Surface plasmon resonance biosensor combined with lentiviral particle stabilization strategy for rapid and specific screening of P-Glycoprotein ligands.

A novel surface plasmon resonance-based P-gp ligand screening system (SPR-PLSS) combined with lentiviral particle (LVP) stabilization strategy was constructed to screen out potential P-gp inhibitors from natural products. Firstly, we constructed LVPs with high and low expression levels of P-gp. The LVPs can ensure the natural conformation of P-gp based on the principle that LVPs germinated from packaging cells will contain cell membrane fragments and P-gp they carry. Then the LVPs with high P-gp expression for active channel and LVPs with low P-gp expression for reference channel were immobilized on CM5 chip respectively. The affinity detection was thus carried out with the signal reduction on the two channels. The P-gp inhibitors, Valspodar (Val) and cyclosporin (CsA), as positive compounds, were detected to characterize the chip's activity, and the KD of Val and CsA were 14.09 µM and 16.41 µM, respectively. Forty compounds from natural product library were screened using the SPR CM5 chip, and magnolol (Mag), honokiol (Hon), and resveratrol (Res) were screened out as potential P-gp ligands, showing a significant response signal. This work presented a novel P-gp ligand screening system based on LVP-immobilized biosensor to rapidly screen out P-gp ligands from natural product library. Compared with traditional cell experiments which the screening time may take up to several days, our method only takes several hours. Furthermore, this study has also provided solid evidences to support that some complicated membrane proteins would apply to the lentivirus-based SPR screening system.

Surface Plasmon Resonance-Based Membrane Protein-Targeted Active Ingredients Recognition Strategy: Construction and Implementation in Ligand Screening from Herbal Medicines.

Membrane proteins (MPs) are playing important roles in several biological processes. Screening new candidate compounds targeting MPs is important for drug discovery. However, it remains challenging to characterize the interactions between MPs and small-molecule ligands in a label-free method. In this study, a surface plasmon resonance (SPR)-based membrane protein-targeted active ingredients recognition strategy was constructed. This strategy contains two major modules: affinity detection module and ligand screening module. Through the combination of these two functional modules, it is feasible to screen small molecular ligands targeting MPs from herbal medicines. First, we have constructed high/low comparative C-X-C chemokine receptor type 4 (CXCR4)-expressed lentiviral particles (LVPs) models and characterized the expression levels. Then we immobilized LVPs on CM5 chips and detected the affinity between AMD3100 and CXCR4 by using affinity detection module. The KD of AMD3100 was 32.48 ± 3.17 nM. Furthermore, the suitability and robustness of the ligand screening module were validated by using AMD3100 as a positive compound. Subsequently, this module was applied in the screening of CXCR4 small molecular ligands from herbal medicine extracts. Senkyunolide I was screened out from Chuanxiong extract. The affinity constant between senkyunolide I and CXCR4 was 2.94 ± 0.36 µM. The Boyden chamber assay revealed that senkyunolide I could inhibit cell migration process. In conclusion, an SPR-based small molecular ligand recognition strategy combined with virus-based membrane protein stabilization method was constructed. The SPR-based membrane protein-targeted active ingredients recognition strategy will be an effective tool to screen target components from complex systems acting on MPs.

Simulation Strategies for Characterizing Phosphodiesterase-5 Inhibitors in Botanical Dietary Supplements.

