Ligand-target Interactions Research Articles

Clitoria ternatea L. (Butterfly Pea) Flower Against Endometrial Pain: Integrating Preliminary In Vivo and In Vitro Experimentations Supported by Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation Studies.

Clitoria ternatea L. (CT) is a perennial herbaceous plant with deep blue flowers native to tropical Asia. This work explores the endometrial pain (EP) regulation of CT flower through a multifaceted approach. Phytochemical screening unveiled the presence of alkaloids, steroids, flavonoids, glycosides, and tannins in CT flower methanolic extract (ME). In the in vitro membrane stabilizing experiment, the ME demonstrated 91.47% suppression of heat-induced hemolysis. Upon carrageenan-induced paw edema assay conducted on male Swiss albino mice at doses of 200 mg/kg and 400 mg/kg, 65.28% and 81.89% inhibition rates, respectively, of paw edema were reported. For the same doses, upon acetic acid-induced-writhing assay, 75.6% and 76.78% inhibition rates, respectively, were observed. For network pharmacology analyses, a protein-protein interaction network was constructed for 92 overlapping gene targets of CT and EP, followed by GO and KEGG pathway enrichment analyses. Network pharmacology-based investigation identified the anti-EP activity of CT to be mostly regulated by the proteins SRC homology, ESR1, and PI3KR1. Physicochemical, pharmacokinetic, and toxicity property predictions for the compounds with stable ligand-target interactions and a molecular dynamics simulation for the highest interacting complex further validated these findings. This work affirmed the anti-EP role of CT flower against EP, suggesting a probable molecular mechanism involved.

Unveiling Anticancer Potential in the Interactions of Melittin Peptides with CD147 Receptor: A Structural and Functional Analysis of Ligand-Target Interactions

In this study, the anticancer potential of melittin peptides interacting with the CD147 receptor was investigated through in silico structural and functional analyses. The interaction between the transmembrane glycoprotein CD147 and cyclophilin A (CypA) activates signaling pathways crucial in cancer pathology. The focus of this study was on the potential of melittin peptides to inhibit this interaction. Structures of the CD147 receptor and melittin peptides were obtained from the Protein Data Bank (PDB), including the three-dimensional structure of the Ig1 domain of CD147 (PDB ID: 5XF0) and melittin structures (PDB IDs: 2MLT, 6O4M, 3QRX, 8AHT, and 8AHS). Validated ligand structures were acquired through X-ray crystallography. Receptor-ligand interactions and anticancer activity were evaluated using the ClusPro2.0 molecular docking server, AnciCP2.0 and ENNAACT anticancer analysis servers, ProtScale hydrophobicity analysis, PDBSum amino acid interaction analysis, and PRODIGY thermodynamic stability analysis tools. Molecular docking simulations analyzed receptor-ligand interactions, emphasizing the role of hydrophobic interactions. Structural analysis revealed variability in peptide quality, with 2MLT demonstrating favorable attributes while 3QRX exhibited weak integrity. Anticancer analysis servers indicated that 2MLT and 3QRX, exhibiting similar binding patterns with 5XF0 and CD147/CypA, may both demonstrate potential anticancer activity. Specifically, non-bonded interactions involving Gly181 and Arg201 in the 5XF0-2MLT complex, and non-bonded interactions involving Pro180, Gly181, and Arg201 in the 5XF0-3QRX complex were highlighted, resembling the interaction pattern of CD147/CypA. Therefore, the importance of understanding molecular interactions and guiding drug discovery through structural examinations and computational analyses was emphasized, providing insights into the anticancer effects and drug design implications of these complexes; moreover, further research into their structural determinants and therapeutic potentials is critically important for biomedical applications.

