Letters in Drug Design & Discovery - Volume 21, Issue 18, 2024

Hypertension, a major risk factor for cardiovascular disease, is often managed with antihypertensive drugs. Medicinal plants are commonly used to control hypertension, and many studies assess their antihypertensive effects using the rat mesenteric vascular bed model.

This paper aims to highlight the value of the rat mesenteric vascular bed as a pharmacological model for evaluating the vascular effects of medicinal plants with traditional antihypertensive properties.

We reviewed 55 articles published between 1980 and 2022, using Scopus, PubMed, Web of Science, and Google Scholar databases, focusing on medicinal plants studied in the rat mesenteric vascular bed. Furthermore, we conducted a computational evaluation of the main vasorelaxant phytochemicals derived from these plants.

We identified 63 species from 36 plant families evaluated in the mesenteric artery. Most of these plants showed varying degrees of vasorelaxation due to vasorelaxant phytochemicals. The mechanisms of vasorelaxation include angiotensin-converting enzyme inhibition, L-type voltage-gated calcium channel blockade, and activation of muscarinic (M3), and adrenergic (β2) receptors. These experimental findings were supported by computational studies, which confirmed the potent antihypertensive effect.

The rat mesenteric artery remains a valuable model for studying the vascular effects of plants and for developing new antihypertensive drugs.

Hepatic cancer, an aggressive tumour that often develops along with cirrhosis and chronic liver disease like infections with the hepatitis B and hepatitis C viruses, while non-alcoholic steatohepatitis, is linked to metabolic syndrome or diabetes mellitus. It is the third most prevalent cause of cancer-related mortality globally and ranks fifth in cancer incidence. According to GLOBOCON, the prevalence is expected to rise by 55.0% and the fatalities by 56.4% in the near future.

The present review offered natural plant-based substances and compounds having curative effects on liver cancer, along with novel drug delivery systems and nanocarrier-based therapies.

The literature has been taken from PubMed, Google Scholar, SciFinder, Springer Nature, Bentham Science, PLOS one, or other internet sites.

Treatment for heterogeneous malignancy is multidimensional, and care guidelines differ depending on the specialty and location. Several nutritional herbal remedies and their active phytoconstituents may have an abundance of impacts on the management of liver cancer, including preventing the growth and spread of tumor cells, shielding the body from liver carcinogens, boosting the effects of chemotherapy and immunomodulating the body.

The treatment of liver cancer involves multidisciplinary and multimodel therapy. The literature is a compilation of extract, compounds, and novel approaches like nanoparticles, microsphere, liposomes, niosomes, phytosomes and microparticles. These approaches not only manage cancer but also boost the immunity of the individuals.

Benzoinum is a traditional Chinese medicine used to treat ischemic stroke. However, the mechanism of action of benzoinum for treating ischemic stroke still remains unclear. This study aims to elucidate the mechanism of benzoinum for treating ischemic stroke based on network pharmacology and molecular docking, which will explore its key targets and provide a basis and new treatment ideas for its clinical application.

Targets associated with ischemic stroke were retrieved from the Genecards database using the keywords “Ischemic stroke” and “Cerebral ischemia.” Network pharmacology analysis was conducted, and a network diagram encompassing drugs, components, targets, and diseases was constructed. The analysis was performed using the Intelligent Network Pharmacology Platform Unique for Traditional Chinese Medicine (INPUT). PPI enrichment analysis was utilized to identify key target genes; GO and KEGG enrichment analyses were carried out to ascertain the primary biological processes, molecular functions, cellular components, and pathways involved. A target network diagram was generated to identify the most enriched targets. The interaction between compounds and targets was determined via molecular docking.

A total of 65 active ingredients from benzoinum were identified as potentially effective for the treatment of ischemic stroke. Potential active substances, oleanolic acid, 2,3,5,7-Tetrahydroxyflavone, naphthalene, eucalyptol, and benzoic acid were ranked according to their degree values. In addition, 226 targets were found to be involved in the process. The PPI topology analysis revealed that the core targets included TP53, JUN, STAT3, AKT1, PIK3CA, RELA, MAPK1, MAPK3, TNF, and CXCL8. GO enrichment analysis yielded 6807 entries, with 5589 entries in BP, 385 entries in CC, and 833 entries in MF. KEGG enrichment analysis resulted in 290 entries, primarily related to lipid and atherosclerosis, PI3K-Akt pathway, chemical carcinogenesis receptor activation, IL-17 pathway, and TNF pathway. Molecular docking also demonstrated the interactions between the principal compounds and their respective targets.

Benzoinum appears to exert therapeutic effects on ischemic stroke through multiple components, targets, and pathways, with a primary association with its anti-inflammatory properties. However, further experimental validation is recommended to more accurately define its active constituents and mechanisms of action.

Lysine-specific histone demethylase 1 (LSD1) is a well-known anti-cancer target for drug discovery. Novel reversible inhibitors of LSD1 are desirable to be developed.

This study aimed to build reliable predictive models to evaluate the antineoplastic efficacy of compounds and reveal the structural foundation underlying the inhibitory activity of LSD1.

Multiple artificial intelligence algorithms were utilized in the development of quantitative structure-activity relationship (QSAR) models. A dataset comprising 915 compounds with well-defined IC50 values against LSD1 was assembled for analysis. The structures of these compounds were described by different descriptor packages. Principal component analysis (PCA) was performed to explore the chemical space distribution of each dataset. Y-randomization test and applicability domain (AD) analysis were deployed to validate the reliability of models.

