Combinatorial Chemistry & High Throughput Screening - Online First

Benzoimidazo[1,2-a]pyrimidines are important compounds that have many useful effects in the body. They can help fight cancer, fungal infections, inflammation, and viruses. They can also help with various other health conditions. They can act as antineoplastic, antitubercular, parasitical activity, benzodiazepine receptor agonists, calcium channel blockers, potent P38 MAP kinase inhibitors, TIE-2 and/or VEGFR2 inhibitory activities, protein kinase inhibitors, and T cell activation. There are different methods to make the benzoimidazo[1,2-a]pyrimidines. Some of them dealth with the one-pot threecomponent condensation reactions of β-dicarbonyl compounds, aldehyde and 1H-benzo[d]imidazol-2-amine in the presence of catalyst. Although the synthesis of this group of compounds has been done before, and the products have been identified from the spectroscopic point of view, the kinetics and reaction mechanism have not been investigated. The strength of these calculations is that evaluation of the activation energy of various steps suggests possible mechanisms, probable mechanisms, and valuable synthetic intermediates.

In this report, seven possible mechanisms for synthesizing the benzoimidazo[1,2-a]pyrimidines have been investigated using density functional theory (DFT) at the B3LYP/6-311G** level of theory. Each synthetic route involves condensation of the benzaldehyde, indanedione and 1H-benzo[d]imidazol-2-amine molecules to yield the proposed product. The calculations showed that the suggested method has six steps; its initiation step includes the Knoevenagel reaction between indanedione and aldehyde, and the rate determining state is dehydration in the fifth step.

Six potential pathways for the reaction will occur. Then, we focused on the best pathway and studied it in detail. The ways that three chemicals-indanedione (R1), benzaldehyde (R2), and 1H-benzo[d]imidazol-2-amine (R3) react with each other were studied using ab-initio program by ChemBio3D, Gauss View, and Gaussian 09. The Density Functional Theory (DFT) using the B3LYP basis set was used to improve the arrangement of molecules involved in the three-part creation of a specific compound called 12-phenyl-5H-benzo[4,5]imidazo[1,2-a]indeno[1,2-d]pyrimidin-13(12H)-one (P).

During the study of the six mechanisms, the proposed pathway 2 is the best mechanism for this reaction because its rate-determining step has the lowest activation energy value. This route consists of 6 steps, the fifth step of which is related to the conversion of IM4 to IM5 (relative ∆E: 109.80 Kj/mol), during which a dehydration reaction is performed, and this step occurs by passing through transition state TS5 (Total Energy (Hart./particles: -1194.747403).

Esophageal Squamous Cell Carcinoma (ESCC) remains a significant global health challenge, underscoring the urgent need for the development of innovative therapeutic approaches. Ranunculus ternatus Thunb., a traditional herb, exhibits potential anticancer properties, but its mechanisms against ESCC remain poorly understood. This study integrates network pharmacology and experimental validation to explore the therapeutic effects of the ethyl acetate extract of Ranunculus ternatus Thunb. (RTE).

Potential targets of RTE and ESCC were screened using public databases. A Protein-Protein Interaction (PPI) network was constructed to identify key targets, followed by GO and KEGG pathway enrichment analyses. The predicted mechanisms were validated using in vitro assays, including cell proliferation analysis and western blot assay in ESCC cell lines.

Network pharmacology analysis identified 274 potential targets, with 14 key genes implicated in the therapeutic effects of RTE. GO analysis revealed significant involvement in the inflammatory response and apoptotic signaling pathways. KEGG pathway analysis highlighted the MAPK, Relaxin, and PI3K/Akt signaling pathways as critical mechanisms. In vitro experiments demonstrated that RTE significantly inhibited the proliferation of EC-109 and TE-13 cells by modulating the MAPK/ERK and PI3K/Akt pathways.

The study reveals that active compounds of RTE target MAPK/ERK and PI3K/Akt pathways, aligning with prior evidence. However, future studies should explore animal models to confirm efficacy.

This study provides a comprehensive understanding of the molecular mechanisms underlying the anticancer effects of RTE against ESCC. These findings underscore the potential of RTE as a promising natural compound for ESCC treatment.

The objective of this research is to demonstrate that alignment-free bioinformatics approaches are effective tools for analyzing the similarity and dissimilarity of protein sequences. All numerical parameters representing sequences are expressed analytically, ensuring precision, clarity, and efficient processing, even for large datasets and long sequences. Additionally, a novel approach for identifying previously unknown virus strains is introduced.

A novel approach is proposed, integrating the unique features of our newly developed method, the 20D-Dynamic Representation of Protein Sequences, with the K-means clustering algorithm. The sequences are represented as clouds of material points in a 20-dimensional space (20D-dynamic graphs), with their spatial distribution being unique to each protein sequence. The numerical parameters, referred to as descriptors in molecular similarity theory, represent quantities characteristic of dynamic systems and serve as input data for the K-means clustering algorithm.

Examples of the application of the approach are presented, including projections of the 20D-dynamic graphs onto 3D spaces, which serve as a visual tool for comparing sequences. Additionally, cluster plots for the analyzed sequences are provided using the proposed method.