Trivalent oleanolic acid-glucose conjugates: Synthesis and efficacy against Influenza A virus

Influenza A virus (IAV) leads to significant morbidity and mortality due to the seasonal epidemics and spread. We have demonstrated that oleanolic acid (OA) C28 glucose conjugates and OA trimers are capable of effectively blocking the recognition and interaction between the influenza virus and host cells. In this study, a series of OA-glucose trimers were designed and synthesized through the CuAAC reaction. All trimers underwent screening for anti-IAV activities in vitro. Among these, compounds 13a and 13b showed inhibitory activity against the influenza virus, with IC50 values of 0.68 μM and 0.47 μM, respectively, demonstrating greater potency than oseltamivir (IC50 = 1.36 μM). Results from the time-of-addition experiment and hemagglutination inhibition assay suggest that these OA-glucose trimers may disrupt the recognition between the HA protein of IAV and sialic acid receptors on host cells, thus blocking viral entry. Furthermore, it was found that compound 13b effectively inhibits IAV infection in BALB/c mice. This study has elucidated the structure-activity relationships of OA trimers against the influenza virus and highlighted the utility of multivalent OA conjugates for enhancing ligand-target interactions in anti-influenza virus drug design, laying a groundwork for future research into the antiviral applications of these natural products.

Self-organizing maps of unbiased ligand-target binding pathways and kinetics.

The interpretation of ligand-target interactions at atomistic resolution is central to most efforts in computational drug discovery and optimization. However, the highly dynamic nature of protein targets, as well as possible induced fit effects, makes difficult to sample many interactions effectively with docking studies or even with large-scale molecular dynamics (MD) simulations. We propose a novel application of Self-Organizing Maps (SOMs) to address the sampling and dynamic mapping tasks, particularly in cases involving ligand flexibility and induced fit. The SOM approach offers a data-driven strategy to create a map of the interaction process and pathways based on unbiased MD. Furthermore, we show how the preliminary SOM mapping is complementary to kinetic analysis, with the employment of both network-based approaches and Markov state models. We demonstrate the method by comprehensively mapping a large dataset of 640 μs of unbiased trajectories sampling the recognition process between the phosphorylated YEEI peptide and its high-specificity target lck-SH2. The integration of SOM into unbiased simulation protocols significantly advances our understanding of the ligand binding mechanism. This approach serves as a potent tool for mapping intricate ligand-target interactions with unprecedented detail, thereby enhancing the characterization of kinetic properties crucial to drug design.

Determining the In Vitro Ligand-Target Interaction by Cellular Thermal Shift Assay and Isothermal Dose-Response Fingerprint Assay.

The cellular thermal shift assay (CETSA) and isothermal dose-response fingerprint assay (ITDRF CETSA) have been introduced as powerful tools for investigating target engagement by measuring ligand-triggered thermodynamic stabilization of cellular target proteins. Yet, these techniques have rarely been used to evaluate the thermal stability of RNA-binding proteins (RBPs) when exposed to ligands. Here, we present an adjusted approach using CETSA and ITDRFCETSA to determine the interaction between enasidenib and RBM45. Our assay is sensitive and time-efficient and can potentially be adapted for studying the interactions of RBM45 protein with other potential candidates. Key features • This protocol builds upon the method developed by Molina et al. and extends its application to new protein classes, such as RBPs.

Structure-Based Optimization of Novel Sterol 24-C-Methyltransferase Inhibitors for the Treatment of Candida albicans Infections.

Interfering with sterol biosynthesis is an important strategy for developing safe and effective antifungal drugs. We previously identified compound H55 as an allosteric inhibitor of the fungal-specific C-24 sterol methyltransferase Erg6 for treating Candida albicans infections. Herein, 62 derivatives of H55 were designed and synthesized based on target-ligand interactions to identify more active candidates. Among them, d28 displayed the most potent antivirulence ability (MHIC50 = 0.25 μg/mL) by targeting Erg6, exhibiting an 8-fold increase in potency compared with H55. Moreover, d28 significantly outperformed H55 in inhibiting cell adhesion and biofilm formation, and exhibited minimal cytotoxicity and negligible potential to induce drug resistance. Of note, the coadministration of d28 and other sterol biosynthesis inhibitors, such as tridemorph or terbinafine, demonstrated a strong synergistic antifungal action in vitro and in vivo in a murine skin infection model. These results support the potential application of d28 in the treatment of C. albicans infections.