For regression models, a consensus model was constructed by integrating the predictions of four top-performing individual models (SVM_ECFP4, RFR_PyDescriptor, RFR_RDKIT, and TRANSNNI), resulting in enhanced predictive performance as compared to the individual models. The consensus model achieved a determination coefficient (r², for the test set) value of 0.82. For classification models, the consensus model was derived from the amalgamation of three individual models (ASNN_RDKIT, ASNN_ECFP4, and RFR_ECFP4), and the overall prediction accuracy of the model was 0.96 for external validation.

The reliable models could be used to identify highly active LSD1 inhibitors for the purpose of efficient virtual screening. In addition, the important molecular properties and structural fragments derived from this work can provide guidance for the structural optimization of novel LSD1 inhibitors.

Thymidine kinase 2 (TK2) is a crucial enzyme in the mitochondrial pyrimidine salvage pathway, strongly associated with several mitochondrial diseases. Current treatments frequently damage mitochondria, leading to a decrease in cellular energy output.

This study aimed to use computational approaches to identify inhibitors of TK2 that could prevent these harmful consequences.

The initial screening process entailed the application of machine learning algorithms, more particularly a Random Forest model, which was trained on 189 FDA-approved drugs and decoy datasets obtained from the DUD-E database. Its purpose was to identify potential inhibitors. The molecular docking technique was employed to evaluate the affinity of the chosen medicines towards TK2. Molecular dynamics (MD) simulations lasting 100 nanoseconds were employed to conduct additional validation by examining the dynamic interactions between the top-found compounds and TK2.

Three hit compounds (3168, 5209502, and 135402009) were identified through the screening process for their high affinity for TK2. Compound 5209502 had the most stable interaction with the lowest root-mean-square deviation (RMSD) in the molecular dynamics (MD) simulations and maintained 12 hydrogen bonds consistently. MM/GBSA computations verified that 5209502 exhibited the strongest binding affinity with a binding free energy of -62.14 kcal/mol, which was notably lower than that of the control ligand.

Compound 5209502 is a promising candidate for additional experimental evaluation because of its notable stability and great affinity for TK2. This chemical may provide a focused and less harmful treatment for mitochondrial illnesses linked to TK2 malfunction.

Enzymes belonging to the kinase family have been extensively implicated in cancer. Aurora A (AURKA) is crucial in regulating the cell cycle. AURKA's significant role in the formation of abnormal mitotic spindles and the failure of cytokinesis positions it as a promising target for anticancer treatments. Notably, AURKA is observed to be overexpressed in various cancer types, making its inhibition a compelling strategy for the development of anticancer agents.

In this study, we set out to investigate a novel de novo design strategy aimed at developing and optimizing potent inhibitors for Aurora Kinase A. Given Aurora Kinase A's critical role in cell cycle regulation and its overexpression in various cancers, it presents a promising target for therapeutic intervention. Our goal was to create a new library of compounds, building on existing inhibitors known for their selectivity and potency against Aurora Kinase A. By making strategic modifications to these lead molecules, we aimed to improve their binding affinity and inhibitory effectiveness. This research was focused on identifying and refining compounds with enhanced drug-like properties and robust inhibitory potential, contributing to the advancement of effective anticancer therapies.

A compound library based on known inhibitors having Aurora Kinase A selectivity and IC50 value in the nanomolar range was designed by modification in the lead molecules identified by analyzing the binding mode of the molecules in the catalytic site of the enzyme. A molecular docking study was performed in GOLD 2020. Drug-likeness ADME parameters (molecular weight, H-bond acceptors, H-bond donors, LogP, and the number of rotatable bonds) of designed molecules were calculated using SwissADME, pkCSM, and ProToxII web servers.

The docking study, utilizing GOLD 2020 software on Aurora Kinase A (PDB: 3W2C), successfully identified inhibitors that hindered the enzyme's activity by occupying its catalytic site. This inhibition mechanism, consistent across all cases, involves crucial interactions with residues such as Ala213, Asp274, and Phe144. A detailed analysis of the compounds guided the design of new analogs, aiming to enhance the lead compound's affinity for the receptor. Subsequent derivatization of M1 and M15 resulted in molecules (M1_46, M1_49, M1_50, M15_21, M15_14, and M15_43) showing a notable 10-15% increase in the Chemscore fitness scoring function compared to their parent molecules. This improvement correlated with a rise in the number of hydrogen bond interactions in the complexes, guiding further development.

This computational assessment lays a foundation for further in-vitro and in-vivo studies in drug development, suggesting these derivatives as promising candidates for cancer treatment.

Advances in nanotechnology have revealed innovative applications in pharmaceutical sciences to solve unmet medical needs. Over the past decades, antibiotic resistance has emerged as a global concern. This catastrophic phenomenon, with a rapid increase in frequency, indicates the urgent need for the introduction of new approaches. In this respect, as a class of inorganic nanomaterials, mesoporous silica nanoparticles (MSNs) are of interest. Amongst, MCM-41 (MCM-Mobil Composition of Matter) possesses many advantages suitable for biomedical applications such as high pore volume, large surface area capacity, and controlled release properties as well as high bioavailability.

In the current study, we aimed to develop a new drug delivery platform of ciprofloxacin (CIP) to combat antibiotic resistance practically using MSNs.

The MCM-41 nanoparticles were synthesized using surfactant as the templating agent. Afterward, drug molecules were loaded in the prepared mesoporous structure, and several experiments were conducted to assess physicochemical properties. As well, the encapsulation efficiency, release profile, and antibacterial properties were also evaluated.

The CIP-loaded MCM-41 (CIP@MCM-41) nanoparticles represented good physicochemical properties. The results of the DLS method showed a particle size of 93.73 nm with a low polydispersity index (PDI) of 0.21, while SEM imaging demonstrated spherical particles with relative shape uniformity and size distribution. The encapsulation efficacy of MCM-41 MSNs for CIP was measured to be 28.7% ± 0.37 followed by negligible changes over 60 days. The release profile of CIP from prepared nanoparticles was also demonstrated to follow the zero-order kinetic model. Moreover, CIP@MCM-41 nanoparticles exhibited high antibacterial properties against test microorganisms (Escherichia coli, Klebsiella pneumoniae, Staphylococcus epidermidis, and Micrococcus luteus).

