Finding New Molecular Targets of Familiar Natural Products Using In Silico Target Prediction

Abstract

Natural products comprise a rich reservoir for innovative drug leads and are a constant source of bioactive compounds. To find pharmacological targets for new or already known natural products using modern computer-aided methods is a current endeavor in drug discovery. Nature’s treasures, however, could be used more effectively. Yet, reliable pipelines for the large-scale target prediction of natural products are still rare. We developed an in silico workflow consisting of four independent, stand-alone target prediction tools and evaluated its performance on dihydrochalcones (DHCs)—a well-known class of natural products. Thereby, we revealed four previously unreported protein targets for DHCs, namely 5-lipoxygenase, cyclooxygenase-1, 17β-hydroxysteroid dehydrogenase 3, and aldo-keto reductase 1C3. Moreover, we provide a thorough strategy on how to perform computational target predictions and guidance on using the respective tools.

E Se tea alleviates acetaminophen-induced liver injury by activating the Nrf2 signaling pathway

“…9,10 Dihydrochalcones are important natural products, which exhibit antioxidant, anti-inflammatory, antibacterial, antidiabetic, anticancer, and cardioprotective activities. 11,12 They are mainly present in the edible species of Lithocarpus, Rubus, Malus, and Averrhoa. Among dihydrochalcones, phloretin and phlorizin can protect the liver by activating the Keap1-Nrf2 signaling pathway.…”

In-Silico Drug Toxicity and Interaction Prediction for Plant Complexes Based on Virtual Screening and Text Mining

“…For the first time, a workflow ( Figure 1 ) for both toxicity and drug interaction prediction of herbal medicine based on virtual screening and text mining [ 45 , 46 ] was constructed. For studies on drug toxicity, drug-drug interactions, and drug-food interactions, with detailed related information retrieved, this workflow is beneficial for hypothesis construction and insight interpretation.…”

Identification of Potent Bioassay Guided Terpenoid and Glycoside Root Fractions of Astragalus candolleanus against Clinically Significant Bacterial Strains

“…The powdered root extract along with different solvent systems was allowed to stand for 48 hours. After filtration, chemical tests allow the qualitative analysis of the extract [ 18 , 28 ]. The presence of several chemical classes of compounds, such as alkaloids, glycosides, terpenoids, flavonoids, saponins, carbohydrates, lipids, volatile oils, steroids, phenols, tannins, gums, and mucilage, was determined.…”

“…The isolated compounds were subjected to Swiss Target Prediction (STP) ( https://www.swisstargetprediction.ch/ ) [ 28 ] and Prediction of Activity Spectra for Substances (PASS) online bioactivity score software ( https://www.way2drug.com/ ) [ 29 – 31 ] to understand the probable targets of these compounds.…”