SwissTargetPrediction: a web server for target prediction of bioactive small molecules

Identifying the toxic mechanisms of emerging electronic contaminations liquid crystal monomers and the construction of a priority control list for graded control

Liquid crystal monomers (LCMs) are identified as emerging organic contaminations with largely unexplored health impacts. To elucidate their toxic mechanisms, support the establishment of environmental discharge and management standards, and promote effective LCMs control, this study constructs a database covering 20,545 potential targets of 1431 LCMs, highlighting 9 key toxic target proteins that disrupt the nervous system and metabolic functions. GO and KEGG pathway analysis suggests LCMs severely affect nervous system, linked to neurodegenerative diseases and mental health disorders, with toxicity variations driven by electronegativity and structural complexity of LCM terminal groups. To achieve tiered control of LCMs, construct toxicity risk control lists for 9 key toxic target proteins, suitable for the graded control of LCMs, management recommendations are provided based on toxicity levels. These lists were validated for reliability and offer reliable toxicity predictions for LCMs. SHAP analysis points to electronic properties, molecular shape, and structural characteristics of LCMs as primary health impact factors. As the first study integrating machine learning with computational toxicology to outline LCMs health impacts, it aims to enhance public understanding of LCM toxicity risks and support the development of environmental standards, effective management of LCM production and emissions, and reduction of public exposure risks.

Multifaceted computational profiling of thymol and geraniol against the human proteome for bio-repellent alternatives: Toxicity predictions, degradation analysis, and quantum mechanical approaches

With growing interest in natural compounds as alternative mosquito repellents, assessing the toxicity and structure of potential repellent naturals like thymol (monoterpene phenol) and geraniol (monoterpene alcohol) is vital for understanding their stability and human impact. This study aimed to determine the structural, toxicity, and binding profiles of thymol and geraniol using computational predictions, xTB metadynamics, quantum mechanics, and principal component analysis. Toxicity studies using Protox-II, T.E.S.T, and SwissADME indicated that thymol and geraniol belong to toxicity class 4 and 5, respectively, with low toxicity predictions in other endpoints. Overall pharmacokinetic profile was generated via pkCSM. Off-target predictions via SwissTarget Predictions, LigTMap, Pharmapper, and SuperPred showed that these molecules can bind to 614 human proteins. The degradation of thymol and geraniol were performed using xTB metadynamics and the outcomes showed that the degradants for both compounds were stable and had lower toxicity profile. Nine tautomers were generated via quantum mechanics for thymol and four for geraniol, with RMSD ranging from 3.8 to 6.3 Å for thymol and 3.6 to 4 Å for geraniol after superimpositions. DFT studies found that HOMO-LUMO values and electronegativity parameters of thymol and geraniol did not differ significantly from their isomers. Binding affinity studies against 614 proteins, analysed via PCA and violin plots, highlighted the probable range of binding. These multifaceted in-silico findings corroborate the stability and potential utility of thymol and geraniol as safer alternatives in repellent applications.

Exploring potential molecular targets and therapeutic efficacy of beauvericin in triple-negative breast cancer cells

Triple negative breast cancer (TNBC) presents a significant global health concern due to its aggressive nature, high mortality rate and limited treatment options, highlighting the urgent need for targeted therapies. Beauvericin, a bioactive fungal secondary metabolite, possess significant anticancer potential, although its molecular targets in cancer cells remain unexplored. This study has investigated possible molecular targets of beauvericin and its therapeutic insights in TNBC cells. In silico studies using molecular docking and MD simulation predicted the molecular targets of beauvericin. The identified targets included MRP-1 (ABCC1), HDAC-1, HDAC-2, LCK and SYK with average binding energy of -90.1, -44.3, -72.1, -105 and -60.8 KJ/mol, respectively, implying its multifaceted roles in reversing drug resistance, inhibiting epigenetic modulators and oncogenic tyrosine kinases. Beauvericin has significantly reduced the viability of MDA-MB-231 and MDA-MB-468 cells, with IC50 concentrations of 4.4 and 3.9 µM, while concurrently elevating the intracellular ROS by 9.0 and 7.9 folds, respectively. Subsequent reduction of mitochondrial transmembrane potential in TNBC cells, has confirmed the induction of oxidative stress, leading to apoptotic cell death, as observed by flow cytometric analyses. Beauvericin has also arrested cell cycle at G1-phase and impaired the spheroid formation and clonal expansion abilities of TNBC cells. The viability of spheroids was reduced upon beauvericin treatment, exhibiting IC50 concentrations of 10.3 and 6.2 µM in MDA-MB-468 and MDA-MB-231 cells, respectively. In conclusion, beauvericin has demonstrated promising therapeutic potential against TNBC cells through possible inhibition of MRP-1 (ABCC1), HDAC-1, HDAC-2, LCK and SYK.

Discovering novel targets of abscisic acid using computational approaches

Abscisic acid (ABA) is a crucial plant hormone that is naturally produced in various mammalian tissues and holds significant potential as a therapeutic molecule in humans. ABA is selected for this study due to its known roles in essential human metabolic processes, such as glucose homeostasis, immune responses, cardiovascular system, and inflammation regulation. Despite its known importance, the molecular mechanism underlying ABA's action remain largely unexplored. This study employed computational techniques to identify potential human ABA receptors. We screened 64 candidate molecules using online servers and performed molecular docking to assess binding affinity and interaction types with ABA. The stability and dynamics of the best complexes were investigated using molecular dynamics simulation over a 100 ns time period. Root mean square fluctuations (RMSF), root mean square deviation (RMSD), solvent-accessible surface area (SASA), radius of gyration (Rg), free energy landscape (FEL), and principal component analysis (PCA) were analyzed. Next, the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method was employed to calculate the binding energies of the complexes based on the simulated data. Our study successfully pinpointed four key receptors responsible for ABA signaling (androgen receptor, glucocorticoid receptor, mineralocorticoid receptor, and retinoic acid receptor beta) that have a strong affinity for binding with ABA and remained structurally stable throughout the simulations. The simulations with Hydralazine as an unrelated ligand were conducted to validate the specificity of the identified receptors for ABA. The findings of this study can contribute to further experimental validation and a better understanding of how ABA functions in humans.

Natural compound screening predicts novel GSK-3 isoform-specific inhibitors

Glycogen synthase kinase-3 (GSK-3) plays important roles in the pathogenesis of cardiovascular, metabolic, neurological disorders and cancer. Isoform-specific loss of either GSK-3α or GSK-3β often provides cytoprotective effects under such clinical conditions. However, available synthetic small molecule inhibitors are relatively non-specific, and their chronic use may lead to adverse effects. Therefore, screening for natural compound inhibitors to identify the isoform-specific inhibitors may provide improved clinical utility. Here, we screened 70 natural compounds to identify novel natural GSK-3 inhibitors employing comprehensive in silico and biochemical approaches. Molecular docking and pharmacokinetics analysis identified two natural compounds Psoralidin and Rosmarinic acid as potential GSK-3 inhibitors. Specifically, Psoralidin and Rosmarinic acid exhibited the highest binding affinities for GSK-3α and GSK-3β, respectively. Consistent with in silico findings, the kinase assay-driven IC50 revealed superior inhibitory effects of Psoralidin against GSK-3α (IC50 = 2.26 μM) vs. GSK-3β (IC50 = 4.23 μM) while Rosmarinic acid was found to be more potent against GSK-3β (IC50 = 2.24 μM) than GSK-3α (IC50 = 5.14 μM). Taken together, these studies show that the identified natural compounds may serve as GSK-3 inhibitors with Psoralidin serving as a better inhibitor for GSK-3α and Rosmarinic for GSK-3β isoform, respectively. Further characterization employing in vitro and preclinical models will be required to test the utility of these compounds as GSK-3 inhibitors for cardiometabolic and neurological disorders and cancers.

Network pharmacology-based approach to investigate the molecular targets and molecular mechanisms of Rosmarinus officinalis L. for treating aging-related disorders

Aging, a natural biological process, presents challenges in maintaining physiological well-being and is associated with increased vulnerability to diseases. Addressing aging mechanisms is crucial for developing effective preventive and therapeutic strategies against age-related ailments. Rosmarinus officinalis L. is a medicinal herb widely used in traditional medicine, containing diverse bioactive compounds that have been studied for their antioxidant and anti-inflammatory properties, which are associated with potential health benefits. Using network pharmacology, this study investigates the anti-aging function and underlying mechanisms of R. officinalis. Through network pharmacology analysis, the top 10 hub genes were identified, including TNF, CTNNB1, JUN, MTOR, SIRT1, and others associated with the anti-aging effects. This analysis revealed a comprehensive network of interactions, providing a holistic perspective on the multi-target mechanism underlying Rosemary's anti-aging properties. GO and KEGG pathway enrichment analysis revealed the relevant biological processes, molecular functions, and cellular components involved in treating aging-related conditions. KEGG pathway analysis shows that anti-aging targets of R. officinalis involved endocrine resistance, pathways in cancer, and relaxin signaling pathways, among others, indicating multifaceted mechanisms. Genes like MAPK1, MMP9, and JUN emerged as significant players. These findings enhance our understanding of R. officinalis's potential in mitigating aging-related disorders through multi-target effects on various biological processes and pathways. Such approaches may reduce the risk of failure in single-target and symptom-based drug discovery and therapy.

Deciphering the mechanism of Chaihu Shugan San in the treatment of nonalcoholic steatohepatitis using network pharmacology and molecular docking

OBJECTIVES

In China, there is a long history and rich clinical experience in treating nonalcoholic steatohepatitis (NASH) with traditional Chinese herbal medicines, including Chai Hu Shu Gan San. This study aims to investigate the potential regulatory effects of Chaihu Shugan San (CSS) on liver lipid metabolism and inflammatory damage in mice with experimental nonalcoholic steatohepatitis (NASH) induced by a choline-deficient high-fat diet (CDHFD). Utilizing network pharmacology, we systematically explore the mechanisms of action and therapeutic potential of CSS against NASH.

METHODS

Potential targets in CSS and targets for NASH were identified using online databases. Functional enrichment and protein-protein interaction analyses were conducted to identify hub-targeted genes and elucidate the underlying molecular mechanisms. The affinities of active compounds in CSS with hub-targeted genes were evaluated using molecular docking. Finally, hub-targeted genes were validated through real-time polymerase chain reaction, western blotting, and immunofluorescence in choline-deficient high-fat diet mice, both with and without CSS treatment.

KEY FINDINGS

CSS reduces serum ALT and AST levels in NASH mice(P < 0.05) and ameliorates ballooning degeneration in the livers of NASH mice, thereby lowering the NAS score(P < 0.05). Including naringenin, high-performance liquid chromatography/mass spectrometrys identified 12 chromatographic peaks. Based on network pharmacology analysis, CSS contains a total of 103 active compounds and 877 target genes. Transferase activity represents a potential mechanism for therapeutic intervention of CSS in NASH. The transcriptional levels and protein expression of the SIRT1 gene in NASH mice are significantly increased by CSS (P < 0.05).