PT-Finder: A multi-modal neural network approach to target identification

Efficient target identification for bioactive compounds, including novel synthetic analogs, is crucial for accelerating the drug discovery pipeline. However, the process of target identification presents significant challenges and is often expensive, which in turn can hinder the drug discovery efforts. To address these challenges machine learning applications have arisen as a promising approach for predicting the targets for novel chemical compounds. These methods allow the exploration of ligand–target interactions, uncovering of biochemical mechanisms, and the investigation of drug repurposing. Typically, the current target identification tools rely on assessing ligand structural similarities. Herein, a multi-modal neural network model was built using a library of proteins, their respective sequences, and active inhibitors. Subsequent validations showed the model to possess accuracy of 82 % and MPRAUC of 0.80. Leveraging the trained model, we developed PT-Finder (Protein Target Finder), a user-friendly offline application that is capable of predicting the target proteins for hundreds of compounds within a few seconds. This combination of offline operation, speed, and accuracy positions PT-Finder as a powerful tool to accelerate drug discovery workflows. PT-Finder and its source codes have been made freely accessible for download at https://github.com/PT-Finder/PT-Finder.

Abstract 3091: Discovery of highly selective ligands with unique binding modes for challenging oncology targets using DNA-encoded chemical libraries

Abstract DNA-encoded chemical library (DEL) technology enables the efficient screening of large collections of encoded compounds and has emerged as a powerful tool for hit identification in recent years. The technology allows for the multiplexed interrogation of target-ligand binding interactions and results in DEL hits with unusual binding modes and desirable selectivity. This screening methodology is particularly effective for oncology targets. Examples of discovery of highly selective ligands for challenging oncology targets, including kinases, protein-protein interactions, and receptors, will be presented. We will illustrate how DEL campaign strategies directly aim at novel binding modes, and provide molecular details around the uniqueness of these interactions. Furthermore, we will show how these novel binding modes lead to unique pharmacology with direct benefit to patients. Lastly, we will demonstrate how X-Chem’s high-quality encoded libraries enhance the tractability and novelty of chemical equity discovered with the platform. Citation Format: Ying Zhang, Anthony Keefe, Matthew A. Clark. Discovery of highly selective ligands with unique binding modes for challenging oncology targets using DNA-encoded chemical libraries [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3091.

Second Near-Infrared Macrophage-Biomimetic Nanoprobes for Photoacoustic Imaging of Neuroinflammation.

Neuroinflammation is a significant pathological event involving the neurodegenerative process associated with many neurological disorders. Diagnosis and treatment of neuroinflammation in its early stage are essential for the prevention and management of neurological diseases. Herein, we designed macrophage membrane-coated photoacoustic (PA) probes (MSINPs), with targeting specificities based on naturally existing target-ligand interactions for the early diagnosis of neuroinflammation. The second near-infrared dye, IR1061, was doped into silica as the core and was encapsulated with a macrophage membrane. In vitro as well as in vivo, the MSINPs could target inflammatory cells via the inflammation chemotactic effect. PA imaging was used to trace the MSINPs in a neuroinflammation mouse model and showed a great targeted effect of MSINPs in the prefrontal cortex. Therefore, the biomimetic nanoprobe prepared in this study offers a new strategy for PA molecular imaging of neuroinflammation, which can enhance our understanding of the evolution of neuroinflammation in specific brain regions.