A novel "Prediction and Confirmation" (PC) strategy was proposed for characterizing phosphodiesterase-5 inhibitor (PDE-5) derivatives in botanical dietary supplements (BDSs) for on-site detection. Discovery Studio (DS) and density functional theory (DFT) calculations were used for the "Prediction" step in order to estimate PDE-5 derivative structures and theoretical Raman shifts without synthesizing the derivatives. After 11 potentially bioactive sildenafil derivatives were acquired through DS, 32 common calculated Raman shifts were obtained through DFT. The mean absolute wavenumber deviation (δ, peak range) of the major bands and the minimum number (τ) of Raman spectral peaks matching the calculated common shifts were optimized, so that a positive result of an unknown sample could be reasonably produced. In this study, δ was set at ±10 cm-1 and the corresponding τ was set at 4-5 after optimization. Surface plasmon resonance (SPR) biosensor and surface-enhanced Raman scattering (SERS) detection were the "Confirmation" step to validate the reliability and accuracy of DS and DFT in the "Prediction" step, respectively. The optimized δ and τ criteria were used as indexes for on-site SERS detection after thin-layer chromatographic (TLC) separation of six real-world samples, one of which was preliminarily identified as "suspected positive samples." This strategy allows for a quick determination of the BDSs adulterated with sildenafil or its derivatives, independent of any standard materials.

Biosensor-Based Active Ingredients Recognition System for Screening STAT3 Ligands from Medical Herbs.

A surface plasmon resonance (SPR) biosensor-based active ingredients recognition system (SPR-AIRS) was developed, validated, and applied to screen signal transducer and activator of transcription 3 (STAT3) ligands. First, features of the screening system were investigated in four aspects: (1) specificity of the STAT3-immobilized chip, it shows that the chip could be applied to screen STAT3 ligands from complex mixture; (2) linearity and limit of detection (LOD) of the system, the minimum recovery cycle number was determined as 5 cycles; (3) saturability of the chip, the results indicate that it is necessary to select a proper concentration based on the compound's Kd value; (4) robustness of the system, it indicates that inactive compounds in the matrix could not interfere with active compounds in the process of screening. Next, SPR-AIRS was applied to screen STAT3 ligands from medicinal herbs. Nine candidate compounds were fished out. Then SPR assay and molecular docking were performed to verify the interplay between STAT3 and candidate compounds. Apoptosis assay and luciferase report assay were performed to investigate the drug effect of candidate compounds on STAT3 activity. Western blot results indicated that neobaicalein and polydatin could inhibit the phosphorylation of STAT3. As far as we know, this is the first time that neobaicalein and polydatin are reported as effective STAT3 ligands. In a conclusion, we have systemically demonstrated the feasibility of SPR biosensor-based screening method applying to complex drug systems, and our findings suggest that SPR-AIRS could be a sensitive and effective solution for the discovery of active compounds from a complex matrix.

Target Identification of Kinase Inhibitor Alisertib (MLN8237) by Using DNA-Programmed Affinity Labeling.

Accurate identification of the molecular targets of bioactive small molecules is a highly important yet challenging task in biomedical research. Previously, a method named DPAL (DNA-programmed affinity labeling) for labeling and identifying the cellular targets of small molecules and nucleic acids was developed. Herein, DPAL is applied for the target identification of Alisertib (MLN8237), which is a highly specific aurora kinase A (AKA) inhibitor and a drug candidate being tested in clinical trials for cancer treatment. Apart from the well-established target of AKA, several potential new targets of MLN8237 were identified. Among them, p38 mitogen-activated protein kinase (p38) and laminin receptor (LAMR) were validated to be implicated in the anticancer activities of MLN8237. Interestingly, these new targets were not identified with non-DNA-based affinity probes. This work may facilitate an understanding of the molecular basis of the efficacy and side effects of MLN8237 as a clinical drug candidate. On the other hand, this work has also demonstrated that the method of DPAL could be a useful tool for target identification of bioactive small molecules.

Dynamic metabolic and transcriptomic profiling of methyl jasmonate-treated hairy roots reveals synthetic characters and regulators of lignan biosynthesis in Isatis indigotica Fort.

