Developing a quantitative structure-property relationships (QSPR) model using Caco-2 cell bioavailability indicators (BA) to predict the BA of phytochemicals.

ABSTRACT:

Background

The present study aimed to measure bioavailability (BA) indicators, including epithelial barrier function, apparent permeability (P_app) and efflux ratio, of 84 types of phytochemicals using Caco-2 cell and to develop predictive model systems using machine learning with a quantitative structure-property relationship (QSPR) model based on BA indicators and an Isomeric Simplified Molecular Input Line Entry System (SMILES). Analysis of phytochemicals was carried out with a validated HPLC analytical method.

Results

With these BA indicators, Isomeric SMILES including information such as the stereochemistry, chemical structure and properties of phytochemicals was encoded to molecular descriptors using PaDEL-Descriptor and alvaDesc. The validity of the dataset

SUBMITTER: Lee KW 

PROVIDER: S-EPMC12355335 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature