Novel multitarget-labeled molecular networking for exploring pharmacodynamic compounds of traditional Chinese medicine formulae: a case study of Zhu-Ling decoction

Abstract

Traditional Chinese Medicine (TCM) formulae exert therapeutic effects through the synergistic actions of multiple compounds. The interaction between compounds of TCM and their biological targets can be pivotal in revealing the pharmacodynamic material basis and compatibility mechanisms. Here, a novel strategy named multitarget-labeled molecular networking (MLMN), which combines feature-based molecular networking (FBMN) and -CDOCKER interaction energy (-CIE) calculated from molecular docking, was presented to discover the pharmacodynamic compounds and implemented in a case study of Zhu-Ling Decoction (ZLD), a well-known TCM formula for kidney diseases. First, VOSviewer and Carrot2 were employed to focus on the clinical disease of ZLD, known as chronic glomerulonephritis (CGN) and its five core targets (TGF-β, Smad3, TLR4, IL-6 and Nrf2) for further study. Subsequently, 98 compounds were identified using HPLC-Q-Exactive MS in combination with FBMN. These compounds were then docked with the five core targets as ligands and receptors. The results showed that TGF-β, Smad3, and IL-6 had stronger binding affinities with various chemical compounds in ZLD. Finally, MLMN analysis was proposed to visually and comprehensively display the interactions between compounds in ZLD and multiple targets. Compounds in ZLD, such as poricoic acid A and polyporusterone A, demonstrated good binding affinities with all five targets, suggesting that they are key pharmacodynamic compounds contributing to the efficacy of ZLD against CGN. Finally, the effects of alisol B 23-acetate, poricoic acid A and polyporusterone A in regulating mRNA expression levels of core targets were verified based on a zebrafish model of kidney injury. This study provides a novel strategy for the rapid exploration of the pharmacodynamic material basis of TCM efficacy through a “multi-compounds to multi-targets” standpoint.