The current formulation could be a promising candidate for the delivery of therapeutic agents to combat antibiotic resistance and promote public health.

Tuberculosis (TB) remains a significant global health concern, necessitating the exploration of novel therapeutic agents. Reported antitubercular activities of previously synthesized benzopyran and other oxygen-containing heterocycles motivate us to synthesize and evaluate the antitubercular potential of benzopyran derivatives.

The aim of this study was to combine two scaffolds; one is coumarin (benzopyran-2-one), and another one is piperazine, as both are found in anti-tubercular derivatives.

Through a four-step synthetic approach, compounds SM1-SM10 were synthesized. These derivatives were subsequently evaluated for their in vitro anti-tubercular potential using the resazurin microtiter assay (REMA), with isoniazid as the standard (MIC 0.25 to 0.5µg/mL).

Among the synthesized compounds, SM2 and SM8 demonstrated remarkable anti-tubercular activity, with MICs of 4 and 6µg/mL, respectively. Notably, these MIC values are considerable for the further development of benzopyran derivatives as potent antitubercular agents.

Outcomes underscore the potential of benzopyran derivatives as valuable assets in TB drug discovery, warranting further exploration and development.

This study aims to investigate the active ingredients and potential mechanisms of Total Flavonoids of Hippophae (TFH) in the treatment of Allergic Dermatitis (AD) using network pharmacology and molecular docking.

The effective components and targets of TFH were identified using the TCMSP, PubChem, and Pharmmapper databases. AD-related targets were screened through GeneCards, OMIM, and TTD databases, leading to the identification of TFH anti-AD related targets. The STRING database was utilized to obtain protein interaction relationships, and Cytoscape 3.9.0 software was employed to construct the protein-protein interaction network. GO and KEGG enrichment analyses were conducted to elucidate the biological processes and pathways involved. Molecular docking between key components and key targets was verified using AutoDock Tools 1.5.6 software.

The key components identified for anti-AD activity were Quercetin, Kaempferol, Cianidanol, and Epicatechin, while the key targets included MAPK8, MAPK10, MAPK14, AKT1, SRC, and EGFR. GO analysis indicated that TFH's anti-AD effects are primarily associated with hormone regulation, cellular processes, response to stimuli, organelles, and cytoplasm. KEGG enrichment analysis suggested that the key pathways involved are pathways in cancer, lipid and atherosclerosis, and the IL-17 signaling pathway, with a significant emphasis on the IL-17 signaling pathway. Molecular docking results demonstrated that the key active ingredients exhibited strong binding activity with all the key targets, with the highest binding affinities observed between kaempferol and MAPK14, epicatechin and MAPK14, and quercetin and AKT1.

TFH exerts therapeutic effects on atopic dermatitis through multi-component, multi-target, and multi-pathway mechanisms involving inflammatory response, immune regulation, and apoptosis. This study provides valuable insights for the further development of drugs specifically targeting AD.

Ionic immobilized liquids and multi-component reactions are integral to green chemistry, facilitating the synthesis of biologically active compounds, such as xanthene and acridine derivatives. These approaches have garnered significant attention in recent years.

The aim of this study was to synthesize novel xanthene and acridine derivatives with diverse substituents and heterocyclic rings. Furthermore, the research sought to evaluate their anticancer activity against various cancer cell lines and analyze their structure-activity relationships (SAR) to determine how structural modifications impact their biological effectiveness.

The core compounds in this study were synthesized from cyclohexane-1,3-dione and triethoxymethane under two distinct reaction conditions. The first involved the use of a solvent with either Et3N or NH4OAc as a catalyst, while the second employed a solvent-free approach using an ionic liquid catalyst (ILs).

The anti-proliferative activity of all synthesized compounds was evaluated against six selected cancer cell lines, revealing that many compounds exhibited significant inhibitory effects. Furthermore, their inhibitory potential against tyrosine kinases and Pim-1 kinases was assessed, along with an investigation of their mechanism of action on tyrosine kinases.

The anti-proliferative activity of the newly synthesized compounds was evaluated against six cancer cell lines. Many of the compounds exhibited strong inhibitory effects not only against the tested cancer cell lines but also against tyrosine kinases and Pim-1 kinases.

Neuraminidase enzyme plays a major role in the life cycle of influenza viruses. Targeting neuraminidases is a key strategy in preventing and treating influenza A and B spread by inhibiting the release of new viral particles from infected cells. Developing new neuraminidase inhibitors with enhanced efficacy and reduced risk of resistance is the ultimate of ongoing research.

In this study, we tried to shed light on molecules of natural origin that inhibit neuraminidase enzyme by utilizing different aspects of in silico studies.

The work started by generating structure-based pharmacophore, later used for the virtual screening of electronic libraries constructed from chemical and natural compounds. Hits raised from virtual screening were subjected to molecular docking to assess and explain different modes of interactions with the neuraminidase enzyme. Drug likeness and ADME filters were applied to choose compounds that may be taken effectively by oral route with good gastrointestinal absorption and acceptable pharmacokinetics with respect to Lipinski and Ghose rules. The hits were also inspected for toxicity risks, including mutagenic, tumorigenic, irritant, and reproductive effects.