CONCLUSIONS

Naringenin is probable active compound in CSS and SIRT1 is the hub gene by which CSS is involved in NASH treatment.

Dentatacid A: An Unprecedented 2, 3-Seco-arbor-2, 3-dioic Triterpenoid from the Invasive Plant Euphorbia dentata, with Cytotoxicity Effect on Colon Cancer

Euphorbia dentata Michx. is an invasive plant species in China, known for its toxicity and potential to reduce crop yields, posing numerous threats. To gain a deeper understanding of this invasive plant, phytochemical methods were employed to isolate 13 terpenoids (1-11, 19, 20) and 7 sterols (12-18) from the ethanol extract of E. dentata, identifying one new compound and 19 known compounds. Within spectroscopic methods such as NMR, HR-ESI-MS, and ECD, the structures and absolute configurations of these compounds were established. Among them, dentatacid A (11) possesses an unprecedented 2, 3-seco-arbor-2, 3-dioic skeleton within the potential biosynthetic pathway proposed. Dentatacid A also exhibited excellent anti-proliferative activity against the HT-29 (human colorectal adenocarcinoma) cell line, with an IC50 value of 2.64 ± 0.78 μM, which was further confirmed through network pharmacology and molecular docking. This study significantly expands the chemical diversity of E. dentata and offers new insights into the resource utilization and management of this invasive plant from the perspective of natural product discovery.

Diterpenoids of Caryopteris trichosphaera W. W. Sm. inhibiting MRSA and VRE in vitro and in vivo

ETHNOPHARMACOLOGICAL RELEVANCE

Caryopteris trichosphaera W. W. Sm., a traditional ethnic medicine, was recorded in the Compendium of Materia Medica for treating wound infection by pathogenic infection. However, its antibacterial potential and bioactive compositions against drug-resistant bacteria need to be validated.

AIM OF THE STUDY

To investigate the chemical constituents of C. trichosphaera and explore its anti-MRSA component in vitro and in vivo, together with the antibacterial mechanism.

MATERIALS AND METHODS

Bioactive constituents investigation was carried out by phytochemical method and antibacterial screening. The antibacterial mechanism was predicted by network pharmacology, which was further validated by time-kill analysis, membrane function tests, multigenerational resistance induction assay and biofilm test, and metabolomics analysis in vitro. In addition, MRSA-induced epidermal infection in mice was selected to evaluate its pharmacological effect in vivo.

RESULTS

Six antibacterial diterpenoids against MRSA and VRE with MIC values 4-32 μg/mL from C. trichosphaera were reported for the first time, in which the major compound cativic acid (1) disrupted MRSA cell membranes by modulating permeability, depolarization, and fluidity while increasing reactive oxygen species (ROS) and malondialdehyde (MDA) levels. It also displayed remarkable anti-biofilm activity without inducing bacterial resistance or cytotoxicity. Moreover, cativic acid affected MRSA biosynthesis of cofactors, amino acid biosynthesis, nucleotide metabolism by metabolomics analysis. Furthermore, cativic acid accelerated wound healing in MRSA-infected mouse skin wounds, even better than vancomycin.

CONCLUSIONS

The results supported the traditional use of C. trichosphaera, and presented unreported anti-MRSA agent, cativic acid, as a plant-derived bactericide in vitro and in vivo for the first time.

Chlorogenic acid attenuates idiopathic pulmonary fibrosis: An integrated analysis of network pharmacology, molecular docking, and experimental validation

AIMS

Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive lung condition, the cause of which remains unknown and for which no effective therapeutic treatment is currently available. Chlorogenic acid (CGA), a natural polyphenolic compound found in different plants and foods, has emerged as a promising agent due to its anti-inflammatory, antioxidant, and antifibrotic properties. However, the molecular mechanisms underlying the therapeutic effect of CGA in IPF remain unclear. The purpose of this study was to analyze the pharmacological impact and underlying mechanisms of CGA in IPF.

MAIN METHODS

Using network pharmacology analysis, genes associated with IPF and potential molecular targets of CGA were identified through specialized databases, and a protein-protein interaction (PPI) network was constructed. Molecular docking was performed to accurately select potential therapeutic targets. To investigate the effects of CGA on lung histology and key gene expression, a murine model of bleomycin-induced lung fibrosis was used.

KEY FINDINGS

Network pharmacology analysis identified 384 were overlapped between CGA and IPF. Key targets including AKT1, TP53, JUN, CASP3, BCL2, MMP9, NFKB1, EGFR, HIF1A, and IL1B were identified. Pathway analysis suggested the involvement of cancer, atherosclerosis, and inflammatory processes. Molecular docking confirmed the stable binding between CGA and targets. CGA regulated the expression mRNA of EGFR, MMP9, AKT1, BCL2 and IL1B and attenuated pulmonary fibrosis in the mouse model.

SIGNIFICANCE

CGA is a promising multi-target therapeutic agent for IPF, which is supported by its efficacy in reducing fibrosis through the modulation of key pathways. This evidence provides a basis to further investigate CGA as an IPF potential treatment.

Decoding potential targets and pharmacologic mechanisms of curcumin in treating non-small cell lung carcinoma via bioinformatics and molecular docking

Emerging evidence demonstrates that curcumin has an inhibitory effect on non-small cell lung cancer (NSCLC), and its targets and mechanism of action need further exploration. The goal of this study was to explore the potential targets and mechanism of curcumin against NSCLC by network pharmacology, bioinformatics, and experimental validation, thereby providing more insight into combination treatment with curcumin for NSCLC in preclinical and clinical research. Curcumin targets against NSCLC were predicted based on HIT2.0, STD, CTD, and DisGeNET, and the core targets were analyzed via protein-protein interaction network construction (PPI), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and molecular docking. The gene expression levels of samples in A549 cells, NCI-H460, and curcumin treated groups were detected by real-time quantitative PCR. A total of 67 common targets between curcumin and NSCLC were collected by screening public databases. GO and KEGG analysis suggested that curcumin treatment of NSCLC mainly involves cancer-related pathways, such as PI3K-AKT signaling pathway, Foxo signaling pathway, microRNAs, MAPK signaling pathway, HIF-1 signaling pathway, etc. The targets with the highest degree were identified through the PPI network, namely CASP3, CTNNB1, JUN, IL6, MAPK3, HIF1A, STAT3, AKT1, TP53, CCND1, VEGFA, and EGFR. The results of the in vitro experiments showed that curcumin treatment of NSCLC down-regulated the gene expressions of CCND1, CASP3, HIF1A, IL-6, MAPK3, STAT3, AKT1, and TP53. Our findings revealed that curcumin functions as a potential therapeutic candidate for NSCLC by suppressing multiple signaling pathways and interacting with multiple gene targets.

Mechanism of apoptosis in oral squamous cell carcinoma promoted by cardamonin through PI3K/AKT signaling pathway

Currently, surgical resection remains the primary approach for treating oral squamous cell carcinoma (OSCC), with limited options for effective drug therapy. Cardamonin, a principal compound derived from Myristica fragrans of the Zingiberaceae family, has garnered attention for its potential to suppress the onset and progression of various malignancies encompassing breast cancer, hepatocellular carcinoma, and ovarian cancers. Nevertheless, the involvement of cardamonin in the treatment of OSCC and its underlying mechanisms are yet to be elucidated. This research explored the possible target of cardamonin in treating OSCC via network pharmacological analysis. Subsequently, this research investigated the impact of cardamonin on OSCC cells via in vitro experiments, revealing its capacity to impede the migration, proliferation, and invasion of OSCC cells. Additionally, western blotting analysis demonstrated that cardamonin facilitates apoptosis by regulating the PI3K/AKT pathway. The findings suggest that MMP9 and the PI3K/AKT signaling pathway may serve as the target and pathway of cardamonin in treating OSCC. To summarize, the research findings suggest that cardamonin may facilitate apoptosis in OSCC cells by inhibition of PI3K/AKT pathway activation. These outcomes offer a theoretical basis for the utilization of cardamonin as a natural drug for treating OSCC.

Exploring the underlying mechanisms of Danshen-Shanzha Decoction on coronary heart disease: An integrated analysis combining pharmacoinformatics and experimental validation

ETHNOPHARMACOLOGICAL RELEVANCE

The Danshen-Shanzha Decoction (DSD) is a renowned herbal combination consisting of the root of Salvia miltiorrhiza Bunge (known as Danshen in Chinese) and the fruits of Crataegus pinnatifida Bunge (known as Shanzha in Chinese), which has exhibited remarkable clinical efficacy in the treatment of coronary heart disease (CHD) in traditional Chinese medicine, with its earliest recorded application dating to around 202 BCE during the Han Dynasty. Despite significant advancements in the fundamental research and clinical applications of DSD over the past few decades, the precise bioactive components as well as the underlying mechanisms responsible for its protective effect on CHD remain unelucidated.

AIM OF THE STUDY

The present study was designed to elucidate the bioactive components and potential mechanism of DSD in the treatment of CHD using in silico technologies integrated with pharmacoinformatic methods and experimental validation.

MATERIALS AND METHODS

The chemical components of DSD were analyzed and identified using UPLC-Q-TOF-MS. Pharmacoinformatic-based methods were employed to comprehensively investigate the principal active components and targets of DSD for treating CHD. GO and KEGG pathway analyses were utilized to elucidate the underlying mechanism responsible for DSD's efficacy against CHD. Molecular docking and molecular dynamics simulation were performed to assess the binding affinity between active components and putative targets. Furthermore, surface plasmon resonance (SPR) was carried out to verify the affinity and kinetic characteristics of major components to STAT3 protein. Subsequently, a series of in vitro experiments, including cell viability test, flow cytometric analysis, ELISA and western blotting, were conducted to validate the predicted results in an oxygen-glucose deprivation (OGD)-stimulated H9c2 model.

RESULTS

A total of 96 compounds were characterized by UPLC-Q-TOF-MS, and 281 overlapping targets were identified through pharmacoinformatic-based methods. Among these, ten critical compounds were determined as the core active components of DSD. The core targets associated with the development of CHD included STAT3, SRC, TP53, JUN, and AKT1. Notably, Dihydrotanshinone I and (+)-Epicatechin exhibited strong binding affinity towards STAT3. The potential mechanisms by which DSD modulates the pathological progression of CHD were predicted to involve inflammation, oxidative stress, and apoptosis. Importantly, the cytoprotective effect of DSD against apoptosis was confirmed in OGD-stimulated H9c2 cells, as evidenced by the upregulation of Bcl-2 expression and downregulation of both Bax and cleaved caspase-3 expressions upon DSD treatment. Furthermore, DSD significantly enhanced the phosphorylated protein expressions of JAK2 and STAT3 compared to the OGD group, suggesting its potential role in modulating related signaling pathways.

CONCLUSIONS

The current study successfully fills the gap in the understanding of the chemical profiles of DSD, predicting its active components, potential targets, and molecular mechanisms in the treatment of CHD. These findings not only provide a valuable strategy but also robust data support for future investigations into DSD, thereby facilitating the identification of novel therapeutic targets for traditional Chinese medicines in the battle against CHD.

