔG in thiol addition to N ‐acylimines catalyzed by chiral phosphoric acids. Only Dragon descriptors from substrates and catalysts were used to correlate with enantioselectivities by using machine learning algorithms, support vector machine and random forest.