Identification of eupatilin and ginkgolide B as p38 ligands from medicinal herbs by surface plasmon resonance biosensor-based active ingredients recognition system

A dual-target SPR screening system for simultaneous ligand discovery of SARS-CoV-2 spike protein and its receptor ACE2 from Chinese herbs

Traditional Chinese Medicine (TCM) is a supremely valuable resource for the development of drug discovery. Few methods are capable of hunting for potential molecule ligands from TCM towards more than one single protein target. In this study, a novel dual-target surface plasmon resonance (SPR) biosensor was developed to perform targeted compound screening of two key proteins involved in the cellular invasion process of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): the spike (S) protein receptor binding domain (RBD) and the angiotensin-converting enzyme 2 (ACE2). The screening and identification of active compounds from six Chinese herbs were conducted taking into consideration the multi-component and multi-target nature of Traditional Chinese Medicine (TCM). Puerarin from Radix Puerariae Lobatae was discovered to exhibit specific binding affinity to both S protein RBD and ACE2. The results highlight the efficiency of the dual-target SPR system in drug screening and provide a novel approach for exploring the targeted mechanisms of active components from Chinese herbs for disease treatment.

A strategy of screening and binding analysis of bioactive components from traditional Chinese medicine based on surface plasmon resonance biosensor

Elucidating the active components of traditional Chinese medicine (TCM) is essential for understanding the mechanisms of TCM and promote its rational use as well as TCM-derived drug development. Recent studies have shown that surface plasmon resonance (SPR) technology is promising in this field. In the present study, we propose an SPR-based integrated strategy to screen and analyze the major active components of TCM. We used Radix Paeoniae Alba (RPA) as an example to identify the compounds that can account for its anti-inflammatory mechanism via tumor necrosis factor receptor type 1 (TNF-R1). First, RPA extraction was analyzed using an SPR-based screening system, and the potential active ingredients were collected, enriched, and identified as paeoniflorin and paeonol. Next, the affinity constants of paeoniflorin and paeonol were determined as 4.9 and 11.8 μM, respectively. Then, SPR-based competition assays and molecular docking were performed to show that the two compounds could compete with tumor necrosis factor-α (TNF-α) while binding to the subdomain 1 site of TNF-R1. Finally, in biological assays, the two compounds suppressed cytotoxicity and apoptosis induced by TNF-α in the L929 cell line. These findings prove that SPR technology is a useful tool for determining the active ingredients of TCM at the molecular level and can be used in various aspects of drug development. The SPR-based integrated strategy is reliable and feasible in TCM studies and will shed light on the elucidation of the pharmacological mechanism of TCM and facilitate its modernization.

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A surface plasmon resonance-based integrated strategy was established to analyze traditional Chinese medicine.

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Surface plasmon resonance technology can be used for ligand screening, affinity detection, and binding site confirmation.

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Paeoniflorin and paeonol were identified as TNF-R1-bound ingredients in RPA.

Mechanism of Paeoniae Radix Alba in the Treatment of Non-alcoholic Fatty Liver Disease Based on Sequential Metabolites Identification Approach, Network Pharmacology, and Binding Affinity Measurement

Screening functional food ingredients (FFI) from medicinal and edible plants (MEP) has still remained a great challenge due to the complexity of MEP and its obscure function mechanisms. Herein, an integrated strategy based on sequential metabolites identification approach, network pharmacology, molecular docking, and surface plasmon resonance (SPR) analysis was proposed for quickly identifying the active constituents in MEP. First, the sequential biotransformation process of MEP, including intestinal absorption and metabolism, and hepatic metabolism, was investigated by oral gavage, and intestinal perfusion with venous sampling method. Then the blood samples were analyzed by UPLC-Q Exactive Orbitrap HRMS. Second, the network pharmacology approach was used to explore the potential targets and possible mechanisms of the in vivo metabolites of MEP. Third, molecular docking and SPR approaches were used to verify the specific interactions between protein targets and representative ingredients. The proposed integrated strategy was successfully used to explore the heptoprotective components and the underlying molecular mechanism of Paeoniae Radix Alba (PRA). A total of 44 compounds were identified in blood samples, including 17 porotypes and 27 metabolites. The associated metabolic pathways were oxidation, methylation, sulfation, and glucuronidation. After further screening, 31 bioactive candidates and 377 related targets were obtained. In addition, the bioactive components contained in PRA may have therapeutic potentials for non-alcoholic fatty liver disease (NAFLD). The above results demonstrated the proposed strategy may provide a feasible tool for screening FFI and elaborating the complex function mechanisms of MEP.