Emerging insights into traditional Chinese medicine associated with neurodegenerative diseases: A bibliometric analysis

ETHNOPHARMACOLOGICAL RELEVANCE

Research suggests that traditional Chinese medicine (TCM) holds promise in offering innovative approaches to tackle neurodegenerative disorders. In our endeavor, we conducted a comprehensive bibliometric analysis to delve into the landscape of TCM research within the realm of neurodegenerative diseases, aiming to uncover the present scenario, breadth, and trends in this field. This analysis presents potentially valuable insights for the clinical application of traditional Chinese medicine and provides compelling evidence supporting its efficacy in the treatment of neurodegenerative conditions.

AIM OF THE STUDY

The incidence of neurodegenerative diseases is on the rise, yet effective treatments are still lacking. Research indicates that TCM could offer novel perspectives for addressing neurodegenerative conditions. Nonetheless, the literature on this topic is intricate and multifaceted, with existing reviews offering only limited coverage. To gain a thorough understanding of TCM research in neurodegenerative diseases, we undertook a bibliometric analysis to explore the current status, scope, and trends in this area.

MATERIALS AND METHODS

A literature search was carried out on April 1, 2024, utilizing the Web of Science Core Collection (WoSCC). Visualization and quantitative analyses were then performed with the assistance of CiteSpace, VOSviewer, and R software.

RESULTS

A total of 6856 articles were retrieved in the search. Research on TCM for neurodegenerative diseases commenced in 1989 and has exhibited a notable overall growth since then. Main research contributors include East Asian countries like China, as well as the United States. Through our analysis, we identified 15 highly productive authors, 10 top-tier journals, 13 citation clusters, 11 influential articles, and observed a progression in keyword evolution across 4 distinct categories. In 2020, there was a significant upsurge in the knowledge base, collaboration efforts, and publication output within the field. This field is interdisciplinary: network pharmacology emerges as the cutting-edge paradigm in TCM research, while Alzheimer's disease remains a prominent focus among neurodegenerative conditions due to its evolving etiology. A burst detection analysis unveils that in 2024, the focal points of research convergence between TCM and neurodegenerative diseases lie in two key biological processes or mechanisms: autophagy and microbiota.

CONCLUSIONS

For the first time, this study quantitatively and visually captures the evolution of TCM in addressing neurodegenerative diseases, showcasing a notable acceleration in recent years. Our findings underscore the pivotal role of interdisciplinary collaboration and the necessity for increased global partnerships. Network pharmacology, leveraging the advancements of the big data era, embraces a holistic and systematic approach as a novel paradigm in exploring traditional Chinese medicine and unraveling their fundamental mechanisms. Three ethnomedical plants-Tianma, Renshen, and Wuweizi-demonstrate the promise of their bioactive compounds in treating neurodegenerative disorders, bolstered by their extensive historical usage for such ailments. Moreover, our intricate analysis of the evolutionary trajectories of key themes such as targets and biomarkers substantially enriches our comprehension of the underlying mechanisms involved.

Ligand and structure-based virtual screening approaches in drug discovery: minireview

The compilation of ligand and structure-based molecular modeling methods has become an important practice in virtual screening applied to drug discovery. This systematic review addresses and ranks various virtual screening strategies to drive the selection of the optimal method for studies that have as their starting point a multi-ligand investigation and investigation based on the protein structure of a therapeutic target. This study shows examples of applications and an evaluation based on the objective and problematic of a series of virtual screening studies present in the ScienceDirect® database. The results showed that the molecular docking technique is widely used in scientific production, indicating that approaches that use protein structure as a starting point are the most promising strategy for drug discovery that relies on virtual screening-based research.

Polypharmacology prediction: the long road toward comprehensively anticipating small-molecule selectivity to de-risk drug discovery

INTRODUCTION

Small molecules often bind to multiple targets, a behavior termed polypharmacology. Anticipating polypharmacology is essential for drug discovery since unknown off-targets can modulate safety and efficacy - profoundly affecting drug discovery success. Unfortunately, experimental methods to assess selectivity present significant limitations and drugs still fail in the clinic due to unanticipated off-targets. Computational methods are a cost-effective, complementary approach to predict polypharmacology.

AREAS COVERED

This review aims to provide a comprehensive overview of the state of polypharmacology prediction and discuss its strengths and limitations, covering both classical cheminformatics methods and bioinformatic approaches. The authors review available data sources, paying close attention to their different coverage. The authors then discuss major algorithms grouped by the types of data that they exploit using selected examples.

EXPERT OPINION

Polypharmacology prediction has made impressive progress over the last decades and contributed to identify many off-targets. However, data incompleteness currently limits most approaches to comprehensively predict selectivity. Moreover, our limited agreement on model assessment challenges the identification of the best algorithms - which at present show modest performance in prospective real-world applications. Despite these limitations, the exponential increase of multidisciplinary Big Data and AI hold much potential to better polypharmacology prediction and de-risk drug discovery.

Multifaceted targets of cannabidiol in epilepsy: Modulating glutamate signaling and beyond

Cannabidiol has been reported to interact with broad-spectrum biological targets with pleiotropic pharmacology including epilepsy although a cohesive mechanism is yet to be determined. Even though some studies propose that cannabidiol may manipulate glutamatergic signals, there is insufficient evidence to support cannabidiol direct effect on glutamate signaling, which is important in intervening epilepsy. Therefore, the present study aimed to analyze the epilepsy-related targets for cannabidiol, assess the differentially expressed genes with its treatment, and identify the possible glutamatergic signaling target. In this study, the epileptic protein targets of cannabidiol were identified using the Tanimoto coefficient and similarity index-based targets fishing which were later overlapped with the altered expression, epileptic biomarkers, and genetically altered proteins in epilepsy. The common proteins were then screened for possible glutamatergic signaling targets with differentially expressed genes. Later, molecular docking and simulation were performed using AutoDock Vina and GROMACS to evaluate binding affinity, ligand-protein stability, hydrophilic interaction, protein compactness, etc. Cannabidiol identified 30 different epilepsy-related targets of multiple protein classes including G-protein coupled receptors, enzymes, ion channels, etc. Glutamate receptor 2 was identified to be genetically varied in epilepsy which was targeted by cannabidiol and its expression was increased with its treatment. More importantly, cannabidiol showed a direct binding affinity with Glutamate receptor 2 forming a stable hydrophilic interaction and comparatively lower root mean squared deviation and residual fluctuations, increasing protein compactness with broad conformational changes. Based on the cheminformatic target fishing, evaluation of differentially expressed genes, molecular docking, and simulations, it can be hypothesized that cannabidiol may possess glutamate receptor 2-mediated anti-epileptic activities.

High throughput virtual screening and validation of Plant-Based EGFR L858R kinase inhibitors against Non-Small cell lung Cancer: An integrated approach Utilizing GC-MS, network Pharmacology, Docking, and molecular dynamics

Lung cancer ranks as the 2nd most common cancer globally. It's the most prevalent cancer in men and the 2nd most common in women. The prominent events in EGFR-mutated non-small-cell lung cancer (NSCLC) include the emergence of the L858R mutation within EGFR exon 21. Despite the promising efficacy of EGFR inhibitors in managing lung cancer, the development of acquired resistance poses a significant hurdle. In the current investigation, we focused on the screening of two phytochemicals, namely Dehydrocostus lactone and Mokkolactone, derived from the Saussurea lappa plant, as potential inhibitors targeting EGFR L858R mutant lung cancer. The chloroform and ethanol extract of the plant demonstrated anti-proliferative activity through the Resazurin chemosensitivity assay, exhibiting an IC50 value of 37.90 ± 0.29 µg/ml with selectivity index 2.4. Through a GC-MS study, we identified 11 phytochemicals for further insilico analysis. These compounds underwent ADMET assessment followed by drug likeliness analysis before being subjected to molecular docking against EGFR L858R, identified through protein-protein interaction network analysis. All phytochemicals exhibited binding energy scores ranging from -6.9 to -8.1 kcal/mol. Dehydrocostus lactone and Mokkolactone were specifically identified for their binding profile. Findings from 100 ns molecular dynamics simulations demonstrated their enhanced stability compared to the reference ligand DJK. This was evident in the root mean square deviation (RMSD) values, ranging from 0.23 ± 0.01 nm to 0.30 ± 0.05 nm, the radius of gyration values, from 1.71 ± 0.01 nm to 1.72 ± 0.01 nm, and the solvent accessible surface area values, from 155.39 ± 2.40 nm2 to 159.32 ± 2.14 nm2. Additionally, favourable characteristics were observed in terms of hydrogen bonding, principal component analysis, and free energy landscape analysis. Examination of their electronic structure via density functional theory revealed efficient properties, with the highest occupied molecular orbital-least unoccupied molecular orbital energy gap values ranging from -3.984 eV to -6.547 eV. Further, in vivo analysis is required to gain a more comprehensive understanding and efficacy of these identified phytochemicals against lung cancer.

Exploring the potential mechanisms of Rehmannia glutinosa in treating sepsis based on network pharmacology

The present study utilized network pharmacology to identify therapeutic targets and mechanisms of Rehmannia glutinosa in sepsis treatment. RNA-sequencing was conducted on peripheral blood samples collected from 23 sepsis patients and 10 healthy individuals. Subsequently, the RNA sequence data were analyzed for differential expression. Identification of active components and their putative targets was achieved through the HERB and SwissTarget Prediction databases, respectively. Functional enrichment analysis was performed using GO and KEGG pathways. Additionally, protein-protein interaction networks were constructed and survival analysis of key targets was conducted. Single-cell RNA sequencing provided cellular localization data, while molecular docking explored interactions with central targets. Results indicated significant involvement of identified targets in inflammation and Th17 cell differentiation. Survival analysis linked several targets with mortality rates, while molecular docking highlighted potential interactions between active components and specific targets, such as rehmaionoside a with ADAM17 and rehmapicrogenin with CD81. Molecular dynamics simulations confirmed the stability of these interactions, suggesting Rehmannia glutinosa's role in modulating immune functions in sepsis.

Exploring the therapeutic targets of stevioside in management of type 2 diabetes by network pharmacology and in-silico approach

AIMS

The main objective of the current study is to investigate the pathways and therapeutic targets linked to stevioside in the management of T2D using computational approaches.

METHODS

We collected RNA-seq datasets from NCBI, then employed GREIN to retrieve differentially expressed genes (DEGs). Computer-assisted techniques DAVID, STRING and NetworkAnalyst were used to explore common significant pathways and therapeutic targets associated with T2D and stevioside. Molecular docking and dynamics simulations were conducted to validate the interaction between stevioside and therapeutic targets.

RESULTS

Gene ontology and KEGG analysis revealed that prostaglandin synthesis, IL-17 signaling, inflammatory response, and interleukin signaling were potential pathways targeted by stevioside in T2D. Protein-protein interactions (PPI) analysis identified six common hub proteins (PPARG, PTGS2, CXCL8, CCL2, PTPRC, and EDN1). Molecular docking results showed best binding of stevioside to PPARG (-8 kcal/mol) and PTGS2 (-10.1 kcal/mol). Finally, 100 ns molecular dynamics demonstrated that the binding stability between stevioside and target protein (PPARG and PTGS2) falls within the acceptable range.