Combining the 20D-Dynamic Representation of Protein Sequences with an unsupervised machine learning algorithm (K-means clustering) enhances its scalability. This approach is applicable to large datasets without restrictions on sequence length.

It has been demonstrated that the 20D-Dynamic Representation of Protein Sequences, combined with the K-means clustering algorithm, successfully classifies subtypes of influenza A virus strains.

This study aimed to assess the safety and effectiveness of carbamazepine in treating trigeminal neuralgia in contrast to gabapentin. Hence, a systematic review and meta-analysis of randomised controlled trials had been carried out.

The relevant studies were searched in PubMed and filtered according to the inclusion and exclusion criteria. Independently, two reviewers chose the studies, evaluated the quality of the investigations, and retrieved the data. RevMan was used for analysis when the data were collected and entered into the data extraction sheet. In addition to heterogeneity, the overall estimate measures were computed as mean differences with a 95% confidence interval for continuous data and relative risk for dichotomous data. To investigate the impact of outliers on the result, a sensitivity analysis was performed. A funnel plot was used to qualitatively evaluate the publishing bias. A total of 1,650 participants from 19 randomised controlled trials were evaluated.

The meta-analysis revealed that the group receiving gabapentin therapy had a similar overall effective rate to the group receiving carbamazepine therapy (OR = 1.94, 95% CI 1.46, 2.57, P = 0.32). Additionally, our meta-analysis revealed that the group receiving gabapentin therapy witnessed a significantly lower risk of adverse reactions than the group receiving carbamazepine therapy (OR= 0.29, 95% CI 0.22, 0.387, P<0.00001).

In summary, the current trials comparing carbamazepine and gabapentin have had inadequate methodological quality. It is not possible to conclude that gabapentin is more effective than carbamazepine in terms of adverse effects based on the evidence that is currently available.

Atherosclerosis, a leading cause of death globally, is characterized by the buildup of immune cells and lipids in medium to large-sized arteries. However, its precise mechanism remains unclear. The purpose of this study is to explore innovative and reliable biomarkers as a viable approach for the identification and management of atherosclerosis.

The atherosclerosis-related datasets GSE100927 and GSE66360 were retrieved from the Gene Expression Omnibus (GEO) database. The Limma package in the R programming language was utilized, applying the criteria of |logFC| > 1 and P < 0.05. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the 127 identified DEGs using R. Machine learning techniques were then applied to these data to explore and pinpoint potential biomarkers. The diagnostic potential of these markers was assessed via Receiver Operating Characteristic (ROC) curve analysis. Finally, western blot, real-time quantitative PCR (qRT-PCR), and immunohistochemistry (IHC) were employed to confirm the key biomarkers.

Our research indicated that a total of 127 DEGs linked to atherosclerosis were successfully identified. Through the application of machine learning methods, eight critical genes were highlighted. Among these, Nuclear Receptor Subfamily 4 Group A Member-2 (NR4A2) emerged as the most promising marker for further investigation. CIBERSORT analysis revealed that NR4A2 expression levels were significantly correlated with multiple immune cell types, including B cells, plasma cells, and macrophages. Additional validation experiments confirmed that NR4A2 expression was indeed elevated in atherosclerotic plaques, supporting its potential as a biomarker for atherosclerosis.

Our study identified NR4A2 as a potential immune-related biomarker for the diagnosis and treatment of atherosclerosis.

The phylum Thermotogae is composed of five families: Fervidobacteriaceae, Thermatogaceae, Kosmotogaceae, Petrotogaceae, and Mesoaciditogaceae; one class: Thermotogae; and four orders: Kosmotogales, Petrotogales, and Mesoaciditogales. There are thirteen genera in all. The physical and metabolic characteristics of the Thermotogae species reflect the extreme heat from which they were separated. Thermotogae members have a broad spectrum of metabolic capacities, resulting in a pool of valuable chemicals with potential uses in many different sectors.

A 1.5-liter operating capacity bioreactor with a 2.3-liter double-jacket glass volume was utilised to culture Thermotoga maritima in both oxic and anoxic conditions. In addition to temperature, pH, and redox potential, sensors that were installed within the fermentor monitored additional parameters. RNA extraction and cDNA synthesis A total of RNAs was extracted utilising Roche's High Pure RNA reagent. Analysis of glycolysis pathways in T. maritima was performed by NMR spectroscopy

Based on NMR analysis, our findings demonstrate that T. maritima uses the EM route to metabolize 90% of glucose in anoxia and the ED pathway for 10%. On the other hand, T. maritima continues to employ the EM and ED glycolysis routes concurrently when exposed to extended oxidative stress; however, the ED pathway's contribution drops from 10% to around 5%.

Compared to the EM route, the ED pathway has more strongly repressed transcripts that encode its unique enzymes.

