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.