Large-Scale Target Identification of Herbal Medicine Using a Reverse Docking Approach

Abstract

Herbal medicine has been used to countermine various diseases for centuries. However, most of the therapeutic targets underlying herbal therapy remain unclear, which largely slow down the novel drug discovery process from natural products. In this study, we developed a novel computational pipeline for assisting de novo identification of protein targets for herbal ingredients. The pipeline involves pharmacophore comparison and reverse ligand–protein docking simulation in a high throughput manner. We evaluated the pipeline using three traditional Chinese medicine ingredients such as acteoside, quercetin, and epigallocatechin gallate as examples. A majority of current known targets of these ingredients were successfully identified by the pipeline. Structural comparative analyses confirmed that the predicted ligand–target interactions used the same binding pockets and binding modes as those of known ligand–target interactions. Furthermore, we illustrated the mechanism of actions of the ingredients by constructing the pharmacological networks on the basis of the predicted target profiles. In summary, we proposed an efficient and economic option for large-scale target exploration in the herb study. This pipeline will be particularly valuable in aiding precise drug discovery and drug repurposing from natural products.

New Tricks for Old Guys: Recent Developments in the Chemistry, Biochemistry, Applications and Exploitation of Selected Species from the Lamiaceae Family

“…Coridothymus capitatus and Thymbra capitata) is the main wild species belonging to this genus. Also in this case the ethyl acetate and ethanol extracts of several samples collected in the Sicilian territory showed the presence of several polyphenols: caffeic (1) and rosmarinic (4) acids were the main organic acids, all others components were flavonoid derivatives: vicenin-2 (34), luteolin rutinoside (52) (25), thymusin (61), naringenin (9), cirsilineol (13), and chrysoeriol (62). [145] Figure 8 shows the molecular formulas of the currently known Lamiaceae components, whereas Figure 9 reports some typical HPLC profiles of the extracts of some Lamiaceae.…”

“…Carnosic acid, together with carnosol (43) and rosmanol (44), are diterpenoids belonging to the metabolic pool of rosemary, responsible for most of its biological activities. In a recent survey of Sicilian R. officinalis, the ethyl acetate and ethanol extracts showed the presence of several polyphenols subdivided in organic (14), genkwanin (25), salvigenin (33), and diterpenes: carnosol (43), carnosic acid (49) and methyl carnosoate (50). Rosmarinic and carnosic acids were largely the main components contributing to the antioxidant properties of the extracts.…”

“…[56] O. vulgare is one of the main species of this genus and then the most studied, however, other minor species show interesting chemical composition associated with biological activities, for example a study of the chemical characterization and the evaluation of antimicrobial, enzyme inhibitory, and antioxidant activities of methanol and water extracts of Turkish O. onites has been recently reported. [424] In total 28 components belonging to polyphenols, flavonoids, terpenoids, organic acids and esters have been identified: 3-O-(4-coumaroyl)quinic acid (16), acacetin (17), cirsimaritin (14), naringenin (9), tuberonic acid glucoside (18), ferulic acid (3), apigenin-7,4'-dimethyl ether (19), azelaic acid (20), baicalin (21), casticin (22), cirsiliol (11), dihydrorobinetin (23), gardenin B (24), genkwanin (25), isoferulic acid (26), kaempferol (27), nevadensin (28), oroxylin A 7-O-glucuronide (29), quercetin (30), rosmarinic acid methyl ester (31), sakuranetin (32) and salvigenin (33).…”

“…As previously mentioned, this approach is applied also to natural products and plant extracts, [19,20] and recently it has been supported by several tools such as the Connectivity Map (CMap), the Library Integrated Network based Cellular Signatures (LINCS), the Ge-nome Wide Association Studies (GWAS), the Side Effect Resource (SIDER), and the Directionality Map (DMAP), which have significantly reinforced the drug repurposing applications. [21][22][23][24][25] These recent studies besides to be applied to fight the main pathologies previously described appear particularly promising in the research of therapeutic tools against the so-called rare or orphan diseases, which are often chronic and progressive without an appropriate drug equipment as well as focused pharmaceutical studies.…”

Identification of the Molecular Mechanisms of Peimine in the Treatment of Cough Using Computational Target Fishing

“…The information of binding targets will help to understand the mechanisms of drug action, improve the clinical application, explain off-target effects, and allow for better analog design [17]. Compared to the traditional experimental approaches, which are labor-, resource-and time-intensive, computer-aided drug discovery becomes more efficient and economic, being an attractive complementary method in drug development [18,19]. Therefore, computational approaches have the potential to assist in the unraveling of the mechanisms of peimine-mediated cough relief.…”