CONCLUSIONS

This study reveals that stevioside exhibits significant potential in controlling T2D by targeting key pathways and stably binding to PPARG and PTGS2. Further research is necessary to confirm and expand upon these significant computational results.

The Immunosuppressive Properties of Cyclo-[D-Pro-Pro-β3-HoPhe-Phe-] Tetrapeptide Selected from Stereochemical Variants of Cyclo-[Pro-Pro-β3-HoPhe-Phe-] Peptide

The anti-inflammatory, antiviral, and anti-cancer properties, as well as the mechanism of action of cyclo-[Pro-Pro-β3-HoPhe-Phe-] tetrapeptide (denoted as 4B8M), were recently described. The aim of this work was to synthesize and evaluate the immunosuppressive actions of the stereochemical variants of 4B8M by sequential substitution of L-amino acids by D-amino acids (a series of peptides denoted as P01-P07) using parent 4B8M as a reference compound. In addition, diverse available bioinformatics tools using machine learning and artificial intelligence were tested to find the bio-pharmacokinetic and polypharmacological attributes of analyzed stereomers. All peptides were non-toxic to human peripheral blood mononuclear cells (PBMCs) and only cyclo-[D-Pro-Pro-β3-HoPhe-Phe-] peptide (P03) was capable of inhibiting mitogen-induced PBMC proliferation. The peptides inhibited the lipopolysaccharide (LPS)-induced production of tumor necrosis factor-alpha (TNF-α) to various degrees, with P04 (cyclo-[Pro-Pro-D-β3-HoPhe-Phe-]) and P03 being the most potent. For further in vivo studies, P03 was selected because it had the combined properties of inhibiting cell proliferation and TNF-α production. P03 demonstrated a comparable ability to 4B8M in the inhibition of auricle edema and lymph node cell number and in the normalization of a distorted blood cell composition in contact sensitivity to the oxazolone mouse model. In the mouse model of carrageenan-induced inflammation of the air pouch, P03 exhibited a similar inhibition of the cell number in the air pouches as 4B8M, but its inhibitory effects on the percentage of neutrophils and eosinophils in the air pouches and blood, as well as on mastocyte degranulation in the air pouches, were stronger in comparison to 4B8M. Lastly, in a mouse model of dextran sulfate-induced colitis, similar effects to 4B8M regarding thymocyte number restoration and normalization of the blood cell pictures by P03 were observed. In summary, depending on either experimental findings or in silico predictions, P03 demonstrated comparable, or even better, anti-inflammatory and bio-pharmacokinetic properties to 4B8M and may be considered as a potential therapeutic. The possibility of P00 and P03 identification by circular dichroism measurements was tested by quantum-chemical calculations.

Polyphenolic metacyclophane as a radical scavenger for therapeutic activation: a computational study

Modeling antioxidants for improved human health is a prime area of research. Inclusion complexes exhibit antioxidant activity. Supramolecular scaffolds like calixtyrosol are anticipated to have considerable antioxidant and therapeutic activity. In this study, we have designed 30 polyphenolic metacyclophanes and investigated their antioxidant properties. Exceptional O─H bond dissociation energy of 44 kcal/mol is reported for a metacyclophane with acyl urea linkage. This may be explained through a cooperative effect of localization of spin density distribution and an intramolecular hydrogen bonding of the corresponding radical. Further, the pharmacokinetics and toxicity analysis screened eight drug-like candidates. The interaction of the eight screened molecules with the Lysozyme transport protein and SOD protein has been studied using the molecular docking approach. Lastly, the MD simulations are performed to analyze the conformational changes of the transport protein after complexation with the proposed molecules. Comprehensive analyses including density functional studies of physiological parameters, favorable pharmacokinetics, toxicity, molecular docking, and MD simulations affirmed polyphenolic metacyclophane XXI as a radical scavenging and drug-like candidate.

The therapeutic targets and signaling mechanisms of ondansetron in the treatment of critical illness in the ICU

Background

There is accumulating evidence regarding the benefits of the 5-HT3 receptor antagonist ondansetron for the treatment of critical illness due to its potential anti-inflammatory effect. This study attempted to determine the potential targets and molecular mechanisms of ondansetron's action against critical illnesses.

Methods

A bioinformatics analysis of network pharmacology was conducted to demonstrate screening targets and the signaling pathways of ondansetron action against the most common critical illnesses such as acute kidney injury (AKI), sepsis, and acute respiratory distress syndrome (ARDS). Experiments of LPS-stimulated rat neutrophils with ondansetron treatment were conducted to further validate the relevant hypothesis.

Results

A total of 198, 111, and 26 primary causal targets were identified from the data for the action of ondansetron against AKI, sepsis, and ARDS respectively. We found that the pathway of neutrophil extracellular traps (NETs) formation is statistically significantly involved in the action of ondansetron against these three critical illnesses. In the pathway of NETs formation, the common drug-disease intersection targets in these three critical illnesses were toll-like receptor 8 (TLR8), mitogen-activated protein kinase-14 (MAPK14), nuclear factor kappa-B1 (NFKB1), neutrophil elastase (NE), and myeloperoxidase (MPO). Considering these bioinformatics findings, we concluded that ondansetron anti-critical illness effects are mechanistically and pharmacologically implicated with suppression of neutrophils-associated inflammatory processes. It was also showed that after treatment of LPS-stimulated rat neutrophils with ondansetron, the key proteins NE, MPO, and Peptide Arginine Deaminase 4 (PAD4) in the NETs formation were significantly reduced, and the inflammatory factors IL-6, IL-1β, TNF-α, and chemokine receptor (CXCR4) were also significantly decreased.

Conclusion

The excessive formation of NETs may have important research value in the development and progression of critical illness. Ondansetron may reduce excessive inflammatory injury in critical diseases by reducing the formation of NETs via influencing the five targets: TLR8, NFKB1, MAPK14, NE, and MPO. Ondansetron and these primary predictive biotargets may potentially be used to treat critical illness in future clinical practice.

Predicting Antigen-Specificities of Orphan T Cell Receptors from Cancer Patients with TCRpcDist

Approaches to analyze and cluster T-cell receptor (TCR) repertoires to reflect antigen specificity are critical for the diagnosis and prognosis of immune-related diseases and the development of personalized therapies. Sequence-based approaches showed success but remain restrictive, especially when the amount of experimental data used for the training is scarce. Structure-based approaches which represent powerful alternatives, notably to optimize TCRs affinity toward specific epitopes, show limitations for large-scale predictions. To handle these challenges, TCRpcDist is presented, a 3D-based approach that calculates similarities between TCRs using a metric related to the physico-chemical properties of the loop residues predicted to interact with the epitope. By exploiting private and public datasets and comparing TCRpcDist with competing approaches, it is demonstrated that TCRpcDist can accurately identify groups of TCRs that are likely to bind the same epitopes. Importantly, the ability of TCRpcDist is experimentally validated to determine antigen specificities (neoantigens and tumor-associated antigens) of orphan tumor-infiltrating lymphocytes (TILs) in cancer patients. TCRpcDist is thus a promising approach to support TCR repertoire analysis and TCR deorphanization for individualized treatments including cancer immunotherapies.

Predicting novel targets with Bayesian machine learning by integrating multiple biological signatures

The identification of targets for candidate molecules is a pivotal stride in the drug development journey, encompassing lead discovery, drug repurposing, and the scrutiny of potential off-target or side effects. Consequently, enhancing the precision of target prediction has significant implications. Moreover, current target prediction methods primarily rely on the principle of ligand-based chemical similarity, lacking the capture of novel compound-target relationships based on ligand high-level characterization similarity. Therefore, in this context, we introduce a pioneering algorithm known as the Fused Multiple Biological Signatures (FMBS) strategy. This approach leverages a Bayesian framework to amalgamate 25 predictable biological space characterizations of molecules to predict novel targets through scaffold hopping, thereby improving target prediction accuracy and providing a versatile tool for a wide range of small-molecule target prediction. When juxtaposed with alternative target prediction methods, FMBS showcases notable efficacy, outperforming traditional descriptors. Through an analysis of scaffold hopping cases, we elucidate how FMBS attains heightened accuracy by assimilating comprehensive and complementary high-dimensional signatures, thereby underscoring its potential in unearthing novel compound-target relationships. The findings underscore that our approach adeptly pinpoints promising candidate targets, thereby expediting drug mechanism exploration through the integration of multiple high-level characterizations.

Network pharmacology and molecular docking analysis predict the mechanisms of Huangbai liniment in treating oral lichen planus

This study explored the mechanism of Huangbai liniment (HB) for the treatment of oral lichen planus (OLP) through network pharmacology and molecular docking techniques. The study identified HB' active ingredients, therapeutic targets for OLP, and associated signaling pathways. The chemical composition of HB was screened using the HERB database. The disease targets of OLP were obtained through the GeneCards and OMIM databases. A protein-protein interactions network was constructed with the String platform. Topological analysis was performed using Cytoscape software to identify core targets. Gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analysis were performed using the Hiplot database, and the active ingredients and core targets were verified by molecular docking. Date analysis showed that the active composition of HB in the treatment of OLP were quercetin, wogonin, kaempferol, and luteolin. This survey identified 10 potential therapeutic targets, including TNF, CXCL8, IL-6, IL1B, PIK3R1, ESR1, JUN, AKT1, PIK3CA, and CTNNB1. Molecular docking revealed stable interactions between OLP' key targets and HB. These key targets were predominantly involved in the PI3K-Akt signaling pathway, AGE-RAGE signaling pathway, TNF signaling pathway, and HIF-1 signaling pathway. HB plays a crucial role in the treatment of OLP, acting on multiple targets and pathways, particularly the PI3K-Akt signaling pathway. It regulated biological processes like the proliferation of epithelial cells and lymphocytes and mediates the expression of transcription factors, cytokines, and chemokines. Therefore, this study provides a theoretical basis for the clinical trial and application of HB in the therapy of OLP.

Leonurus japonicus Houtt. modulates neuronal apoptosis in intracerebral hemorrhage: Insights from network pharmacology and molecular docking

ETHNOPHARMACOLOGICAL RELEVANCE

Leonurus japonicus Houtt. (Labiatae), commonly known as Chinese motherwort, is a herbaceous flowering plant that is native to Asia. It is widely acknowledged in traditional medicine for its diuretic, hypoglycemic, antiepileptic properties and neuroprotection. Currently, Leonurus japonicus (Leo) is included in the Pharmacopoeia of the People's Republic of China. Traditional Chinese Medicine (TCM) recognizes Leo for its myriad pharmacological attributes, but its efficacy against ICH-induced neuronal apoptosis is unclear.

AIMS OF THE STUDY

This study aimed to identify the potential targets and regulatory mechanisms of Leo in alleviating neuronal apoptosis after ICH.