Identification of α-glucosidase inhibitors from the bran of Chenopodium quinoa Willd. by surface plasmon resonance coupled with ultra-performance liquid chromatography and quadrupole-time-of-flight-mass spectrometry

Extracts from the bran of Chenopodium quinoa Willd. (QBE) were reported to be active in inhibiting α-glycosidase, a promising target for treatment of diabetes mellitus. However, the constituents responsible for the α-glucosidase-inhibiting activity of QBE have not been fully characterized. The present study aimed to set up a method for rapid identification of glycosidase inhibiting compounds from the quinoa bran. With surface plasmon resonance (SPR) coupled with liquid chromatography-mass spectrometry (LC-MS), we identified eight flavonoids and ten triterpenoid saponins that may bind to the α-glycosidase. Analysis of the interaction kinetics by molecular docking supported their α-glucosidase-inhibiting activity and revealed the potential mechanisms for the inhibitory effects. In summary, this study established a SPR and LC-MS-based method for rapid in vitro screening of α-glucosidase inhibitors and suggested the quinoa bran a potential natural source of α-glucosidase inhibitors.

Integrated Systems Pharmacology and Surface Plasmon Resonance Approaches to Reveal the Synergistic Effect of Multiple Components of Gu-Ben-Ke-Chuan Decoction on Chronic Bronchitis

Introduction

Gu-Ben-Ke-Chuan (GBKC) decoction, a well-known prescription composed of seven herbs, has been widely used for treating chronic bronchitis (CB). However, the pharmacological constituents of GBKC and the underlying mechanisms by which these components act on CB remain unclear.

Methods

Ultra-high-pressure liquid chromatography coupled with linear ion trap–Orbitrap tandem mass spectrometry (UHPLC-LTQ-Orbitrap) was first employed to rapidly identify compounds from GBKC. Thereafter, network pharmacology and molecular docking analyses were performed to identify the potential active constituents, candidate targets, and major pathways. Finally, the affinities between the key compounds and targets were verified via surface plasmon resonance (SPR) analysis. In addition, the anti-inflammatory effect of GBKC was verified using an LPS-induced inflammatory cell model based on the predicted results.

Results

A total of 53 major compounds were identified in the GBKC decoction. After network pharmacology-based virtual screening, 141 major targets and 39 main compounds were identified to be effective in the treatment of CB. The major targets were highly enriched in the tumor necrosis factor (TNF) signaling pathway, suggesting that GBKC could attenuate the inflammatory response in patients with CB. Furthermore, molecular docking results indicated that 20 pairs of components and target proteins relevant to the TNF pathway exhibited notable interactions. Among them, eight compound-target pairs exhibited good affinity as per SPR analysis. In addition, the production of interleukin 6 and TNF-α in LPS-induced MH-S cells was suppressed after GBKC treatment.

Conclusion

This study successfully clarified the mechanism of action of GBKC against CB, which demonstrated that the integrated strategy described above is reliable for identifying the active compounds and mechanisms responsible for the pharmacological activities of GBKC decoction.

Biocompatible chitosan-zinc oxide nanocomposite based dispersive micro-solid phase extraction coupled with HPLC-UV for the determination of rosmarinic acid in the extracts of medical plants and water sample

In the present research, a procedure was described for the recovery of rosmarinic acid (RA) from medical extract samples using chitosan‑zinc oxide nanoparticles as a biocompatible nanocomposite (CS-ZnO-NC). The dispersive micro-solid phase extraction (D-μ-SPE) of RA from the medical extract samples was investigated by using the prepared biocompatible composite as a solid phase. The HPLC-UV method was used for measuring the extracted RA. The important variables (pH, biocompatible composite mass, contact time, and volume of eluent) associated with the extraction process were analyzed by the application of central composite design (CCD). The achieved optimum values for the mentioned variables were 7.0, 10 mg, 4 min, and 180 μL, respectively. The extraction recovery (99.68%) obtained from the predicted model was in agreement with the experimental data (98.22 ± 1.33%). In addition, under the obtained optimum conditions and over the concentration in the range of 2-3500 ng mL-1, a linear calibration curve was obtained with R2 > 0.993. The limit of detection (LOD) and quantification (LOQ) values were computed, and the obtained ranges were respectively from 0.060 to 0.089 ng mL-1 and 0.201 to 0.297 ng mL-1. In addition, the enrichment factors were obtained in the range of 93.7-110.5 with preconcentration factor of 83.3. Therefore, the D-μ-SPE-HPLC-UV method could be used for analyzing RA in the samples of the extracts obtained from the medical plants and water with the recovery values of the analyte in the range of 96.6%-105.4% and the precision with relative standard deviation <5.7%.