Natural products are a rich source of diverse chemical compounds with interesting therapeutic properties. There is a need for in-depth investigation of this reservoir with in-silico tools to assert the molecular diversity with respect to clinical significance. Although studies have been reported on plants such as Nyctanthes arbor-tristis(NAT) and its medicinal importance. A comprehensive study on comparative analysis of all phyto-constituents has not been carried out.

n the present work, we have carried out a comparative study of compounds obtained from the ethanolic extracts of various parts such as calyx, corolla, leaf, and bark of the NAT plant.

The extracted compounds were characterized by LCMS and GCMS studies. This was further corroborated by the network analysis, docking, and dynamic simulation studies with validated anti-arthritic targets.

The most significant observation from LCMS and GCMS was that the compounds from calyx and corolla were closer in chemical space to the anti-arthritic compounds. To further expand and explore chemical space, the common scaffolds were seeded to enumerate a virtual library. The virtual molecules were prioritized based on the drug-like, leadlike scores and docked against anti-arthritic targets to reveal identical interactions in the pocket region.

The comprehensive study will be of immense value to medicinal chemists for the rational synthesis of molecules as well as bioinformatics professionals for getting useful insight into identifying rich diverse molecules from plant sources.

Polymerase Chain Reaction (PCR) has been a pivotal scientific technique since the twentieth century, and it is widely applied across various domains. Despite its ubiquity, challenges persist in efficiently amplifying specific DNA templates.

While PCR experimental procedures have garnered significant attention, the analysis of the DNA template, which is the experiment's focal point, has been notably overlooked. This study addresses the uncertainty surrounding the amplification of DNA fragments using conventional Taq DNA polymerase-based PCR protocols. The imperative need to characterize DNA templates and devise a reliable method for predicting PCR success is underscored.

In this study, we formulate a 72-dimensional feature vector representing a DNA template through the utilization of k-word order and modeling of physicochemical properties of double bases. Subsequently, a Support Vector Machine (SVM) model is employed to assess PCR results.

A jackknife cross-validation test is used to evaluate the anticipated success rates, resulting in an overall accuracy of 95.77%. Sensitivity, specificity, and Matthew's Correlation Coefficient (MCC) stand at 95.75%, 95.79%, and 0.915, respectively.

Magnoliae Flos (Chinese name: Xin-Yi) and Xanthii Fructus (Chinese name: Cang-Er-Zi) are Chinese herbal medicines and have been used to treat allergic rhinitis (AR). However, the therapeutic effect, active ingredients, and probable processes of a compound of Magnoliae Flos and Xanthii Fructus in the form of essential oils (CMFXFEO) in treating AR have not been reported. This study aims to determine the efficacy of the CMFXFEO on ovalbumin (OVA)-induced AR in a rat model and to use network pharmacology and molecular docking to reveal the hub genes, biological functions, and signaling pathways of CMFXFEO against AR.

Animal experiments were applied to validate the role of CMFXFEO in the treatment of AR. 20 rats were randomly divided into four groups: control group (CON, n=5), positive control group (AR, n=5), CMFXFEO-treated group (AR+CMFXFEO, n=5), and budesonide-treated group (AR+Budesonide, n=5). Rats were stimulated with OVA to induce AR. Symptom scores assessment and histo-pathomorphological evaluation was performed. The serum level of OVA-specific immunoglobulin (Ig) E was measured. Gas Chromatograph-Mass Spectrometer analysis (GC-MS) was used to identify the monomer chemical composition of CMFXFEO. The target genes of CMFXFEO were obtained by using PubChem and SwissTargetPrediction databases. The target genes of AR were screened using GeneCards, DisGeNET, and OMIM databases. The target genes were intersected using the venny2.1 website to obtain the potential therapeutic targets of CMFXFEO for treating AR and to construct the PPI network. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to reveal associated signaling pathways. The Sybyl tool was used to dock the CMFXFEO with key therapeutic targets molecularly.

Intranasal CMFXFEO administration significantly suppressed the allergic symptoms, reduced the inflammatory cell infiltration, and the serum level of OVA-specific immunoglobulin (Ig) E. The main components of CMFXFEO obtained through the GC-MS analysis, listed as γ-terpinene (9.4908%), limonene (7.2693%), menthol (7.1821%), β-pinene (7.1190%), β-caryophyllene (7.0396%), eucalyptol (6.1367%), linalool(5.9686%), eugenol (5.0776%). A total of 398 CMFXFEO targets and 488 AR-related targets were screened, of which 42 were common targets. The GO and KEGG pathway analyses unveiled that CMFXFEO were strongly associated with several signaling pathways, including the AGE-RAGE signaling pathway, TNF signaling pathway, and Chemokine signaling pathway. PPI network construction screened six hub genes as therapeutic targets, including STAT3, IL1B, TLR4, PTGS2, ICAM1, and VCAM1. The molecular docking verification indicated that CMFXFEO have good binding activity with therapeutic targets, and β-Pinene’s docking ability with TLR4 is particularly prominent.

The anti-inflammatory and anti-allergic effects of CMFXFEO are to inhibit the infiltration of inflammatory cells in the OVA-induced AR rat model. The results of the network pharmacology and molecular docking deduced that the CMFXFEO may have the potential to treat AR by multiple pathways through relieving inflammatory, anti-oxidative stress response, and modulating the immune system.