A molecular description of lignan biosynthesis in Isatis indigotica displaying its synthetic characteristics and regulatory mechanism is of great importance for the improvement of the production of this class of active compounds. To discover the potential key catalytic steps and regulatory genes, I. indigotica hairy roots elicited by methyl jasmonate (MeJA) were used as a source of systematic variation for exploring the metabolic/transcriptional changes and candidate genes that might play key roles in lignan biosynthesis. The reprogramming modulated by MeJA was classified into three distinct phases, referred to as signal responding, transcriptional activation of metabolic pathways and accumulation of metabolites. Candidate genes were pooled according to the three phases and applied to co-expression network analysis. In total, 17 genes were identified as hub genes. 4CL3 was selected to validate its impact on lignan biosynthesis. RNAi of 4CL3 resulted in a significant reduction in lignan production. Taken together with its catalytic property, a major route of lignan biosynthesis in I. indigotica was highlighted, which was catalysed by 4CL3 via the esterization of caffeic acid. In conclusion, this study provides new insights into lignan biosynthesis as well as potential targets for metabolic engineering in I. indigotica.

Identification of a ligand for tumor necrosis factor receptor from Chinese herbs by combination of surface plasmon resonance biosensor and UPLC-MS.

Identification of bioactive compounds directly from complex herbal extracts is a key issue in the study of Chinese herbs. The present study describes the establishment and application of a sensitive, efficient, and convenient method based on surface plasmon resonance (SPR) biosensors for screening active ingredients targeting tumor necrosis factor receptor type 1 (TNF-R1) from Chinese herbs. Concentration-adjusted herbal extracts were subjected to SPR binding assay, and a remarkable response signal was observed in Rheum officinale extract. Then, the TNF-R1-bound ingredients were recovered, enriched, and analyzed by UPLC-QTOF/MS. As a result, physcion-8-O-ß-D-monoglucoside (PMG) was identified as a bioactive compound, and the affinity constant of PMG to TNF-R1 was determined by SPR affinity analysis (K D = 376 nM). Pharmacological assays revealed that PMG inhibited TNF-α-induced cytotoxicity and apoptosis in L929 cells via TNF-R1. Although PMG was a trace component in the chemical constituents of the R. officinale extract, it had considerable anti-inflammatory activities. It was found for the first time that PMG was a ligand for TNF receptor from herbal medicines. The proposed SPR-based screening method may prove to be an effective solution to analyzing bioactive components of Chinese herbs and other complex drug systems. Graphical abstract Scheme of the method based on SPR biosensor for screening and recovering active ingredients from complex herbal extracts and UPLC-MS for identifying them. Scheme of the method based on SPR biosensor for screening and recovering active ingredients from complex herbal extracts and UPLC-MS for identifying them.

Activity ranking of synthetic analogs targeting vascular endothelial growth factor receptor 2 by an integrated cell membrane chromatography system.

Evaluating the biological activities of small molecules represents an important part of the drug discovery process. Cell membrane chromatography (CMC) is a well-developed biological chromatographic technique. In this study, we have developed combined SMMC-7721/CMC and HepG2/CMC with high-performance liquid chromatography and time-of-flight mass spectrometry to establish an integrated screening platform. These systems was subsequently validated and used for evaluating the activity of quinazoline compounds, which were designed and synthesized to target vascular endothelial growth factor receptor 2. The inhibitory activities of these compounds towards this receptor were also tested using a classical caliper mobility shift assay. The results revealed a significant correlation between these two methods (R(2) = 0.9565 or 0.9420) for evaluating the activities of these compounds. Compared with traditional methods of evaluating the activities analogous compounds, this integrated cell membrane chromatography screening system took less time and was more cost effective, indicating that it could be used as a practical method in drug discovery.

Magnolol as STAT3 inhibitor for treating multiple sclerosis by restricting Th17 cells.