MATERIALS AND METHODS

The study employed network pharmacology, UPLC-Q-TOF-MS technique, molecular docking, pharmacodynamic studies, western blotting, and immunofluorescence techniques to explore its potential mechanisms.

RESULTS

Leo was found to assist hematoma absorption, thus improving the neurological outlook in an ICH mouse model. Importantly, molecular docking highlighted JAK as Leo's potential therapeutic target in ICH scenarios. Further experimental evidence demonstrated that Leo adjusts JAK1 and STAT1 phosphorylation, curbing Bax while augmenting Bcl-2 expression.

CONCLUSION

Leo showcases potential in mitigating neuronal apoptosis post-ICH, predominantly via the JAK/STAT mechanism.

Novel drug discovery: Advancing Alzheimer's therapy through machine learning and network pharmacology

Alzheimer's disease (AD), marked by tau tangles and amyloid-beta plaques, leads to cognitive decline. Despite extensive research, its complex etiology remains elusive, necessitating new treatments. This study utilized machine learning (ML) to analyze compounds with neuroprotective potential. This approach exposed the disease's complexity and identified important proteins, namely MTOR and BCL2, as central to the pathogenic network of AD. MTOR regulates neuronal autophagy and survival, whereas BCL2 regulates apoptosis, both of which are disrupted in AD. The identified compounds, including Armepavine, Oprea1_264702,1-cyclopropyl-7-fluoro-8-methoxy-4-oxoquinoline-3-carboxylic acid,(2S)-4'-Hydroxy-5,7,3'-trimethoxyflavan,Oprea1_130514,Sativanone,5-hydroxy-7,8-dimethoxyflavanone,7,4'-Dihydroxy-8,3'-dimethoxyflavanone,N,1-dicyclopropyl-6,Difluoro-Methoxy-Gatifloxacin,6,8-difluoro-1-(2-fluoroethyl),1-ethyl-6-fluoro-7-(4-methylpiperidin-1-yl),Avicenol C, demonstrated potential modulatory effects on these proteins. The potential for synergistic effects of these drugs in treating AD has been revealed via network pharmacology. By targeting numerous proteins at once, these chemicals may provide a more comprehensive therapeutic approach, addressing many aspects of AD's complex pathophysiology. A Molecular docking, dynamic simulation, and Principle Component Analysis have confirmed these drugs' efficacy by establishing substantial binding affinities and interactions with important proteins such as MTOR and BCL2. This evidence implies that various compounds may interact within the AD pathological framework, providing a sophisticated and multifaceted therapy strategy. In conclusion, our study establishes a solid foundation for the use of these drugs in AD therapy. Thus current study highlights the possibility of multi-targeted, synergistic therapeutic approaches in addressing the complex pathophysiology of AD by integrating machine learning, network pharmacology, and molecular docking simulations. This holistic technique not only advances drug development but also opens up new avenues for developing more effective treatments for this difficult and widespread disease.

Olanzapine manipulates neuroactive signals and may onset metabolic disturbances

Olanzapine is one of the most prescribed atypical antipsychotics to treat psychiatric illness and is associated with weight gain and metabolic disturbance. The present study investigated the olanzapine-regulated metabolic pathways using functional enrichent analysis including binding affinity with G-protein-coupled receptors (GPCRs). Proteins modulated by olanzapine were retrieved from SwissTargetPrediction, DIGEP-Pred, and BindingDB and then enriched in Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) to assess molecular function, biological process, and cellular components including Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. We used homology modeling to improve the 3D structure for GPCR synapse proteins including dopamine, serotonin, muscarinic, and histamine receptors which were then optimized using molecular dynamics (MD) simulations. The protein-olanzapine binding mechanisms for different GPCR binders were evaluated using molecular docking; later refined by MD simulations. Binding mechanism of olanzapine with D2, 5HT1A, 5HT2A, 5HT2B, 5HT2C, M1, and M2 receptors were created using homology modeling and optimized using MD simulations. In target identification, it was observed that olanzapine majority targeted G-protein coupled receptors. Further, enrichment analysis identified around 76% of the total genes regulated in molecular function, biological process, and cellular components were common including KEGG pathways. Moreover, it was observed that olanzapine had a major potency over the neurotransmitter synapse including neuroactive signals . Olanzapine-induced weight gain and metabolic alterations could be due to the deregulation of multiple synapses like dopamine, serotonin, muscarinic, and histamine at the feeding center followed by cGMP-PKG, cAMP, and PI3K-Akt signaling pathways. HIGHLIGHTSOlanzapine is used in the management of psychiatric illnesses.Olanzapine causes disturbance in lipids and glucosehomeostasis and manipulates energy expenditure.Olanzapine-induced weight gain may occur due to the deregulation of the multiple synapse and cGMP-PKG, cAMP, and PI3K-Akt signaling pathwayCommunicated by Ramaswamy H. Sarma.

Ultra-high-performance liquid chromatography-quadrupole time-of-flight-mass spectrometry-characterized extract of Aerides odorata Lour alleviates paracetamol-induced hepatotoxicity in animal model evidenced by biochemical, molecular, and computational studies

BACKGROUND

Many kinds of orchids have significant health benefits although adequate research on their biological functions is yet to be carried out. This study investigated the paracetamol-induced liver damage-protecting effect of epiphytic Aerides odorata methanol extract (AODE).

METHODS

The protective effects of AODE were studied by analyzing its effect on liver function parameters, messenger RNA (mRNA) expression, and tissue histopathological architecture. The results were confirmed by ligand-receptor interaction of molecular docking and multitarget interaction of network pharmacological analyses.

RESULTS

AODE significantly (p < 0.05) minimized the dose-dependent increase in acid phosphatase, aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, γ-glutamyl transferase, lactate dehydrogenase, and total bilirubin compared to the reference drug silymarin. Malondialdehyde level decreased, and the antioxidant genes catalase (CAT), superoxide dismutase (SOD), β-actin, paraoxonase-1 (PON1), and phosphofructokinase-1 (PFK-1) were upregulated in AODE-treated paracetamol-intoxicated rats. A total of 376 compounds comprising phenols and flavonoids were identified using ultra-high-performance liquid chromatography-quadrupole time-of-flight-mass spectrometry (UPLC-qTOF-MS). The online toxicity assessment using SwissADME and admetSAR exhibited drug-like, nontoxic, and potential pharmacological properties. Additionally, in silico analysis showed that isoacteoside, one of the identified compounds, exhibited the best docking score (-11.42) with the liver protein human pituitary adenylate cyclase-1 (Protein Data Bank ID: 3N94). Furthermore, network pharmacology analysis identified the top 10 hub genes, namely AKT1 (protein kinase B), CTNNB1 (catenin beta-1), SRC (proto-oncogene c-Src), TNF (tumor necrosis factor), EGFR (epidermal growth factor receptor), HSP90AA1 (heat shock protein 90α), MAPK3 (mitogen-activated protein kinase 3), STAT3 (signal transducer and activator of transcription 3), CASP3 (caspase protein), and ESR1 (estrogen receptor 1), which are responsible for hepatoprotective activity.

CONCLUSION

The findings demonstrate that AODE could be a novel hepatoprotective target in drug-induced liver damage with a further single compound-based animal study.

Exploring the active components and potential mechanisms of Alpiniae oxyphyllae Fructus in treating diabetes mellitus with depression by UPLC-Q-Exactive Orbitrap/MS, network pharmacology and molecular docking

The growing incidence of diabetes mellitus (DM) and depression is a global public health issue. Alpiniae oxyphyllae Fructus (AOF) is a kind of medicinal and edible plant which be found with anti-diabetic property, and could improve depression-like symptoms. This study aimed to screen active targets and potential mechanisms of AOF in treating DM with depression. Injection of streptozotocin (STZ) and exposure to chronic unpredictable mild stress (CUMS) for 4 weeks were used to conduct the DM with depression mice model. Behavioral tests, indexes of glucose metabolism, monoamine neurotransmitters, inflammatory cytokine and oxidative stress were measured. Histopathological change of hippocampus tissue was observing by HE and Nissl staining. UPLC-Q-Exactive Orbitrap/MS, network pharmacology and molecular docking were used to explore the chemical components and mechanisms of AOF on the DM with depression. AOF showed a reversed effect on body weight in DM with depression mice. Glucose metabolism and insulin resistance could be improved by treatment of AOF. In addition, AOF could alleviate depression-like behaviors based on the results of behavior tests and monoamine neurotransmitters. AOF also attenuated STZ-CUMS induced neuron injury in hippocampus. Next, a total of 61 chemical components were identified in the UPLC-Q-Exactive Orbitrap/MS analysis of the extract of AOF. Network pharmacology analysis suggested that 12 active components and 227 targets were screened from AOF, and 1802 target genes were screened from DM with depression, finally 126 intersection target genes were obtained. Drug-disease targets network was constructed and implied that the top five components with a higher degree value includes quercetin, nootkatone, baicalein, (-)-epicatechin and nootkatol. Protein-protein interaction (PPI) network showed that MAPK1, FOS, AKT1, IL6 and TP53 may be the core intersection targets. The mechanism of the effect of AOF on DM with depression was analyzed through gene ontology (GO), and kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, mainly involved in AGE/RAGE, PI3K/AKT, and MAPK signaling pathways. The results of molecular docking indicated that quercetin, nootkatone, baicalein, (-)-epicatechin and nootkatol all had good binding to the core intersection targets. Overall, our experimental researches have demonstrated that AOF could exert the dual effects of anti-diabetic and anti-depression on DM with depression mice, through multi-targets and multi-pathways.

Artificial intelligence for small molecule anticancer drug discovery

INTRODUCTION

The transition from conventional cytotoxic chemotherapy to targeted cancer therapy with small-molecule anticancer drugs has enhanced treatment outcomes. This approach, which now dominates cancer treatment, has its advantages. Despite the regulatory approval of several targeted molecules for clinical use, challenges such as low response rates and drug resistance still persist. Conventional drug discovery methods are costly and time-consuming, necessitating more efficient approaches. The rise of artificial intelligence (AI) and access to large-scale datasets have revolutionized the field of small-molecule cancer drug discovery. Machine learning (ML), particularly deep learning (DL) techniques, enables the rapid identification and development of novel anticancer agents by analyzing vast amounts of genomic, proteomic, and imaging data to uncover hidden patterns and relationships.

AREA COVERED

In this review, the authors explore the important landmarks in the history of AI-driven drug discovery. They also highlight various applications in small-molecule cancer drug discovery, outline the challenges faced, and provide insights for future research.

EXPERT OPINION

The advent of big data has allowed AI to penetrate and enable innovations in almost every stage of medicine discovery, transforming the landscape of oncology research through the development of state-of-the-art algorithms and models. Despite challenges in data quality, model interpretability, and technical limitations, advancements promise breakthroughs in personalized and precision oncology, revolutionizing future cancer management.