7 features of the generated pharmacophore from the potent inhibitor Oselatamiver were the base for virtual screening. The results obtained by database screening highlighted 4 natural compounds listed in the COCONUT library (CNP 0125691 (Penicitrinol K), CNP0256196 (Frenolicin D), CNP 0138184, and CNP 0206296) as potential neuraminidase inhibitors. The compounds showed a similar interaction profile to Oseltamivir by molecular docking with high binding affinity. The key residue TYR 406 hydrogen bonded to Penicitrinol and Frenolicin D as well as to Oseltamevir. The 4 natural compounds exerted drug-like properties and promising pharmacokinetic characters. Toxicity risks estimations put Penicitrinol K and Frenolicin as devoted to mutagenic, tumorigenic, irritant and reproductive potentials. Penicitrinol K and Frenolicin are assigned for further in vitro and in vivo studies as promising neuraminidase inhibitors.

Penicitrinol K, and Frenolicin D are promising natural neuraminidase inhibitors, exhibiting favourable drug-like properties and low toxicity risks in addition to showing the pattern of interaction profiles with neuraminidase enzymes similar to the known drug Oseltamivir contributing to the development of effective antiviral therapies against influenza, suggesting further in vitro and in vivo evaluation.

Mushrooms are shown to protect against the side effects of cancer. Therefore, mushrooms with proven anticancer properties and active ingredients are fascinating in the search for new cancer drugs.

In this study, the effects of extracts from Hericium coralloides (M1), Lactarius deliciosus (M2), Lepista nuda (M3), Pleurotus ostreatus (M4), and Suillus collinitus (M5) together on HCT116 were investigated. Mesenchymal stem cells (MSCs) were used to study the effect on healthy cells.

MTT was used to determine cell viability. Dose-response curves were generated, the IC50 values of the compounds were calculated, and the effect of the extracts was compared using it. The FTIR was used to analyze the quantitative changes of the cellular components.

The evaluation of the IC50 values of all fungal species showed that they reduced the cell viability of HCT116 cells. In contrast, no significant reduction in cell viability was observed in MSCs. Changes in the ratio of cell membrane lipids, proteins, and cell nucleic acids between control and fungal-treated HCT116 cells were detected by FTIR.

Many of the chemotherapeutic agents are of plant origin, and many resources should still be explored to inhibit the side effects of cancer therapy. The data obtained through this experiment will serve as a reference for studies to be a new source of anticancer drugs in modern pharmacology.

Diabetic Nephropathy (DN) is the leading cause of the end-stage renal disease (ESRD). Finerenone (with the molecular formula C21H22N4O3) is an oral non-steroidal mineralocorticoid antagonist (ns-MRA) that is both highly potent and has strong selectivity for the MR. At present, it has been used to treat DN. However, the molecular mechanism of finerenone in the treatment of diabetic nephropathy remains unclear.

In this study, we employed bioinformatics approaches to investigate the molecular mechanism of finerenone as a novel therapeutic agent for the treatment of DN.

We examined a number of databases, including GEO, DisGeNET, Genecards, and OMIM, to find putative genes linked to DN. We then employed the PubChem database and PharmMapper service platform to identify targets of finerenone. Further analysis was conducted using the DAVID database for enrichment analysis and the STRING database for protein-protein interaction (PPI) networks. Molecular docking (MD) was performed using AutoDockTools software, and results were visualized using PyMOL software.

In total, we identified 82 drug-disease targets, primarily associated with lipid and atherosclerosis, diabetic cardiomyopathy, MAPK signaling pathway, and PI3K-Akt signaling pathway. Our PPI network analysis and docking studies demonstrated good binding ability of finerenone to specific targets such as AKT1, MMP-9, IGF1, EGFR, CASP3, PPARG, ESR1, MMP-2, and KDR.

Finerenone has the potential to reduce the progression of DN through various pathways, including lipid and atherosclerosis, diabetic cardiomyopathy, MAPK signaling pathway, and PI3K-Akt signaling pathway. Moreover, it could exert anti-inflammatory and antifibrotic effects on specific targets, such as AKT1, MMP-9, IGF1, EGFR, CASP3, PPARG, ESR1, MMP-2, and KDR.

Hepatocellular carcinoma is the cancer with the highest mortality rate worldwide. Currently, existing treatments are not very effective for this disease. Different science areas have focused on developing new therapies, including nanomedicine. In-vitro studies have reported the anticancer activity of silver nanoparticles, particularly those coated with polyvinylpyrrolidone (AgNPs-PVP).

Characterize the effect of AgNPs on the HepG2 by bioinformatics analysis.

From a list of proteins, we performed in-silico analysis to predict protein-protein interaction, hub gene, gene ontology, KEGG pathways, hub gene expression, protein expression, survival, cell infiltration immune, and molecular docking of AgNPs-PVP to target proteins. Cytoscape and UCSF Chimera software, DAVID, UALCAN, TISIDB, and HDOCK databases were included in the predictive analysis.

Gene ontology and KEGG pathways showed that AgNP exposure causes cellular organelles dysregulation and deregulation of protein production mechanisms.

Additionally, metabolic pathways were altered, including glycolysis, gluconeogenesis, and amino acid biosynthesis. Hub genes RPS15, RPLP0, EEF1B2, RPL12, and NACA showed differential expression for gene expression, protein, and survival analysis. Furthermore, RPS15 and RPL12 were positively correlated with CD8+ T cell infiltration, and RPLP0, EEF1B2, and NACA were negatively correlated with NK cell infiltration. Finally, molecular docking showed that AgNPs-PVP interacts highly with the target proteins.

AgNPs cause alterations in cell viability. Furthermore, the deregulation of hub genes and the modulation of the immune system are associated with anticancer effects, and molecular docking demonstrated high interaction with the target proteins that should be studied experimentally.

Lidocaine is extensively utilized as an anesthetic in clinical settings; however, it has demonstrated significant neurotoxicity when administered for spinal anesthesia. The specific mechanisms underlying lidocaine-induced neurotoxicity are poorly understood.