KcsA-Kv1.x chimeras with complete ligand-binding sites provide improved predictivity for screening selective Kv1.x blockers

Despite significant advances in the development of therapeutic interventions targeting autoimmune diseases and chronic inflammatory conditions, lack of effective treatment still poses a high unmet need. Modulating chronically activated T cells through the blockade of the Kv1.3 potassium channel is a promising therapeutic approach, however, developing selective Kv1.3 inhibitors is still an arduous task. Phage display-based high throughput peptide library screening is a rapid and robust approach to develop promising drug candidates; however, it requires solid-phase immobilization of target proteins with their binding site preserved. Historically, the KcsA bacterial channel chimera harboring only the turret region of the human Kv1.3 channel was used for screening campaigns. Nevertheless, literature data suggest that binding to this type of chimera does not correlate well with blocking potency on the native Kv1.3 channels. Therefore, we designed and successfully produced advanced KcsA-Kv1.3, -Kv1.1 and -Kv1.2 chimeric proteins in which both the turret and part of the filter regions of the human Kv1.x channels were transferred. These T+F (turret-filter) chimeras showed superior peptide ligand binding predictivity compared to their T-only versions in novel phage ELISA assays. Phage ELISA binding and competition results supported with electrophysiological data confirmed that the filter region of KcsA-Kv1.x is essential for establishing adequate relative affinity order among selected peptide toxins (Vm24 toxin, Hongotoxin-1, Kaliotoxin-1, Maurotoxin, Stichodactyla toxin) and consequently obtaining more reliable selectivity data. These new findings provide a better screening tool for future drug development efforts and offer insight into the target-ligand interactions of these therapeutically relevant ion channels.

Computational Molecular Docking and In-Silico, ADMET Prediction Studies of Quinoline Derivatives as EPHB4 Inhibitor

Background:: The creation and development of novel chemical entities is made possible by numerous computer-aided drug design techniques. The ability to visualize the ligand-target interaction and forecast the important holding pocket locations and affinities of ligands to their intended macromolecules is made possible by pharmacophore-based drug design and understanding in-silico methodologies. Objective:: The aim of the current investigation was to find novel 2-chloroquinoline-3-carboxamide derivatives that target the Ephrin B4 (EPHB4) receptor to treat cancer. Materials and Methods:: Chem Axon Marvin Sketch 5.11.5 was used to create derivatives of 2-chloroquinoline-3-carboxamide. The physicochemical characteristics of compounds as well as their toxicity were predicted using SwissADME& the admet SAR online software’s. Molecular docking technology was used to examine the ligand-receptor interactions of 2-chloroquinoline-3-carboxamide derivatives with the target receptor (PDB- 6FNM) using a variety of software’s, including Autodock1.1.2,Procheck, ProtParam tool, Biovia Discovery Studio Visualizer v20.1.0.19295, MGL Tools 1.5.6, PyMOL, and were all included. Results:: All developed compounds were determined to be orally bioavailable, less toxic, and have acceptable pharmacokinetic properties according to in silico studies. In comparison to the traditional medication Erdafitnib, all new compounds displayed higher docking scores. Conclusion:: The increase in binding energy and the number of H-bonds created by novel derivatives with interactions at distances below 3.40A provide a helpful starting point for formulating and synthesizing compounds that are most suitable for additional research. The application of the 2- chloroquinoline-3-carboxamide moiety as a potential new cancer treatment candidate is supported by its pharmacokinetics &toxicological profile, which may aid medicinal chemists in conducting more in-depth in vitro, in vivo chemical and pharmacological studies.