Bioinformatics and In Vitro Study Reveal ERα as The Potential Target Gene of Honokiol to Enhance Trastuzumab Sensitivity in HER2+ Trastuzumab-Resistant Breast Cancer Cells

Trastuzumab resistance presents a significant challenge in the treatment of HER2+ breast cancer, necessitating the investigation of combination therapies to overcome this resistance. Honokiol, a compound with broad anticancer activity, has shown promise in this regard. This study aims to discover the effect of honokiol in increasing trastuzumab sensitivity in HER2+ trastuzumab-resistant breast cancer cells HCC1954 and the underline mechanisms behind. A bioinformatics study performed to explore the most potential target hub gene for honokiol in HER2+ breast cancer. Honokiol, trastuzumab and combined treatment cytotoxicity activity was then evaluated in both parental HCC1954 and trastuzumab resistance (TR-HCC1954) cells using MTT assay. The expression levels of these hub genes were then analyzed using qRT-PCR and those that could not be analyzed were subjected to molecular docking to determine their potential. Honokiol showed a potent cytotoxicity activity with an IC50 of 41.05 μM and 69.61 μM in parental HCC1954 and TR-HCC1954 cell line respectively. Furthermore, the combination of honokiol and trastuzumab resulted in significant differences in cytotoxicity in TR-HCC1954 cells at specific concentrations. Molecular docking and the qRT-PCR showed that the potential ERα identified from the bioinformatics analysis was affected by the treatment. Our results show that honokiol has the potential to increase the sensitivity of trastuzumab in HER2+ trastuzumab resistant breast cancer cell line HCC1954 by affecting regulating estrogen receptor signaling. Further research is necessary to validate these findings.

Naringin and temozolomide combination suppressed the growth of glioblastoma cells by promoting cell apoptosis: network pharmacology, in-vitro assays and metabolomics based study

Introduction: Glioblastoma, which affects a large number of patients every year and has an average overall lifespan of around 14.6 months following diagnosis stands out as the most lethal primary invasive brain tumor. Currently, surgery, radiation, and chemotherapy with temozolomide (TMZ) are the three major clinical treatment approaches. However, the ability to treat patients effectively is usually limited by TMZ resistance. Naringin, a bioflavonoid with anti-cancer, antioxidant, metal-chelating, and lipid-lowering effects, has emerged as a promising therapeutic option. Methods: To explore the targets and pathways of naringin and TMZ in glioblastoma network pharmacology, cell line-based ELISA, flow cytometry, immunocytochemistry, western blotting, and LC-HRMS based metabolomics study were used. Results: The findings through the network pharmacology suggested that the key targets of naringin in the chemosensitization of glioblastoma would be Poly [ADP-ribose] polymerase 1 (PARP-1), O-6-Methylguanine-DNA Methyltransferase (MGMT), and caspases. The functional enrichment analysis revealed that these targets were significantly enriched in important pathways such as p53 signaling, apoptosis, and DNA sensing. Further, the results of the in-vitro study in U87-MG and T98-G glioblastoma cells demonstrated that TMZ and naringin together significantly reduced the percentage of viability and inhibited the DNA repair enzymes PARP-1 and MGMT, and PI3K/AKT which led to chemosensitization and, in turn, induced apoptosis, which was indicated by increased p53, caspase-3 expression and decreased Bcl2 expression. Additionally, a metabolomics study in T98-G glioblastoma cells using liquid chromatography high-resolution mass spectrometry (LC-HRMS) revealed downregulation of C8-Carnitine (-2.79), L-Hexanoylcarnitine (-4.46), DL-Carnitine (-2.46), Acetyl-L-carnitine (-3.12), Adenine (-1.3), Choline (-2.07), Propionylcarnitine (-1.69), Creatine (-1.33), Adenosine (-0.84), Spermine (-1.42), and upregulation of Palmitic Acid (+1.03) and Sphingosine (+0.89) in the naringin and TMZ treatment groups. Discussion: In conclusion, it can be said that naringin in combination with TMZ chemosensitized TMZ antiglioma response and induced apoptosis in tumor cells.

Deciphering the Anticancer Arsenal of Piper longum: Network Pharmacology and Molecular Docking Unveil Phytochemical Targets Against Lung Cancer

Introduction: Lung cancer, characterized by uncontrolled cellular proliferation within the lung tissues, is the predominant cause of cancer-related fatalities worldwide. The traditional medicinal herb Piper longum has emerged as a significant contender in oncological research because of its documented anticancer attributes, suggesting its potential for novel therapeutic development. Methods: This study adopted network pharmacology and omics methodology to elucidate the anti-lung cancer potential of P. longum by identifying its bioactive constituents and their corresponding molecular targets. Results: Through a comprehensive literature review and the Integrated Medicinal Plant Phytochemistry and Therapeutics database (IMPPAT), we identified 33 bioactive molecules from P. longum. Subsequent analyses employing tools such as SwissTargetPrediction, SuperPred, and DIGEP-Pred facilitated the isolation of 676 potential targets, among which 72 intersected with 666 lung cancer-associated genetic markers identified through databases including the Therapeutic Target Database (TTD), Online Mendelian Inheritance in Man (OMIM), and GeneCards. Further validation through protein-protein interaction (PPI) networks, gene ontology, pathway analyses, boxplots, and overall survival metrics underscored the therapeutic potential of compounds such as 7-epi-eudesm-4(15)-ene-1β, demethoxypiplartine, methyl 3,4,5-trimethoxycinnamate, 6-alpha-diol, and aristolodione. Notably, our findings reaffirm the relevance of lung cancer genes, such as CTNNB1, STAT3, HIF1A, HSP90AA1, and ERBB2, integral to various cellular processes and pivotal in cancer genesis and advancement. Molecular docking assessments revealed pronounced affinity between 6-alpha-diol and HIF1A, underscoring their potential as therapeutic agents for lung cancer. Conclusion: This study not only highlights the bioactive compounds of P. longum but also reinforces the molecular underpinnings of its anticancer mechanism, paving the way for future lung cancer therapeutics.

Combining In Vitro, In Vivo, and Network Pharmacology Assays to Identify Targets and Molecular Mechanisms of Spirulina-Derived Biomolecules against Breast Cancer

The current research employed an animal model of 7,12-dimethylbenz(a)anthracene (DMBA)-induced mammary gland carcinogenesis. The estrogen receptor-positive human breast adenocarcinoma cell line (MCF-7) was used for in vitro analysis. This was combined with a network pharmacology-based approach to assess the anticancer properties of Spirulina (SP) extract and understand its molecular mechanisms. The results showed that the administration of 1 g/kg of SP increased the antioxidant activity by raising levels of catalase (CAT) and superoxide dismutase (SOD), while decreasing the levels of malonaldehyde (MDA) and protein carbonyl. A histological examination revealed reduced tumor occurrence, decreased estrogen receptor expression, suppressed cell proliferation, and promoted apoptosis in SP protected animals. In addition, SP disrupted the G2/M phase of the MCF-7 cell cycle, inducing apoptosis and reactive oxygen species (ROS) accumulation. It also enhanced intrinsic apoptosis in MCF-7 cells by upregulating cytochrome c, Bax, caspase-8, caspase-9, and caspase-7 proteins, while downregulating Bcl-2 production. The main compounds identified in the LC-MS/MS study of SP were 7-hydroxycoumarin derivatives of cinnamic acid, hinokinin, valeric acid, and α-linolenic acid. These substances specifically targeted three important proteins: ERK1/2 MAPK, PI3K-protein kinase B (AKT), and the epidermal growth factor receptor (EGFR). Network analysis and molecular docking indicated a significant binding affinity between SP and these proteins. This was verified by Western blot analysis that revealed decreased protein levels of p-EGFR, p-ERK1/2, and p-AKT following SP administration. SP was finally reported to suppress MCF-7 cell growth and induce apoptosis by modulating the PI3K/AKT/EGFR and MAPK signaling pathways suggesting EGFR as a potential target of SP in breast cancer (BC) treatment.

Network pharmacology analysis and molecular mechanism of paeoniflorin and its metabolite in prolactinoma cells

Prolactinoma was the most common functional pituitary neuroendocrine tumor tissue type, which was caused by excessive proliferation of pituitary prolactin (PRL) cells. Drug therapy of dopamine receptor agonists was generally considered as the prior treatment for prolactinoma patients. However, there were still prolactinoma patients who were resistant to dopamine agonists. Studies have been reported that paeoniflorin can inhibit the secretion of PRL in prolactinoma cells lacking dopamine D2 receptor (D2R) expression, and paeoniflorin can be metabolized into albiflorin by intestinal flora in rats. The effect of albiflorin on prolactinoma has not been reported yet. In this study, network pharmacology was used to analyze the mechanism of paeoniflorin and its metabolite albiflorin as multi-target therapy for prolactinoma, and the experimental verification was carried out. In order to clarify the complex relationship among paeoniflorin, albiflorin and prolactinoma, we constructed a component-target-disease network, and further constructed interaction network, MMP9, EGFR, FGF2, FGFR1 and LGALS3 were screened as the core targets. Kyoto encyclopedia of genes and genomes (KEGG) analysis showed that paeoniflorin and albiflorin may be involved in various pathways in the treatment of prolactinoma, included relaxin signaling pathway and PI3K-Akt signaling pathway. Molecular docking analysis showed that paeoniflorin and albiflorin had good binding activity with MMP9. Western blotting results showed that paeoniflorin and albiflorin could significantly reduce the expression of MMP9, and ELISA results showed that paeoniflorin and albiflorin could significantly reduce the concentration of PRL in GH3 cells, and the reduce degree of albiflorin was stronger than paeoniflorin at 50 μM, which indicated that albiflorin might be a potential drug to treat prolactinoma, which can regulate prolactinoma through MMP9 and reduce the concentration of PRL. Our study provided a new therapeutic strategy for prolactinoma.

Synthesis and Structure of Novel Phenothiazine Derivatives, and Compound Prioritization via In Silico Target Search and Screening for Cytotoxic and Cholinesterase Modulatory Activities in Liver Cancer Cells and In Vivo in Zebrafish

Phenothiazines (PTZ) are antipsychotics known to modulate a variety of neurotransmitter activities that include dopaminergic and cholinergic signaling and have been identified as potential anticancer agents in vitro. However, it is important to also test whether a highly cytotoxic, repurposed, or novel PTZ has low toxicity and neuromodulatory activity in vivo using vertebrate model organisms, such as zebrafish. In this study, we synthesized novel phenothiazines and screened them in vitro in liver cancer and in vivo in zebrafish embryos/larvae. The syntheses of several intermediate PTZ 10-yl acyl chlorides were followed by elemental analysis and determination of 1H NMR and 13C NMR mass (ESI+) spectra of a large number of novel PTZ 10-carboxamides. Cytotoxicities of 28 PTZ derivatives (1-28) screened against Hep3B and SkHep1 liver cancer cell lines revealed five intermediate and five novel leads along with trifluoperazine (TFP), prochlorperazine (PCP), and perphenazine, which are relatively more cytotoxic than the basic PTZ core. Overall, the derivatives were more cytotoxic to Hep3B than SkHep1 cells. Moreover, in silico target screening identified cholinesterases as some of the commonest targets of the screened phenothiazines. Interestingly, molecular docking studies with acetylcholinesterase (AChE) and butyrylcholinesterase proteins showed that the most cytotoxic compounds 1, 3, PCP, and TFP behaved similar to Huprin W in their amino acid interactions with the AChE protein. The highly cytotoxic intermediate PTZ derivative 1 exhibited a relatively lower toxicity profile than those of 2 and 3 during the zebrafish development. It also modulated in vivo the cholinesterase activity in a dose-dependent manner while significantly increasing the total cholinesterase activity and/or ACHE mRNA levels, independent of the liver cancer cell type. Our screen also identified novel phenothiazines, i.e., 8 and 10, with significant cytotoxic and cholinesterase modulatory effects in liver cancer cells; yet both compounds had low levels of toxicity in zebrafish. Moreover, they modulated the cholinesterase activity or expression of ACHE in a cancer cell line-specific manner, and compound 10 significantly inhibited the cholinesterase activity in zebrafish. Accordingly, using a successful combination of in silico, in vitro, and in vivo approaches, we identified several lead anticancer and cholinesterase modulatory PTZ derivatives for future research.