OBJECTIVE: Multiple sclerosis (MS) is an immune disease in the central nervous system (CNS) associated with Th17 cells. Moreover, STAT3 initiates Th17 cell differentiation and IL-17A expression through facilitating RORγt in MS. Here, we reported that magnolol, isolated from Magnolia officinalis Rehd. Et Wils, was regarded as a candidate for MS treatment verified by both in vitro and in vivo studies. METHODS: In vivo, experimental autoimmune encephalomyelitis (EAE) model in mice was employed to evaluate the alleviation of magnolol on myeloencephalitis. In vitro, FACS assay was employed to evaluate the effect of magnolol on Th17 and Treg cell differentiation and IL-17A expression; network pharmacology-based study was applied to probe the involved mechanisms; western blotting, immunocytochemistry, and luciferase reporter assay was used to further confirm the regulation of magnolol on JAK/STATs signaling pathway; surface plasmon resonance (SPR) assay and molecular docking were applied to manifest affinity with STAT3 and binding sites; overexpression of STAT3 was employed to verify whether magnolol attenuates IL-17A through STAT3 signaling pathway. RESULTS: In vivo, magnolol alleviated loss of body weight and severity of EAE mice; magnolol improved lesions in spinal cords and attenuated CD45 infiltration, and serum cytokines levels; correspondingly, magnolol focused on inhibiting Th17 differentiation and IL-17A expression in splenocyte of EAE mice; moreover, magnolol selectively inhibited p-STAT3(Y705) and p-STAT4(Y693) of both CD4+ and CD8+ T cells in splenocyte of EAE mice. In vitro, magnolol selectively inhibited Th17 differentiation and IL-17A expression without impact on Treg cells; network pharmacology-based study revealed that magnolol perhaps diminished Th17 cell differentiation through regulating STAT family members; western blotting further confirmed that magnolol inhibited p-JAK2(Y1007) and selectively antagonized p-STAT3(Y705) and slightly decreased p-STAT4(Y693); magnolol antagonized both STAT3 nucleus location and transcription activity; magnolol had a high affinity with STAT3 and the specific binding site perhaps to be at SH2 domain; overexpression of STAT3 resulted in failed inhibition of magnolol on IL-17A. CONCLUSION: Magnolol selectively inhibited Th17 differentiation and cytokine expression through selectively blocking of STAT3 resulting in decreased the ratio of Th17/Treg cells for treating MS, suggesting that the potential of magnolol for treating MS as novel STAT3 inhibitor.

Selection of DNA-encoded chemical libraries against endogenous membrane proteins on live cells.

Membrane proteins on the cell surface perform a myriad of biological functions; however, ligand discovery for membrane proteins is highly challenging, because a natural cellular environment is often necessary to maintain protein structure and function. DNA-encoded chemical libraries (DELs) have emerged as a powerful technology for ligand discovery, but they are mainly limited to purified proteins. Here we report a method that can specifically label membrane proteins with a DNA tag, and thereby enable target-specific DEL selections against endogenous membrane proteins on live cells without overexpression or any other genetic manipulation. We demonstrate the generality and performance of this method by screening a 30.42-million-compound DEL against the folate receptor, carbonic anhydrase 12 and the epidermal growth factor receptor on live cells, and identify and validate a series of novel ligands for these targets. Given the high therapeutic significance of membrane proteins and their intractability to traditional high-throughput screening approaches, this method has the potential to facilitate membrane-protein-based drug discovery by harnessing the power of DEL.

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

Screening of bioactive ligands for a certain protein target from medicinal herbs is a highly important yet challenging task during drug discovery process. In this study, a surface plasmon resonance biosensor-based active ingredient recognition system (SPR-AIRS) was applied to screen p38 mitogen-activated protein kinase (p38) ligands from herbal extracts. After p38 protein was immobilized on a SPR chip and the suitability of SPR-AIRS was validated, thirty-four p38-related medicinal herbs were selected and pre-screened. Two medicinal herbs having high response signal with p38-immobilized chip, Folium Ginkgo and Herba Artemisiae Scopariae, were injected into SPR system for ligand fishing. Among them, two active compounds, eupatilin (EPT) and ginkgolide B (GKB), were identified as p38 ligands, and then the KD values of EPT and GKB were measured as 21.68 ± 2.21 and 44.71 ± 1.80 µM, respectively. They can inhibit p38 activities significantly and bind to the ATP binding site on p38. Furthermore, EPT and GKB can inhibit cell proliferation (IC50 = 30.31 ± 6.84 and 42.97 ± 0.83 µM), induce apoptosis and G2/M cell cycle arrest against K562 cell line. This is the first time that EPT and GKB are reported as effective p38 binding ligands. These results prove that SPR-AIRS could be an effective method to screen active compounds acting on a specific protein from complex systems.