Insights into dietary phytochemicals targeting Parkinson's disease key genes and pathways: A network pharmacology approach

Parkinson's disease (PD) is a complex neurological disease associated with the degeneration of dopaminergic neurons. Oxidative stress is a key player in instigating apoptosis in dopaminergic neurons. To improve the survival of neurons many dietary phytochemicals have gathered significant attention recently. Thus, the present study implements a comprehensive network pharmacology approach to unravel the mechanisms of action of dietary phytochemicals that benefit disease management. A literature search was performed to identify ligands (i.e., comprising dietary phytochemicals and Food and Drug Administration pre-approved PD drugs) in the PubMed database. Targets associated with selected ligands were extracted from the search tool for interactions of chemicals (STITCH) database. Then, the construction of a gene-gene interaction (GGI) network, analysis of hub-gene, functional and pathway enrichment, associated transcription factors, miRNAs, ligand-target interaction network, docking were performed using various bioinformatics tools together with molecular dynamics (MD) simulations. The database search resulted in 69 ligands and 144 unique targets. GGI and subsequent topological measures indicate histone acetyltransferase p300 (EP300), mitogen-activated protein kinase 1 (MAPK1) or extracellular signal-regulated kinase (ERK)2, and CREB-binding protein (CREBBP) as hub genes. Neurodegeneration, MAPK signaling, apoptosis, and zinc binding are key pathways and gene ontology terms. hsa-miR-5692a and SCNA gene-associated transcription factors interact with all the 3 hub genes. Ligand-target interaction (LTI) network analysis suggest rasagiline and baicalein as candidate ligands targeting MAPK1. Rasagiline and baicalein form stable complexes with the Y205, K330, and V173 residues of MAPK1. Computational molecular insights suggest that baicalein and rasagiline are promising preclinical candidates for PD management.

Ligand-Based Competition Binding by Real-Time 19F NMR in Human Cells.

The development of more effective drugs requires knowledge of their bioavailability and binding efficacy directly in the native cellular environment. In-cell nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for investigating ligand-target interactions directly in living cells. However, the target molecule may be NMR-invisible due to interactions with cellular components, while observing the ligand by 1H NMR is impractical due to the cellular background. Such limitations can be overcome by observing fluorinated ligands by 19F in-cell NMR as they bind to the intracellular target. Here we report a novel approach based on real-time in-cell 19F NMR that allows measuring ligand binding affinities in human cells by competition binding, using a fluorinated compound as a reference. The binding of a set of compounds toward Hsp90α was investigated. In principle, this approach could be applied to other pharmacologically relevant targets, thus aiding the design of more effective compounds in the early stages of drug development.

Computational studies of tyrosinase inhibitors.

Computational studies have significantly advanced the understanding of tyrosinase (TYR) function, mechanism, and inhibition, accelerating the development of more effective and selective inhibitors. This chapter provides an overview of in silico studies on TYR inhibitors, emphasizing key inhibitory chemotypes and the main residues involved in ligand-target interactions. The chapter discusses tools applied in the context of TYR inhibitor development, e.g., structure-based virtual screening, molecular docking, artificial intelligence, and machine learning algorithms.

A Review on Molecular Docking As an Interpretative Tool for Molecular Targets in Disease Management.

One of the most often utilized methods for drug discovery is molecular docking. With docking, one may discover new therapeutically relevant molecules by targeting the molecule and predicting the target-ligand interactions as well as different conformation of ligand at various positions. The prediction signifies the effectiveness of the molecule or the developed molecule having different affinity with target. Drug discovery plays an important role in the development of a new drug molecule of different moiety attached to it, which leads us in the management of several diseases. In silico approach led us to identification of numerous diseases caused by virus, fungi, bacteria, protozoa, and other microorganisms that affect human health. By means of computational approach, we can categorize disease symptoms and use the drugs available for such types of warning signs. After the docking process, molecular dynamics computational technique helps in the simulation of the physical movement of atoms and molecules for a fixed period of time, giving a view of the dynamic evaluation of the system. This review is an attempt to illustrate the role of molecular docking in drug development.

Exploration of the VEGFR-2 inhibition activity of phthalazine derivatives: design, synthesis, cytotoxicity, ADMET, molecular docking and dynamic simulation.