This study aimed to investigate the mechanisms through which lidocaine induces neurotoxicity, focusing on its effects on intracellular calcium release and the activation of CaMKII and MAPKs pathways, as well as to evaluate the potential protective effects of cilnidipine.

The investigation has employed both in vitro cell models and in vivo mouse models to conduct the experiments. Neuronal cell viability has been assessed following lidocaine treatment, and neurological function has been evaluated in mice after intrathecal injection of lidocaine. Intracellular calcium levels, CaMKII activation, and the phosphorylation of p38 and p65 have been measured in cultured hippocampal neuronal cells and mouse brain tissues. The effects of the calcium channel blocker cilnidipine on these parameters have also been examined.

Lidocaine treatment led to a reduction in cell viability in cultured neuronal cells and induced neurological dysfunction in mice. It increased intracellular Ca²⁺ levels and activated CaMKII in both cultured neuronal cells and mouse brain tissues. Lidocaine also elevated the phosphorylation levels of p38 and p65 in neuronal cells. These effects have been suppressed by cilnidipine, indicating a calcium-dependent mechanism.

This study suggests that lidocaine induces neurotoxicity through a calcium-dependent activation of CaMKII and MAPK pathways, leading to neuronal apoptosis and dysfunction.

Cilnidipine has been found to exhibit promise as a protective agent against lidocaine-induced neurotoxicity.

This study investigates the efficacy of α7-nicotinic acetylcholine receptor (α7nAChR) agonists in mitigating postoperative cognitive dysfunction (POCD) in a rat model. This investigation aimed to elucidate the therapeutic potential of α7nAChR agonists in modulating neuroinflammatory pathways to improve cognitive outcomes post-surgery.

Serum levels of pro-inflammatory cytokines IL-1β and IL-18 were measured as markers of systemic inflammation, while the expression levels of NLRP3 mRNA were quantified to evaluate pyroptosis and NLRP3 inflammasome activation.

Adult male Sprague-Dawley rats were divided into control (no surgery), POCD (surgery-induced), and POCD treated with an α7nAChR agonist. Cognitive function was assessed using the Morris Water Maze (MWM) and Novel Object Recognition (NOR) tests.

The results showed a notable cognitive impairment in the group with POCD, as shown by increased escape latency noted in the MWM test and decreased discrimination index in the NOR test, while controls had no change. However, treatment with the α7nAChR agonist led to a significant improvement in cognitive performance among the POCD rats such that it closely matched those of the controls. Furthermore, the POCD group exhibited elevated serum levels of IL-1β and IL-18 and increased expression of pyroptosis-related markers, indicating enhanced neuroinflammation and inflammasome activation.

These findings highlighted the therapeutic efficacy of α7nAChR agonists in mitigating neuroinflammation and improving cognitive outcomes post-surgery. Our study supports the potential of targeting the cholinergic anti-inflammatory pathway, emphasizing clinical evaluation of α7nAChR agonists in postoperative patients.

Sedum sarmentosu Bunge (SSB), a perennial herb, exhibits notable therapeutic effects on hepatic fibrosis (HF). However, the mechanism of treatment has not been fully determined.

The objective of this study is to explore the active components in SSB and investigate its molecular mechanism of action in the treatment of HF based on network pharmacology, molecular docking, and molecular dynamics simulation (MD).

Databases such as TCMSP, Gene Cards, OMIM, and DAVID, as well as Cytoscape, AutoDock Vina, and Gromacs software, were used for analysis.

A total of 5 active components and 86 HF-related targets were screened for SSB, among which the most prominent components are luteolin and quercetin. The key targets for HF are MMP2, MMP3, MMP9, ABCG2, etc. GO enrichment analysis showed that SSB was closely associated with apoptosis, inflammatory response and cell migration processes. KEGG enrichment analysis showed that the major enrichment pathways for liver fibrosis include EGFR tyrosine kinase inhibitor resistance, PI3K-Akt signaling pathway, and cancer-related pathways. Molecular docking and MD showed that luteolin and quercetin have good affinity and stable binding to MMP2, MMP3, and MMP9.

SSB exerts therapeutic effects on HF through multiple components, targets, and pathways, thereby providing a theoretical foundation for the development of its active compounds and mechanisms of action.

Stroke is one of the most important causes of mortality and disability in the world. Over 80% of strokes are ischemic, resulting from blockages in cerebral arteries. Increasing evidence suggests that enriching the diet with nutritional antioxidants could decrease brain damage and enhance cognitive function. Cornelian cherry has anti-inflammatory and antioxidant properties and is introduced as a potential source of active ingredients, like anthocyanins, vitamin C, phenolic compounds, and minerals.

Our research study aimed to evaluate the neuroprotective impact of Cornus mas L. (cornelian cherry) on a rat model of Cerebral Ischemia/Reperfusion Injury (CIRI).

Middle cerebral artery blockage induced CIRI for 60 minutes. After inducing CIRI, intra-peritoneal injections of Cornus mas Extract (CME) were administered for 14 days in a dose-dependent manner (30, 60, and 120 mg/kg body weight). The effects of CME on learning and memory recovery were evaluated using a shuttle box behavioral test.

Two weeks following CIRI, several factors of oxidative stress, such as nitrite (NO2-), Ferric ion Reducing Antioxidant Power (FRAP), and Malondialdehyde (MDA), were measured in the hippocampal tissues and serum. Anti-inflammatory genes, such as miR-125b, and the target genes (TNF-α and iNOS) were evaluated via real-time PCR assay. Additionally, neural damage in the CA1 and CA3 regions of the hippocampus was assessed using Hematoxylin and Eosin (H&E) staining.