The active components of Erzhi wan and their anti-Alzheimer's disease mechanisms determined by an integrative approach of network pharmacology, bioinformatics, molecular docking, and molecular dynamics simulation

Erzhi Wan (EZW), a classic Traditional Chinese Medicine formula, has shown promise as a potential therapeutic option for Alzheimer's disease (AD), yet its mechanism remains elusive. Herein, we employed an integrative in-silico approach to investigate the active components and their mechanisms against AD. We screened four active components with blood-brain barrier permeabilities from TCMSP, along with 307 corresponding targets predicted by SwissTargetPrediction, PharmMapper, and TCMbank websites. Then, we retrieved 2260 AD-related targets from Genecards, OMIM, and NCBI databases. Furthermore, we constructed the protein-protein interaction (PPI) network of the intersected targets via the STRING database and performed the GO and KEGG enrichment analyses using the "clusterProfiler" R package. The results showed that the intersected targets were intimately related to the p53/PI3K/Akt signaling pathway, serotonergic synapse, and response to oxygen level. Subsequently, 25 core targets were found differentially expressed in brain regions by bioinformatics analyses of GEO datasets of clinical samples from the Alzdata database. The binding sites and stabilities between the active components and the core targets were investigated by the molecular docking approach using Autodock 4.2.6 software, followed by pocket detection and druggability assessment via the DoGSiteScorer server. The results showed that acacetin, β-sitosterol, and 3-O-acetyldammarenediol-II strongly interacted with the druggable pockets of AR, CASP8, POLB, and PREP. Eventually, the docking results were further cross-referenced with the literature research and validated by 100 ns of molecular dynamics simulations using GROMACS software. Binding free energies were calculated via MM/PBSA strategy combined with interaction entropy. The simulation results indicated stable bindings between four docking pairs including acacetin-AR, acacetin-CASP8, β-sitosterol-POLB, and 3-O-acetyldammarenediol-II-PREP. Overall, our study demonstrated a theoretical basis for how three active components of EZW confer efficacy against AD. It provides a promising reference for subsequent research regarding drug discoveries and clinical applications.

Network pharmacology: an efficient but underutilized approach in oral, head and neck cancer therapy-a review

The application of network pharmacology (NP) has advanced our understanding of the complex molecular mechanisms underlying diseases, including neck, head, and oral cancers, as well as thyroid carcinoma. This review aimed to explore the therapeutic potential of natural network pharmacology using compounds and traditional Chinese medicines for combating these malignancies. NP serves as a pivotal tool that provides a comprehensive view of the interactions among compounds, genes, and diseases, thereby contributing to the advancement of disease treatment and management. In parallel, this review discusses the significance of publicly accessible databases in the identification of oral, head, and neck cancer-specific genes. These databases, including those for head and neck oral cancer, head and neck cancer, oral cancer, and genomic variants of oral cancer, offer valuable insights into the genes, miRNAs, drugs, and genetic variations associated with these cancers. They serve as indispensable resources for researchers, clinicians, and drug developers, contributing to the pursuit of precision medicine and improved treatment of these challenging malignancies. In summary, advancements in NP could improve the globalization and modernization of traditional medicines and prognostic targets as well as aid in the development of innovative drugs. Furthermore, this review will be an eye-opener for researchers working on drug development from traditional medicines by applying NP approaches.

Molecular Mechanism of Cynodon dactylon Phytosterols Targeting MAPK3 and PARP1 to Combat Epithelial Ovarian Cancer: A Multifaceted Computational Approach

Epithelial Ovarian Cancer (EOC) presents a global health concern, necessitating the development of innovative therapeutic strategies to combat its impact. This study was employed to investigate the unexplored therapeutic efficacy of Cynodon dactylon phytochemicals against EOC using a multifaceted computational approach. A total of 19 out of 89 rigorously curated phytochemicals were assessed as potential drug targets via ADMET profiling, while protein-protein interaction analysis scrutinized the top 20 hub genes among 264 disease targets, revealing their involvement in cancer-related pathways and underscoring their significance in EOC pathogenesis. In molecular docking, Stigmasterol acetate showed the highest binding affinity (-10.9 kcal/mol) with Poly [ADP-ribose] polymerase-1 (PDB: 1UK1), while Arundoin and Beta-Sitosterol exhibited strong affinities (-10.4 kcal/mol and -10.1 kcal/mol, respectively); additionally, Beta-Sitosterol interacting with Mitogen-activated protein kinase 3 (PDB: 4QTB) showed a binding affinity of -10.1 kcal/mol, forming 2 hydrogen bonds and a total of 10 bonds with 10 residues. Molecular dynamics simulations exhibited the significant structural stability of the Beta-Sitosterol-4QTB complex with superior binding free energy (-36.61 kcal/mol) among the three complexes. This study identified C. dactylon phytosterols, particularly Beta-Sitosterol, as effective in targeting MAPK3 and PARP1 to combat EOC, laying the groundwork for further experimental validation and drug development efforts.

Exploring putative drug properties associated with TNF-alpha inhibition and identification of potential targets in cardiovascular disease using machine learning-assisted QSAR modeling and virtual reverse pharmacology approach

Cardiovascular disease is a chronic inflammatory disease with high mortality rates. TNF-alpha is pro-inflammatory and associated with the disease, but current medications have adverse effects. Therefore, efficient inhibitors are urgently needed as alternatives. This study represents a structural-activity relationship investigation of TNF-alpha, curated from the ChEMBL database. Exploratory data analysis was performed to visualize the physicochemical properties of different bioactivity groups. The extracted molecules were subjected to PubChem and SubStructure fingerprints, and a QSAR-based Random Forest (QSAR-RF) model was generated using the WEKA tool. The QSAR random Forest model was built based on the SubStructure fingerprint with a correlation coefficient of 0.992 and 0.716 as the respective tenfold cross-validation scores. The variance important plot (VIP) method was used to extract the important features for TNF-alpha inhibition. The Substructure-based QSAR-RF (SS-QSAR-RF) model was validated using molecules from PubChem and ZINC databases. The generated model also predicts the pIC50 value of the molecules selected from the docking study followed by molecular dynamic simulation with the time step of 100 ns. Through virtual reverse pharmacology, we determined the main drug targets from the top four hit compounds obtained via molecular docking study. Our analysis included an integrated bioinformatics approach to pinpoint crucial targets like EGRF, HSP900A1, STAT3, PSEN1, AKT1, and MDM2. Further, GO and KEGG pathways analysis identified relevant cardiovascular disease-related pathways for the hub gene involved. However, this study provides valuable insights, it is important to note that it lacks experimental application. Future research may benefit from conducting in-vitro and in-vivo studies.

Copper transporter protein (MctB) as a therapeutic target to elicit antimycobacterial activity against tuberculosis

Tuberculosis (TB) is a prehistoric infection and major etiologic agent of TB, Mycobacterium tuberculosis, which is considered to have advanced from an early progenitor species found in Eastern Africa. By the 1800s, there were approximately 800 to 1000 fatality case reports per 100,000 people in Europe and North America. This research suggests an In-silico study to identify potential inhibitory compounds for the target Mycobacterial copper transport protein (Mctb). ADME-based virtual screening, molecular docking, and molecular dynamics simulations were conducted to find promising compounds to modulate the function of the target protein. Four chemical compounds, namely Anti-MCT1, Anti-MCT2, Anti-MCT3 and Anti-MCT4 out of 1500 small molecules from the Diverse-lib of MTiOpenScreen were observed to completely satisfy Lipinski rule of five and Veber's rule. Further, significantly steady interactions with the MctB target protein were observed. Docking experiments have presented 9 compounds with less than -9.0 kcal/mol free binding energies and further MD simulation eventually gave 4 compounds having potential interactions and affinity with target protein and favorable binding energy ranging from -9.2 to -9.3 kcal/mol. We may propose these compounds as an effective candidate to reduce the growth of M. tuberculosis and may also assist present a novel therapeutic approach for Tuberculosis. In vivo and In vitro validation would be needed to proceed further in this direction.Communicated by Ramaswamy H. Sarma.

Icariside II in NSCLC and COVID-19: Network pharmacology and molecular docking study

BACKGROUND

Patients with non-small cell lung cancer (NSCLC) are susceptible to coronavirus disease-2019 (COVID-19), but current treatments are limited. Icariside II (IS), a flavonoid compound derived from the plant epimedin, showed anti-cancer,anti-inflammation and immunoregulation effects. The present study aimed to evaluate the possible effect and underlying mechanisms of IS on NSCLC patients with COVID-19 (NSCLC/COVID-19).

METHODS

NSCLC/COVID-19 targets were defined as the common targets of NSCLC (collected from The Cancer Genome Atlas database) and COVID-19 targets (collected from disease database of Genecards, OMIM, and NCBI). The correlations of NSCLC/COVID-19 targets and survival rates in patients with NSCLC were analyzed using the survival R package. Prognostic analyses were performed using univariate and multivariate Cox proportional hazards regression models. Furthermore, the targets in IS treatment of NSCLC/COVID-19 were defined as the overlapping targets of IS (predicted from drug database of TMSCP, HERBs, SwissTarget Prediction) and NSCLC/COVID-19 targets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis of these treatment targets were performed aiming to understand the biological process, cellular component, molecular function and signaling pathway. The hub targets were analyzed by a protein-protein interaction network and the binding capacity with IS was characterized by molecular docking.

RESULTS

The hub targets for IS in the treatment of NSCLC/COVID-19 includes F2, SELE, MMP1, MMP2, AGTR1 and AGTR2, and the molecular docking results showed that the above target proteins had a good binding degree to IS. Network pharmacology showed that IS might affect the leucocytes migration, inflammation response and active oxygen species metabolic process, as well as regulate the interleukin-17, tumor necrosus factor and hypoxia-inducible factor-1 signaling pathway in NSCLC/COVID-19.

CONCLUSIONS

IS may enhance the therapeutic efficacy of current clinical anti-inflammatory and anti-cancer therapy to benefit patients with NSCLC combined with COVID-19.

