Predicting pungency and understanding the pungency mechanism of capsaicinoids using TOPS-MODE approach.

Abstract:

:Quantitative structure-property relationship (QSPR) models were developed for predicting the pungency of a set of capsaicinoids. Multiple linear regression (MLR) coupled with topological substructural molecular descriptor (TOPS-MODE) approach was used. The best MLR model based on only five orthogonalized TOPS-MODE variables allowed us to obtain a coefficient of determination of 0.954 on the training set. The predictive power of the model was validated through a test set and several external validation parameters. This showed that the TOPS-MODE descriptors weighted by bond dipole moments, van der Waals atomic radii, and the total solute hydrogen bond basicity affected pungency. The contributions of certain bonds and fragments to pungency were used to understand the pungency mechanism of capsaicinoids. The selected model can more accurately predict pungency of capsaicinoids compared than those found in the literature, and especially bring insights into the structural features and chemical factors related to pungency.

journal_name

SAR QSAR Environ Res

authors

Yu S,Jia S,Wang D,Lv Z,Chen Y,Wang N,Yao W,Yuan J

doi

10.1080/1062936X.2020.1777583

subject

Has Abstract

pub_date

2020-07-01 00:00:00

pages

527-545

issue

7

eissn

1062-936X

issn

1029-046X

journal_volume

31

pub_type

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