Novel phthalazine derivatives were designed, synthesized and evaluated against Hep G2 and MCF-7 as VEGFR-2 inhibitors. In particular, compounds 2g and 4a were found to be the most potent derivatives among all the tested compounds against MCF-7 and Hep G2 cancer cell lines with IC50 values of 0.15 and 0.12 and 0.18 and 0.09 μM respectively. Moreover, compounds 3a, 3c, 5a and 5b displayed excellent anticancer activities against MCF-7 and Hep G2 cancer cell lines. The highly active derivatives 2g, 3a, 3c, 4a, 5a and 5b were evaluated for their inhibitory activities against VEGFR-2. The tested compounds displayed high to low inhibitory activities with IC50 values ranging from 0.148 to 0.892 μM. Among them, compounds 2g and 4a were found to be the most potent derivatives that inhibited VEGFR-2 with IC50 values of 0.148 and 0.196 μM respectively. Compounds 3a, 3c, 5a and 5b exhibited good activity with IC50 values of 0.375, 0.892, 0.548 and 0.331 μM respectively. Sorafenib was used as a reference drug in this study. Molecular modeling studies were carried out for all compounds against the VEGFR-2 active site. The data obtained from biological testing highly correlated with those obtained from molecular modeling studies. Moreover, MD simulation results indicated the stability of ligand-target interaction. Furthermore, our derivatives 2g and 4a showed a good in silico calculated ADMET profile.

Pancreatic beta cell regenerative potential of Zanthoxylum chalybeum Engl. Aqueous stem bark extract

Ethnopharmacological relevanceZanthoxylum chalybeum Engl. is endemic to Africa and has been used traditionally to treat diabetes mellitus. Moreover, its pharmacological efficacy has been confirmed experimentally using in vitro and in vivo models of diabetes. However, the effects of Z. chalybeum extracts and its major constituent compounds on beta cell and islet regeneration are not clear. Further, the mechanisms associated with observed antidiabetic effects at the beta cell level are not fully elucidated. Aim of the studyWe determined the beta cell regenerative efficacy of Z. chalybeum aqueous stem bark extract, identified the chemical compounds in Z. chalybeum aqueous stem bark extracts and explored their putative mechanisms of action. Materials and methodsPhytochemical profiling of the Z. chalybeum extract was achieved using ultra high-performance liquid chromatography hyphenated to high-resolution mass spectrometry. Thereafter, molecular interactions of the compounds with beta cell regeneration targets were evaluated via molecular docking. In vitro, effects of the extract on cell viability, proliferation, apoptosis and oxidative stress were investigated in RIN-5F beta cells exposed to palmitate or streptozotocin. In vivo, pancreas tissue sections from streptozotocin-induced diabetic male Wistar rats treated with Z. chalybeum extract were stained for insulin, glucagon, pancreatic duodenal homeobox protein 1 (Pdx-1) and Ki-67. ResultsBased on ligand target and molecular docking interactions diosmin was identified as a dual specificity tyrosine-phosphorylation-regulated kinase 1A (Dyrk1A) inhibitor. In vitro, Z. chalybeum augmented cell viability and cell proliferation while in palmitate-pre-treated cells, the extract significantly increased cell activity after 72 h. In vivo, although morphometric analysis showed decreased islet and beta cell size and density, observation of increased Pdx-1 and Ki-67 immunoreactivity in extract-treated islets suggests that Z. chalybeum extract has mild beta cell regenerative potential mediated by increased cell proliferation. ConclusionsOverall, the mitogenic effects observed in vitro, were not robust enough to elicit sufficient recovery of functional beta cell mass in our in vivo model, in the context of a sustained diabetic milieu. However, the identification of diosmin as a potential Dyrk1A inhibitor merits further inquiry into the attendant molecular interactions.

