Chemogenomics Approaches to Rationalizing the Mode-of-Action of Traditional Chinese and Ayurvedic Medicines

Abstract

Traditional Chinese medicine (TCM) and Ayurveda have been used in humans for thousands of years. While the link to a particular indication has been established in man, the mode-of-action (MOA) of the formulations often remains unknown. In this study, we aim to understand the MOA of formulations used in traditional medicine using an in silico target prediction algorithm, which aims to predict protein targets (and hence MOAs), given the chemical structure of a compound. Following this approach we were able to establish several links between suggested MOAs and experimental evidence. In particular, compounds from the 'tonifying and replenishing medicinal' class from TCM exhibit a hypoglycemic effect which can be related to activity of the ingredients against the Sodium-Glucose Transporters (SGLT) 1 and 2 as well as Protein Tyrosine Phosphatase (PTP). Similar results were obtained for Ayurvedic anticancer drugs. Here, both primary anticancer targets (those directly involved in cancer pathogenesis) such as steroid-5-alpha-reductase 1 and 2 were predicted as well as targets which act synergistically with the primary target, such as the efflux pump P-glycoprotein (P-gp). In addition, we were able to elucidate some targets which may point us to novel MOAs as well as explain side effects. Most notably, GPBAR1, which was predicted as a target for both 'tonifying and replenishing medicinal' and anticancer classes, suggests an influence of the compounds on metabolism. Understanding the MOA of these compounds is beneficial as it provides a resource for NMEs with possibly higher efficacy in the clinic than those identified by single-target biochemical assays.

Aqueous Ethanolic Extract of Tinospora cordifolia as a Potential Candidate for Differentiation Based Therapy of Glioblastomas

“…In Ayurveda, various medicinal plants have been reported to possess anticancer properties but their mode of action is largely unknown. Using phenotypic information of anticancer compounds used in Ayurveda, Fauzi et al (2012) predicted ten most enriched targets through in silico target prediction method that include primary targets involved in cancer progression such as PTP1B and T-cell Protein Tyrosine Phosphatase (TC-TCP) and synergistic targets such as efflux pumps, P-glycoprotein, opening new avenues for Ayurvedic drug research [57]. Tinospora cordifolia is an important component of various ayurvedic decoction used to treat diseases of nervous system and other vital organs like liver, pancreas and kidney.…”

Novel Synthetic Biscoumarins Target Tumor Necrosis Factor-α in Hepatocellular Carcinoma in Vitro and in Vivo

“…For this purpose, we employed in silico target prediction algorithms, which are trained on known bioactivity data and which have been successfully applied in different situations before (44,45). We employed a Laplacian-modified Naïve Bayes classifier as published previously (46).…”

Memory‐Enhancing Effects of the Crude Extract of Polygala tenuifolia on Aged Mice

“…Potential mechanisms which make EPT an effective agent for treating learning and memory disorders might be partially related to improved antioxidation and reduced activities of AChE and MAO. By combining analytical chemistry and chemogenomics [35] in the future, we aim to identify the memory-enhancing phytochemicals within EPT and elucidate their molecular mechanisms.…”