A method for screening active components from Chinese herbs by cell membrane chromatography-offline-high performance liquid chromatography/mass spectrometry and an online statistical tool for data processing.

Cell membrane chromatography (CMC) has been successfully applied to screen bioactive compounds from Chinese herbs for many years, and some offline and online two-dimensional (2D) CMC-high performance liquid chromatography (HPLC) hyphenated systems have been established to perform screening assays. However, the requirement of sample preparation steps for the second-dimensional analysis in offline systems and the need for an interface device and technical expertise in the online system limit their extensive use. In the present study, an offline 2D CMC-HPLC analysis combined with the XCMS (various forms of chromatography coupled to mass spectrometry) Online statistical tool for data processing was established. First, our previously reported online 2D screening system was used to analyze three Chinese herbs that were reported to have potential anti-inflammatory effects, and two binding components were identified. By contrast, the proposed offline 2D screening method with XCMS Online analysis was applied, and three more ingredients were discovered in addition to the two compounds revealed by the online system. Then, cross-validation of the three compounds was performed, and they were confirmed to be included in the online data as well, but were not identified there because of their low concentrations and lack of credible statistical approaches. Last, pharmacological experiments showed that these five ingredients could inhibit IL-6 release and IL-6 gene expression on LPS-induced RAW cells in a dose-dependent manner. Compared with previous 2D CMC screening systems, this newly developed offline 2D method needs no sample preparation steps for the second-dimensional analysis, and it is sensitive, efficient, and convenient. It will be applicable in identifying active components from Chinese herbs and practical in discovery of lead compounds derived from herbs.

Network pharmacology-based strategy for predicting active ingredients and potential targets of Yangxinshi tablet for treating heart failure.

ETHNOPHARMACOLOGICAL RELEVANCE: Yangxinshi tablet (YXST) is an effective treatment for heart failure and myocardial infarction; it consists of 13 herbal medicines formulated according to traditional Chinese Medicine (TCM) practices. It has been used for the treatment of cardiovascular disease for many years in China. MATERIALS AND METHODS: In this study, a network pharmacology-based strategy was used to elucidate the mechanism of action of YXST for the treatment of heart failure. Cardiovascular disease-related protein target and compound databases were constructed for YXST. A molecular docking platform was used to predict the protein targets of YXST. The affinity between proteins and ingredients was determined using surface plasmon resonance (SPR) assays. The action modes between targets and representative ingredients were calculated using Glide docking, and the related pathways were predicted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. RESULTS: A protein target database containing 924 proteins was constructed; 179 compounds in YXST were identified, and 48 compounds with high relevance to the proteins were defined as representative ingredients. Thirty-four protein targets of the 48 representative ingredients were analyzed and classified into two categories: immune and cardiovascular systems. The SPR assay and molecular docking partly validated the interplay between protein targets and representative ingredients. Moreover, 28 pathways related to heart failure were identified, which provided directions for further research on YXST. CONCLUSIONS: This study demonstrated that the cardiovascular protective effect of YXST mainly involved the immune and cardiovascular systems. Through the research strategy based on network pharmacology, we analysis the complex system of YXST and found 48 representative compounds, 34 proteins and 28 related pathways of YXST, which could help us understand the underlying mechanism of YSXT's anti-heart failure effect. The network-based investigation could help researchers simplify the complex system of YXSY. It may also offer a feasible approach to decipher the chemical and pharmacological bases of other TCM formulas.

