In Silico Pharmacokinetic and Microbiota-Integrated Profiling of Resveratrol Analogs

Resveratrol, a polyphenolic compound, possesses extensive biological activities; however, its use in clinical applications is restricted due to its poor bioavailability and rapid metabolism. In the present work, resveratrol and 14 of its structural analogs were screened by a combined <em>in silico</em> methodology. The methodology integrated density functional theory (DFT) calculations, quantitative structure–activity relationship (QSAR) modeling, physiologically based pharmacokinetic (PBPK) simulations, and microbiota-associated interaction considerations. Molecular descriptors were generated from optimized geometries at the DFT level of theory to predict permeability and metabolic characteristics. PBPK modelling was used to simulate the distribution of compounds in different physiological states. In contrast, bioinformatics analysis was used to support the gene expression modulation and the response of the microbial community to the analog structure. Several analogs predicted permeability and metabolic stability significantly better than native resveratrol. Furthermore, some compounds exhibited good associations with gut microbiota and metabolic pathways that may have regulatory functions. The results indicate that certain resveratrol analogs are potential drug candidates for further <em>in vitro</em> and <em>in vivo</em> studies. Furthermore, we report a full computational framework to aid the discovery of rational bioavailable polyphenol-related drugs.