The avoidance time in the shuttle-box behavior test supported our finding that CME exhibited improved fear memory. Furthermore, it increased the CA1 and CA3 hippocampal post-stroke pyramidal cell layers. Levels of NO2- and MDA were decreased, and FRAP was considerably increased in both the hippocampus and serum by CME. Additionally, CME increased miR-125b expression, while modulating TNF-α and iNOS production in the hippocampal regions.

Based on our findings, we can conclude CME to possess antioxidant and anti-inflammatory properties, which confer neuroprotective potential against CIRI, thereby protecting neurons from ischemic death.

Chronic Renal Failure (CRF) refers to the gradual decline in renal function caused by various chronic kidney diseases, eventually leading to end-stage renal failure. Yangshen Paidu Decoction (YPD) is a Traditional Chinese medicine (TCM) formula utilized in CRF treatment. This work has analyzed the effects of YPD on CRF and the specific mechanism.

Network pharmacology was performed to screen effective components and targets of YPD, from which key targets and signaling pathways contributing the most to the treatment effects on CRF were determined. Subsequently, we validated the therapeutic role of YPD and the underlying pathological mechanisms using the 5/6-nephrectomy rat model.

Network pharmacology analysis showed the mTOR pathway to be a pivotal mechanism underlying the effectiveness of YPD in CRF treatment. YPD significantly suppressed urine protein levels, blood urea nitrogen, and serum creatinine in 5/6 nephrectomized rats. Furthermore, YPD remarkably improved renal pathological injuries. Western blot analysis revealed that YPD enhanced autophagy and upregulated the expression of nephrin, podocin, beclin1, p-AMPK/AMPK, and p-ULK1/ULK1, and attenuated the ratios of p-mTOR/mTOR to its downstream protein phosphorylated eIF4E-binding protein (p-4EBP1). However, these effects were notably reversed by the AMPK inhibitor compound C.

Our findings have demonstrated YPD to suppress the mTOR pathway and stimulate autophagy by modulating AMPK pathways, thereby mitigating podocyte injury and enhancing renal function. Our study has confirmed autophagy and the AMPK/mTOR pathway as potential targets for YPD in CRF treatment.

This study evaluated the effects of Rigosertib (RGS) on the prevention of intra-abdominal adhesions in a mouse model.

Eighteen mice were divided into three groups: Sham (no abrasion or adhesion), Positive Control (surgical abrasion and adhesion), and Rigosertib Treatment (200 mg/kg/day intraperitoneally for 7 days). Adhesions were induced through cecal abrasion and assessed using Nair and Leach adhesion scoring systems. Histological evaluations were performed using Haematoxylin & Eosin (H & E) and Masson's trichrome stains in order to analyze inflammatory cell infiltration and collagen deposition.

Results showed that RGS administration did not have a significant impact on the formation or rigidity of adhesion bands compared to the positive control group. Both Nair and Leach scoring systems confirmed the lack of significant differences. Histological analysis revealed no reduction in inflammatory responses or collagen deposition in RGS-treated mice. H & E staining showed similar inflammatory cell infiltration across all groups, while Masson's trichrome staining indicated no differences in fibrosis levels between treated and untreated mice. In conclusion, Rigosertib did not demonstrate efficacy in down-regulating peritoneal adhesions or associated inflammatory responses and fibrosis in this mouse model.

These findings suggest that Rigosertib may not be suitable for preventing intra-abdominal adhesions, warranting further investigation into alternative therapeutic strategies.

Currently, network pharmacology and molecular docking technology are valuable tools frequently employed to predict the mechanisms and targets of drugs. Wengbu, a Tibetan medicine, is an anti-inflammatory agent commonly used in the Qinghai-Tibet Plateau of China, and it has been demonstrated to have an effect against skin inflammation. However, the network pharmacological mechanisms and targets of Wengbu in relation to skin inflammation have not yet been reported. This paper aims to provide a scientific basis for the anti-skin inflammatory effects of Wengbu through experimental verification based on the predicted targets.

The chemical constituents and targets of Myricaria germanica essential oil were identified through a literature search, as well as databases such as PubChem and Swiss Target Prediction. Targets associated with skin inflammation were obtained from the Gene Cards human gene database, DisGeNET, and the OMIN databases. Subsequently, a Myricaria germanica essential oil-skin inflammation target database and a corresponding target network diagram were constructed. Biological function enrichment analysis and molecular docking verification were then conducted. In vitro cell experiments were performed to validate the role of Myricaria germanica essential oil's key targets in inhibiting skin inflammation.

Ten compounds were selected through a literature review, including linalool, eugenol, and vanillin. A total of 429 essential oil component targets, 889 skin inflammation targets, and 108 intersection targets were identified. MAPK1, PIK3CD, PIK3CA, and MAPK14 could be the principal targets of Myricaria germanica. essential oil to reduce skin inflammation. The principal signaling pathways through which Myricaria germanica essential oil exerts its anti-inflammatory effects include the cancer pathway, coronavirus disease (COVID-19), lipid metabolism, and atherosclerosis. These effects may be attributed to the regulation of the cellular inflammatory response, the cellular response to lipopolysaccharide, and the positive regulation of cytoplasmic calcium concentration. Molecular docking results indicated that the potential components of Myricaria germanica essential oil exhibited strong binding affinity with the core target proteins. In vitro cell experiments demonstrated that Myricaria germanica essential oil effectively reduced the levels of TNF-α, IL-6, and Caspase-3, decreased the levels of reactive oxygen species (ROS) and malondialdehyde (MDA) in cells, and enhanced the activity of superoxide dismutase (SOD), thereby inhibiting skin inflammation.

Myricaria germanica essential oil exhibits multi-component, multi-target, and multi-pathway characteristics in the inhibition of skin inflammation. This experiment serves as a reference and foundation for further elucidating its material basis and the mechanisms involved in inhibiting skin inflammation.