The Active Components of Fuzheng Huayu Formula and Their Potential Mechanism of Action in Inhibiting the Hepatic Stellate Cells Viability - A Network Pharmacology and Transcriptomics Approach.

Purpose: This study aimed to identify the active components of Fuzheng Huayu (FZHY) formula and the mechanism by which they inhibit the viability of hepatic stellate cells (HSCs) by a combination of network pharmacology and transcriptomics. Methods: The active components of FZHY formula were screened out by text mining. Similarity match and molecular docking were used to predict the target proteins of these compounds. We then searched the STRING database to analyze the key enriched processes, pathways and related diseases of these target proteins. The relevant networks were constructed by Cytoscape. A network analysis method was established by integrating data from above network pharmacology with known transcriptomics analysis of quiescent HSCs-activated HSCs to identify the most possible targets of the active components in FZHY formula. A cell-based assay (LX-2 and T6 cells) and surface plasmon resonance (SPR) analysis were used to validate the most possible active component-target protein interactions (CTPIs). Results: 40 active ingredients in FZHY formula and their 79 potential target proteins were identified by network pharmacology approach. Further network analysis reduced the 79 potential target proteins to 31, which were considered more likely to be the target proteins of the active components in FZHY formula. In addition, further enrichment analysis of 31 target proteins indicated that the HIF-1, PI3K-Akt, FoxO, and chemokine signaling pathways may be the primary pathways regulated by FZHY formula in inhibiting the HSCs viability for the treatment of liver fibrosis. Of the 31 target proteins, peroxisome proliferator activator receptor gamma (PPARG) was selected for validation by experiments at the cellular and molecular level. The results demonstrated that schisandrin B, salvianolic acid A and kaempferol could directly bind to PPARG, decreasing the viability of HSCs (T6 cells and LX-2 cells) and exerting anti-fibrosis effects. Conclusion: The active ingredients of FZHY formula were successfully identified and the mechanisms by which they inhibit HSC viability determined, using network pharmacology and transcriptomics. This work is expected to benefit the clinical application of this formula.

Identification of Annexin A2 as a target protein for plant alkaloid matrine.

Matrine is a plant alkaloid and a major active component in the Chinese medical herb Sophora flavescens. Matrine has shown potent anti-cancer activities but its molecular target(s) and mechanism are still unknown. Using the photo-affinity labeling approach, for the first time, Annexin A2 was identified as a direct-binding target of matrine in cancer cells.

A novel strategy of profiling the mechanism of herbal medicines by combining network pharmacology with plasma concentration determination and affinity constant measurement.

Herbal medicines have long been widely used in the treatment of various complex diseases in China. However, the active constituents and therapeutic mechanisms of many herbal medicines remain undefined. Therefore, the identification of the active components and target proteins in these herbal medicines is a formidable task in herbal medicine research. In this study, we proposed a strategy, which integrates network pharmacology with biomedical analysis and surface plasmon resonance (SPR) to predict the active ingredients and potential targets of herbal medicine Sophora flavescens or Kushen in Chinese, and evaluate its anti-fibrosis activity. First, we applied a virtual HTDocking platform to predict the potential targets of Kushen related to liver fibrosis by selecting five crucial protein targets based on network parameters and text mining. Then, we identified nine components in mice plasma after oral administration of Kushen extract and determined the plasma concentration of each compound. Binding affinities between the nine potential active compounds and five target proteins were detected by SPR assays. Finally, we constructed a multi-parameter network model on the basis of three important parameters to tentatively explain the anti-fibrosis mechanism of Kushen. The results not only provide evidence for the therapeutic mechanism of Kushen but also shed new light on the activity-based analysis of other Chinese herbal medicines.