A unified predictive model for chiroptical sensing: a substrate-centric approach to predicting circular dichroism outputs across two chemically distinct organic classes

Abstract

This study presents an innovative approach for rapid and reliable determination of circular dichroism outputs using a chiroptical supramolecular sensor based on an oxo-vanadium(V) complex. The research focuses on developing a unified predictive model capable of analyzing two distinct organic classes of chiral substrates: amides and carboxylates. Using a diverse library of forty-one substrates, molecular descriptors were calculated exclusively from the free-substrate structures, without considering the host–guest complex. This approach allowed for the construction of robust statistical models that correlate structural and electronic features of the substrates with the intensity of the induced circular dichroism (CD) signal. The resulting global model, based on only three terms, demonstrates good predictive capability for both substrate classes. This approach eliminates the need for individual calibration curves for each analyte, representing a significant step towards a universal platform for enantiomeric excess (ee) determination. This methodology opens new perspectives for high-throughput chiral analysis, with potential applications in fields such as asymmetric catalysis and drug discovery.