Non-ionic surfactant-based vesicles (niosomes) as coherent and self-organization capability structures form organized core/shell nanostructures.

In this academic research, Ni/NiAl2O4 core/shell nanostructures were successfully synthesized with the ultrasound-assisted direct micelle (UADM) method and these structures were used as a delivery system for minoxidil drugs.

The synthesis conditions for producing Ni/NiAl2O4 core/shell structures were optimized using a design of experiments (DOE) approach. Process control was systematically examined through analysis of variance (ANOVA) and response surface methodology (RSM). The Ni/NiAl2O4, core/shell nanostructures, underwent characterization using various techniques such as SEM (scanning electron microscopy), TEM (transmission electron microscopy), AFM (atomic force microscopy), FT-IR (Fourier-transform infrared spectroscopy), TGA (thermogravimetric analysis), BET analysis, differential thermal analysis (DTA), and nitrogen adsorption isotherms. The in vitro release of minoxidil from the Ni/NiAl2O4 core/shell nanostructures was studied using UV-vis spectroscopy at a wavelength of 486 nm.

Results indicated an encapsulation efficiency (EE%) of around 74% after 150 minutes. Furthermore, the loading efficiency of minoxidil in niosomes modified with Ni/NiAl2O4 core/shell nanostructures was calculated to be approximately 99.83% at 486 nm.

Overall, this research lays a foundational framework for developing innovative nanomaterials with tailored properties for advanced delivery systems and other novel applications.

Traditional Chinese medicine rarely applies the herb Safflower (Carthamus tinctorius) to the treatment of tumors and little is known about its mechanisms and the treatment of Safflower for melanoma.

This study aims to analyze the active ingredients and underlying mechanisms of Safflower in treating melanoma using network pharmacology, molecular docking, and in vitro experiments and provide a new direction for the research and development of new drugs for melanoma treatment.

We collected the active chemical ingredients from Safflower and generated a network of “Drug-Active Ingredient-Target” by Cytoscape. From the DrugBank, OMIM, and GeneCard databases, disease-related targets of melanoma were obtained. The intersection target genes between Safflower and melanoma were identified, leading to the construction of a protein-protein interaction (PPI) network via Cytoscape software. Metascape database was used to enrich pathways for relative targets of Safflower. Molecular docking was demonstrated by the software AutoDockTools-1.5.6. Use an online database (https://xenabrowser.net/) and R package IOBR (version 0.99.9) to evaluate the correlation between the core target genes and prognosis or the immune score. CCK8 and PCR were used to detect the toxicity of quercetin on melanoma cells and its effects on mRNA expression of AKT1, JUN, and TP53.

Our investigation identified 17 active pharmaceutical ingredients within Safflower alongside 94 potential targets related to melanoma treatment. Gene Ontology (GO) analysis is primarily concerned with extracellular exosomes, positive regulation of transcription from RNA polymerase II promoter, and protein binding. KEGG pathway enrichment analysis mainly involves Pathways in cancer, IL-17 signaling pathway, AGE-RAGE signaling pathway, and other pathways. Using molecular docking, it can be seen that the compounds Quercetin, kaempferol, luteolin, baicalein, and beta-sitosterol in Safflower have strong binding abilities with important targets. The results of survival analysis and immune score analysis suggest that Safflower may regulate the immune cell infiltration of melanoma patients by acting on core target genes and improving the prognosis of patients. In vitro analysis confirmed that Quercetin was cytotoxic toward B16-F10 cells and altered mRNA expression of AKT1, JUN, and TP53 identified through the network pharmacology approach.

This work offered an active pharmaceutical ingredient in Safflower and potential targets for melanoma, and the mechanism of its action on melanoma may be related to the regulation of immune-related pathways in melanoma.

Post-operative adhesion band formation is a serious post-surgery complication with a highly detrimental impact on patient morbidity and health care costs. In this study, we aimed to investigate the repurposed potential of a safe and FDA-approved drug, metformin, in attenuating post-surgical adhesion band formation in Achilles tendon surgeries in an animal model.

Wistar albino rats were divided randomly into three groups: sham, positive control, and metformin-treated groups (n=6). We administered Metformin 100 mg/kg orally for 21 days. Achilles tendon tissue sections were stained with Hematoxylin-Eosin and Masson's trichrome to assess the accumulation of inflammatory cells and collagen deposition. Spectrophotometric analysis was performed on tissue samples to determine oxidative stress markers. According to Tang and Ishiyama scoring systems, Achilles tendon adhesion properties were compared.

Using the Tang and Ishiyama scoring system, we showed that metformin significantly decreased the length, density, grading, and severity of adhesion bands at surgery sites (***p<0.001). Pathologic morphological changes and oxidative stress markers decreased in tendon tissue samples of metformin-treated rats compared to control (**p<0.01, ***p<0.001). Moreover, administration of metformin markedly decreased collagen deposition, fibrosis accumulation, and fibrosis quantity score as visualized by Masson’s trichrome staining in tissue sections (*p<0.05).

These results suggest that metformin, with its potent anti-inflammatory and anti-fibrotic properties, can be repurposed as a potential therapeutic molecule for preventing post-operative adhesion band formation.

Acute myocardial infarction (MI) is a serious emergency disease with high mortality. Hypoxia is associated with unfavorable outcomes in cancer patients. Nevertheless, there remains a shortage of effective hypoxia-related biomarkers to forecast the prognosis of acute MI patients and to identify targeted therapies.