<i>Emblica officinalis</i> Gaertn. (<i>Amalaki</i>): A Natural Herbal Remedy to Enhance Cardiorespiratory Fitness in <i>Ayurveda</i> - An <i>In Silico</i> Molecular Docking Approach

Background: Cardiorespiratory fitness is the capacity of the circulatory and respiratory systems to transport oxygen to the skeletal muscle mitochondria for energy production during physical activity. Cardiorespiratory fitness has been recognized as a vital health biomarker and is very crucial for sports persons. Physical activities, aerobic exercise, yoga, meditation, nutritional supplements, and ergogenic aids are the ways to enhance cardiorespiratory fitness. Emblica officinalis Gaertn. is one of the widely used drugs in Ayurveda traditional medicine to enhance Cardiorespiratory Fitness (CRF). However, there is a dearth of clear information regarding how Emblica officinalis can improve CRF. Objective: The current in silico molecular docking study was planned to identify the phytochemicals, and targets of endurance and predict the probable mode of action of the drug and thereby substantiate the ability of Emblica officinalis as a natural and ethical way of enhancing cardiorespiratory fitness. Methods: The phytochemicals and targets are collected from reliable sources, and the effectiveness of these gene targets was validated using network pharmacology ligand-target interaction methods. The Protein Data Bank and PubChem were used to find the ligands and targets, and PyRx was used to do docking. Conclusion: Emblica officinalis is found to have a positive influence on the 12 metabolic pathways that act in enhancing the cardiorespiratory endurance in the human being. PRKCA was analyzed and concluded as the highly modulated gene target with the lowest binding energy. Thus, Emblica officinalis was found to have an action in enhancing cardio-respiratory endurance.

Covalent Capture and Selection of DNA-Encoded Chemical Libraries via Photo-Activated Lysine-Selective Crosslinkers.

Covalent crosslinking probes have arisen as efficient toolkits to capture and elucidate biomolecular interaction networks. Exploiting the potential of crosslinking in DNA-encoded chemical library (DEL) selection methods significantly boosted bioactive ligand discovery in complex physiological contexts. Herein, we incorporated o-nitrobenzyl alcohol (o-NBA) as a photo-activated lysine-selective crosslinker into divergent DEL formats and achieved covalent capture of ligand-target interactions featuring improved crosslinking efficiency and site specificity. In addition, covalent DEL selection was realized with the modularly designed o-NBA-functionalized mock libraries.

Screening and identification of potential hypoglycemic and hypolipidemic compounds from aqueous extract of Scutellaria baicalensis Georgi root combing affinity ultrafiltration with multiple drug targets and in silico analysis.

Scutellaria baicalensis Georgi, a traditional Chinese medicine, is widely applied to treat various diseases among people, especially in East Asia. However, the specific active compounds in S.baicalensis aqueous extracts (SBAEs) responsible for the hypoglycemic and hypolipidemic properties as well as their potential mechanisms of action remain unclear. This work aimed to explore the potential hypoglycemic and hypolipidemic compounds from SBAE and their potential mechanisms of action. The in vitro inhibitory tests against lipase and α-glucosidase, and the effects of SBAE on glucose consumption and total triglyceride content in HepG2 cells were first performed to evaluate the hypoglycemic and hypolipidemic effects. Then, affinity ultrafiltration liquid chromatography-mass spectrometry (LC-MS) screening strategy with five drug targets, including α-glucosidase, α-amylase, protein tyrosine phosphatase 1B (PTP1B), lipase and 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) was developed to screen out the potential active constituents from SBAE, and some representative active compounds were further validated. SBAE displayed noteworthy hypoglycemic and hypolipidemic properties, and 4, 10, 4, 8, and 8 potential bioactive components against α-amylase, α-glucosidase, PTP1B, HMGCR, and lipase were initially screened out, respectively. The interaction network was thus constructed between the potential bioactive compounds screened out and their corresponding drug targets. Among them, baicalein, wogonin, and wogonoside were revealed to possess remarkable hypoglycemic and hypolipidemic effects. The potential hypolipidemic and hypoglycemic bioactive compounds in SBAE and their mode of action were initially explored through ligand-target interactions by combining affinity ultrafiltration LC-MS strategy with five drug targets.