Quantitative and Systems Pharmacology 3. Network-Based Identification of New Targets for Natural Products Enables Potential Uses in Aging-Associated Disorders

Abstract

Aging that refers the accumulation of genetic and physiology changes in cells and tissues over a lifetime has been shown a high risk of developing various complex diseases, such as neurodegenerative disease, cardiovascular disease and cancer. Over the past several decades, natural products have been demonstrated as anti-aging interveners via extending lifespan and preventing aging-associated disorders. In this study, we developed an integrated systems pharmacology infrastructure to uncover new indications for aging-associated disorders by natural products. Specifically, we incorporated 411 high-quality aging-associated human genes or human-orthologous genes from mus musculus (MM), saccharomyces cerevisiae (SC), caenorhabditis elegans (CE), and drosophila melanogaster (DM). We constructed a global drug-target network of natural products by integrating both experimental and computationally predicted drug-target interactions (DTI). We further built the statistical network models for identification of new anti-aging indications of natural products through integration of the curated aging-associated genes and drug-target network of natural products. High accuracy was achieved on the network models. We showcased several network-predicted anti-aging indications of four typical natural products (caffeic acid, metformin, myricetin, and resveratrol) with new mechanism-of-actions. In summary, this study offers a powerful systems pharmacology infrastructure to identify natural products for treatment of aging-associated disorders.

Onion Bulb Extract Downregulates EGFR/ERK1/2/AKT Signaling Pathway and Synergizes With Steroids to Inhibit Allergic Inflammation

“…The use of natural products as therapeutic agents has been on the rise, not only due to their demonstrated efficacy (both in humans and in preclinical models of disease) but possibly due to their perceived, and in many instances, real lack of adverse effects, even when consumed in large quantities ( Bohlin et al, 2010 ; Atanasov et al, 2015 ). Based on this, many studies have been conducted over the past decades in an attempt to understand the scientific basis for the use of many natural products, elucidate their actions, and identify their mechanisms of action in animal models of disease ( Fang et al, 2017 ). To this point, several studies have reported that OBE, or its constituents, have many pharmacological actions in many conditions and diseases such as wounds, scars, dysentery, inflammation, hypertension, and also asthma.…”

A Computational Systems Pharmacology Approach to Investigate Molecular Mechanisms of Herbal Formula Tian-Ma-Gou-Teng-Yin for Treatment of Alzheimer’s Disease

“…The combined Global model also outperformed the other two. Comparing to other network prediction models for natural products ( Fang et al, 2017a , b ) which had approximately 750 drug targets in their global models, our global model covered a much wider range of targets, i.e., 1,426 drug targets, which empowered our model a greater potential to predict more diverse and credible targets for natural products with higher accuracy (using AUC value as an evaluation indicator).…”

Network-Based Methods for Prediction of Drug-Target Interactions

“…After performing systematic analysis using the networks and previously published evidence, we found that the three natural products may exert anticancer effects by inhibiting different cancer-associated proteins and pathways. Moreover, the similar workflow was also used to investigate molecular mechanism of anti-aging effects of natural products ( Fang et al, 2017a ).…”