In Silico Modeling and Quantification of Synergistic Effects of Multi-Combination Compounds: Case Study of the Attenuation of Joint Pain Using a Combination of Phytonutrients

Abstract

The quantification of synergistic effects of multi-combination compounds is critical in developing “cocktails” that are efficacious. In this research, a method for in silico modeling and the quantification of synergistic effects of multi-combination compounds is applied for assessing a combination of phytonutrients for joint pain. Joint pain is the most prominent and disabling symptom of arthritis. Arthritic pain leads to a reduced quality of life. This research explores the efficacy of a synergistic combination of two plant-based flavonoids—apigenin and hesperidin—on joint pain. The study employs computational systems biology: (1) to identify biomolecular mechanisms of joint pain; (2) to identify the specific effects of apigenin and hesperidin, individually and in combination, on the mechanisms of joint pain; and (3) to predict the quantitative effects of apigenin and hesperidin, individually and in combination, on joint pain and whether these combination effects are synergistic or additive. Four molecular pathways that are affected by apigenin and hesperidin include the following: (1) arachidonic acid metabolism, (2) PGE2 signaling, (3) COX-2 synthesis, and (4) oxidative stress. The combination of apigenin and hesperidin significantly lowered PGE2 production, CGRP production, TRVP-1 synthesis, COX-2 production, and reactive oxygen species (ROS) production. Our results indicate that the apigenin and hesperidin combination synergistically affected four of the five modalities to attenuate joint pain.

Mechanistic Understanding of D-Glucaric Acid to Support Liver Detoxification Essential to Muscle Health Using a Computational Systems Biology Approach

“…The CytoSolve ® computational systems biology platform was employed in this process. The protocol for setting up and using CytoSolve ® is explained in detailed by Ayyadurai and Deonikar, 2022 [ 31 ], and briefly described in Supplementary File S1 .…”

“…The workflow for the identification, organization, and curation of the literature and the extraction of information from the literature was performed per the standardized CytoSolve ® protocol detailed in previous studies [ 29 , 30 , 31 ]. The specific list of Medical Subject Headings (MeSH) keywords is provided in File S3 in Supplementary Materials Section S3.1 .…”

“…The identification and extraction of data related to reaction rate constants, biochemical reactions, and pharmacokinetic properties of GA with respect to the molecular pathways of liver detoxification were performed per the standardized CytoSolve ® protocol detailed in previous studies [ 29 , 30 , 31 ]. All biochemical reactions for each of the individual liver detoxification mathematical models, along with the kinetic parameters and the initial concentration of biochemical species, are listed in Supplementary File S2 in Tables S2.1–S2.4 .…”

“…Molecular pathways of liver detoxification are converted into individual mathematical models using the biochemical reactions per the standardized CytoSolve ® protocol detailed in previous studies [ 29 , 30 , 31 ]. The individual mathematical models were integrated using the standardized CytoSolve ® protocol detailed in previous studies [ 29 , 30 , 31 ].…”

“…The study herein employs CytoSolve, a proven computational systems biology approach to: (1) identify potential molecular mechanisms involved in liver detoxification affected by GA; and (2) quantitatively predict the effect of GA in aiding liver detoxification. Previous work has demonstrated the viability of using such a computational systems biology approach to model complex biomolecular phenomena [ 23 , 26 , 27 , 28 , 29 , 30 , 31 ].…”