First, data on acute MI patient samples and hypoxia-related genes were obtained based on public databases. Hypoxia-related gene scores were calculated by single sample Gene Set Enrichment Analysis (ssGSEA). Hypoxia-related hub genes in acute MI were screened via weighted correlation network analysis (WGCNA). Acute MI samples were analyzed for differentially expressed genes (DEGs) using the limma package and intersected with hub gene for hypoxia-related DEGs. Then, machine learning methods were used to identify hypoxia-related biomarkers in acute MI. Gene set enrichment analysis (GSEA) and immune infiltration analysis were performed on biomarkers. Targeted drug prediction and molecular docking were conducted based on biomarkers.

The hypoxia-related gene score of the acute MI group was higher than the control group, and 319 hypoxia-related hub genes in acute MI were acquired. A total of 7 hypoxia-related DEGs were obtained by WGCNA and DEGs analysis. Then, 2 hypoxia-related biomarkers in acute MI, HAUS3 and SLC2A3, were identified based on machine learning algorithms. Both HAUS3 and SLC2A3 were enriched in the ribosome and spliceosome pathways. The expression levels of SLC2A3 and HAUS3 were correlated with immune cell infiltration. Furthermore, 8-hydroxyquinoline, perhexiline, and sotalol were selected as the targeted drugs, which could bind to HAUS3 and SLC2A3.

In short, we screened two important hypoxia-related biomarkers and three potential target drugs based on bioinformatics techniques. This provides new ideas and potential drug targets for early diagnosis and targeted therapy of acute MI.

Phosphodiesterase-5 (PDE5) is an enzyme that promotes the degradation of cGMP in the blood, leading to a restriction in regulating blood flow in the penis, thereby reducing cGMP causing difficulties for men in achieving hardness (erectile dysfunction). Natural products with fewer side effects are being developed in many different treatment strategies and are necessary today. The current study aims to evaluate this enzyme's in silico inhibitory potential and marine xanthones through computational models.

The database of marine xanthones was collected from previously published literature. Protein structures were downloaded from the RCSB protein data bank (PDB ID: 1UDT). Molecular docking studies were performed using the AutoDock Vina v1.2.3 program to conduct screening. Molecular dynamics simulations were carried out with the GROMACS program to assess structural stability, and gmx_MMPBSA was used to make free-binding energy calculations for each PDE5 protein complex with potential compounds. Furthermore, Density Functional Theory (DFT) was applied in this study to calculate the atomic properties of the molecules based on quantum mechanics using the Gaussian 09 program.

Molecular docking revealed that 21 compounds (staprexanthone A (69), emerixanthone E (89), emerixanthone A (90), emerixanthone C (91), varixanthone (92), aspergixanthone H (95), austocystin L (98), austocystin M (99), emerixanthone D (109), 15-acetyl tajixanthone hydrate (117), tajixanthone hydrate (118), 16-chlorotajixanthone (119), citreamicin ε A (131), citreamicin ε B (132), engyodontochone A (146), citreamicin θ B (151), citreaglycon A (152), dehydrocitreaglycon A (153), neocitreamicin I (159), citreamicin α (161), ukixanthomycin A (165) had superior binding affinities (ΔG < -11 kcal/mol) compared to the control inhibitor. Molecular dynamics confirmed the stability of the protein-ligand complexes. MM/GBSA analysis showed nine compounds (91, 98, 109, 118, 119, 151, 159, 161, 131) had binding energies comparable to or better than sildenafil. Quantum mechanical estimates indicated their potential as electron donors and acceptors, highlighting their antagonistic potential.

These promising marine xanthones warrant further research to assess their PDE5 inhibitory activity in vitro and in vivo. This could provide valuable insights for developing new natural resource-based drugs to prevent or treat erectile dysfunction.

To address the issues of liposomal instability and enhance the delivery of docetaxel (DTX) to breast cancer cells, the development of polyethylene glycol (PEG)-coated proliposomes was proposed, utilizing a thin film hydration technique followed by lyophilization with an appropriate cryoprotectant. Various compositions of phospholipid, cholesterol, and docetaxel were optimized, and the PEG was used in a 1.3:1 ratio of the phospholipid.

The liposomes were converted to proliposomes using a lyophilizer. The optimized formulation possesses a particle size of 117.0 ± 9.78 nm, with a polydispersity index (PDI) of 0.265 ± 0.094, drug entrapment (DE) of 96.0± 6.14%, and drug loading (DL) of 9.20 ± 3.17%. In-vitro study demonstrated a controlled release pattern consistent with the Higuchi model, alongside significantly lower protein binding relative to free DTX, indicating a potential reduction in side effects.

Cell viability study demonstrated increased cytotoxicity of PEG-DTX proliposomes (PEG-DTX PL) against MDA-MB-231 cells, evidenced by a lower IC50 (4.677 μg/mL) relative to free DTX, underscoring the promise of this nanocarrier for targeted therapy.

The findings are promising as a simple and scalable carrier comprising general and biocompatible materials that can provide a safe surfactant free nanosystem with improved efficacy and performance.

Breast cancer is a common and deadly disease that affects women worldwide. Despite advancements in research and treatment, breast cancer continues to be a significant health issue.

This study examined the potential of black soybean, commonly known as Sojae Semen Nigrum (SSN), in the prevention and therapy of breast cancer using a mix of data mining, network pharmacology, and docking analysis.

Molecular dynamic simulation studies and docking analysis supported the findings by confirming the bioactive compounds' efficient activity against potential target genes.

The study discovered the top three significant compounds Pramoxine, Sapogenol C, and beta-sitosterol, that may change target genes involved in the etiology of breast cancer as well as proteins like AKT1, MAPK1, and MAPK3. The study's conclusions point to SSN as having potential multi-target pharmacological defenses against breast cancer, laying the groundwork for more experimental exploration.

The study's conclusion suggests that SSN may help certain people with breast cancer and might transform cancer treatment.