A novel bioinformatics strategy to uncover the active ingredients and molecular mechanisms of Bai Shao in the treatment of non-alcoholic fatty liver disease

Introduction: As a new discipline, network pharmacology has been widely used to disclose the material basis and mechanism of Traditional Chinese Medicine in recent years. However, numerous researches indicated that the material basis of TCMs identified based on network pharmacology was the mixtures of beneficial and harmful substances rather than the real material basis. In this work, taking the anti-NAFLD (non-alcoholic fatty liver disease) effect of Bai Shao (BS) as a case, we attempted to propose a novel bioinformatics strategy to uncover the material basis and mechanism of TCMs in a precise manner. Methods: In our previous studies, we have done a lot work to explore TCM-induced hepatoprotection. Here, by integrating our previous studies, we developed a novel computational pharmacology method to identify hepatoprotective ingredients from TCMs. Then the developed method was used to discover the material basis and mechanism of Bai Shao against Non-alcoholic fatty liver disease by combining with the techniques of molecular network, microarray data analysis, molecular docking, and molecular dynamics simulation. Finally, literature verification method was utilized to validate the findings. Results: A total of 12 ingredients were found to be associated with the anti-NAFLD effect of BS, including monoterpene glucosides, flavonoids, triterpenes, and phenolic acids. Further analysis found that IL1-β, IL6, and JUN would be the key targets. Interestingly, molecular docking and molecular dynamics simulation analysis showed that there indeed existed strong and stable binding affinity between the active ingredients and the key targets. In addition, a total of 23 NAFLD-related KEGG pathways were enriched. The major biological processes involved by these pathways including inflammation, apoptosis, lipid metabolism, and glucose metabolism. Of note, there was a great deal of evidence available in the literature to support the findings mentioned above, indicating that our method was reliable. Discussion: In summary, the contributions of this work can be summarized as two aspects as follows. Firstly, we systematically elucidated the material basis and mechanism of BS against NAFLD from multiple perspectives. These findings further enhanced the theoretical foundation of BS on NAFLD. Secondly, a novel computational pharmacology research strategy was proposed, which would assist network pharmacology to uncover the scientific connotation TCMs in a more precise manner.

In silico studies and development of a protein-based electrochemical sensor for selective and sensitive detection of aflatoxin B1

Proteins from different species have been docked with aflatoxin B1 (AFB1) and identified 3 proteins (prostaglandin-E(2)9-reductase from Oryctolagus uniculus, proto-oncogene serine/threonine-protein kinase Pim-1 and human immunoglobulin G (hIgG)) as potential candidates to develop an electrochemical sensor. Fluorescence spectroscopy experiments have confirmed the interaction of hIgG with AFB1 with an affinity constant of 4.6 × 105 M-1. As a proof-of-concept, hIgG was immobilized on carbon nanocomposite (carbon nanotube-nanofiber, CNT-F)-coated glassy carbon electrode (GCE). FT-IR spectra, HR-TEM and BCA assay have confirmed successful immobilization of hIgG on the electrode (hIgG@CNT-F/GCE). The preparation of this protein electrochemical sensor requires only 1 h 36 min, which is fast as compared with preparing an electro immunosensor. hIgG@CNT-F/GCE has displayed an excellent AFB1 limit of detection (0.1 ng/mL), commendable selectivity in the presence of two other mycotoxins (ochratoxin A and patulin) and the detection of  AFB1 in spiked peanuts and corn samples.

Phytochemical Characterization and Antioxidant Activity Evaluation for Some Plant Extracts in Conjunction with Pharmacological Mechanism Prediction: Insights into Potential Therapeutic Applications in Dyslipidemia and Obesity

Lipid metabolism dysregulation can lead to dyslipidemia and obesity, which are major causes of cardiovascular disease and associated mortality worldwide. The purpose of the study was to obtain and characterize six plant extracts (ACE-Allii cepae extractum; RSE-Rosmarini extractum; CHE-Cichorii extractum; CE-Cynarae extractum; AGE-Apii graveolentis extractum; CGE-Crataegi extractum) as promising adjuvant therapies for the prevention and treatment of dyslipidemia and its related metabolic diseases. Phytochemical screening revealed that RSE was the richest extract in total polyphenols (39.62 ± 13.16 g tannic acid/100 g dry extract) and phenolcarboxylic acids (22.05 ± 1.31 g chlorogenic acid/100 g dry extract). Moreover, the spectrophotometric chemical profile highlighted a significant concentration of flavones for CGE (5.32 ± 0.26 g rutoside/100 g dry extract), in contrast to the other extracts. UHPLC-MS quantification detected considerable amounts of phenolic constituents, especially chlorogenic acid in CGE (187.435 ± 1.96 mg/g extract) and rosmarinic acid in RSE (317.100 ± 2.70 mg/g extract). Rosemary and hawthorn extracts showed significantly stronger free radical scavenging activity compared to the other plant extracts (p < 0.05). Pearson correlation analysis and the heatmap correlation matrix indicated significant correlations between phytochemical contents and in vitro antioxidant activities. Computational studies were performed to investigate the potential anti-obesity mechanism of the studied extracts using target prediction, homology modeling, molecular docking, and molecular dynamics approaches. Our study revealed that rosmarinic acid (RA) and chlorogenic acid (CGA) can form stable complexes with the active site of carbonic anhydrase 5A by either interacting with the zinc-bound catalytic water molecule or by directly binding Zn2+. Further studies are warranted to experimentally validate the predicted CA5A inhibitory activities of RA and CGA and to investigate the hypolipidemic and antioxidant activities of the proposed plant extracts in animal models of dyslipidemia and obesity.

One-Step Synthesis, Crystallography, and Acute Toxicity of Two Boron-Carbohydrate Adducts That Induce Sedation in Mice

Boronic acids form diester bonds with cis-hydroxyl groups in carbohydrates. The formation of these adducts could impair the physical and chemical properties of precursors, even their biological activity. Two carbohydrate derivatives from d-fructose and d-arabinose and phenylboronic acid were synthesized in a straightforward one-step procedure and chemically characterized via spectroscopy and X-ray diffraction crystallography. Additionally, an acute toxicity test was performed to determine their lethal dose 50 (LD50) values by using Lorke's method. Analytical chemistry assays confirmed the formation of adducts by the generation of diester bonds with the β-d-pyranose of carbohydrates, including signals corresponding to the formation of new bonds, such as the stretching of B-O bonds. NMR spectra yielded information about the stereoselectivity in the synthesis reaction: Just one signal was found in the range for the anomeric carbon in the 13C NMR spectra of both adducts. The acute toxicity tests showed that the LD50 value for both compounds was 1265 mg/kg, while the effective dose 50 (ED50) for sedation was 531 mg/kg. However, differences were found in the onset and lapse of sedation. For example, the arabinose derivative induced sedation for more than 48 h at 600 mg/kg, while the fructose derivative induced sedation for less than 6 h at the same dose without the death of the mice. Thus, we report for the first time two boron-containing carbohydrate derivatives inducing sedation after intraperitoneal administration. They are bioactive and highly safe agents. Further biological evaluation is desirable to explore their medical applications.

Integrating Network Pharmacology and Experimental Validation to Decipher the Mechanism of Action of Astragalus-Atractylodes Herb Pair in Treating Hepatocellular Carcinoma

Purpose

Traditional Chinese medicine (TCM) therapy is an important means to treat hepatocellular carcinoma (HCC), Astragalus (Latin name: Hedysarum Multijugum Maxim; Chinese name: Huangqi, HQ) and Atractylodes (Latin name: Atractylodes Macrocephala Koidz; Chinese name: Baizhu, BZ) (HQBZ), a classic herb pair, is often used in combination to HCC. However, the main components and potential mechanisms of HQBZ therapy in HCC remain unclear. This study aimed to identify the potential active ingredients and molecular mechanisms of action of HQBZ in HCC treatment.

Methods

The HQBZ-Compound-Target-HCC network and HQBZ-HCC transcriptional regulatory network were constructed to screen the core active compound components and targets of HQBZ therapy for HCC. Molecular docking techniques are used to verify the stability of binding core active compound components to targets. GO and KEGG enrichment analysis were used to explore the signaling pathway of HQBZ in HCC treatment, the mechanism of HQBZ treatment of HCC was verified based on in vivo H22 tumor bearing mice and in vitro cell experiments.

Results

Network pharmacology and molecular docking studies showed that HQBZ treatment of HCC was related to the targeted regulation of IL-6 and STAT3 by the active compound biatractylolide, KEGG pathway enrichment analysis suggest that HQBZ may play a role in the treatment of HCC through IL-6/STAT3 signaling pathway. In vitro experiment results proved that HQBZ could regulate IL-6/STAT3 signaling pathway transduction on CD8+T cells, inhibit CD8+T cell exhaustion and restore the function of exhausted CD8+T cells. In vivo experiment results proved that HQBZ can regulate IL-6/STAT3 signaling pathway transduction in H22 liver cancer model mouse tumor tissue, increased the proportion of tumor infiltrating CD8+T cells.

Conclusion

This study found that HQBZ may play a therapeutic role in HCC by targeting IL-6 and STAT3 through biatractylolide, its mechanism of action is related to regulating IL-6/STAT3 signaling pathway, reversing T cell failure and increasing tumor infiltration CD8+T cells.

Structure and Ligand Based Virtual Screening and MPO Topological Analysis of Triazolo Thiadiazepine-fused Coumarin Derivatives as Anti-Parkinson Drug Candidates

Parkinson's disease (PD) is a debilitating condition that can cause locomotor problems in affected patients, such as tremors and body rigidity. PD therapy often includes the use of monoamine oxidase B (MAOB) inhibitors, particularly phenylhalogen compounds and coumarin-based semi-synthetic compounds. The objective of this study was to analyze the structural, pharmacokinetic, and pharmacodynamic profile of a series of Triazolo Thiadiazepine-fused Coumarin Derivatives (TDCDs) against MAOB, in comparison with the inhibitor safinamide. To achieve this goal, we utilized structure-based virtual screening techniques, including target prediction and absorption, distribution, metabolism, and excretion (ADME) prediction based on multi-parameter optimization (MPO) topological analysis, as well as ligand-based virtual screening techniques, such as docking and molecular dynamics. The findings indicate that the TDCDs exhibit structural similarity to other bioactive compounds containing coumarin and MAOB-binding azoles, which are present in the ChEMBL database. The topological analyses suggest that TDCD3 has the best ADME profile, particularly due to the alignment between low lipophilicity and high polarity. The coumarin and triazole portions make a strong contribution to this profile, resulting in a permeability with Papp estimated at 2.15 × 10-5 cm/s, indicating high cell viability. The substance is predicted to be metabolically stable. It is important to note that this is an objective evaluation based on the available data. Molecular docking simulations showed that the ligand has an affinity energy of - 8.075 kcal/mol with MAOB and interacts with biological substrate residues such as Pro102 and Phe103. The results suggest that the compound has a safe profile in relation to the MAOB model, making it a promising active ingredient for the treatment of PD.