Combinatorial Chemistry & High Throughput Screening - Volume 24, Issue 2, 2021

Background: Diabetes mellitus type-II is a major health problem characterized by hypoinsulinemia and insulin resistance, leading to hyperglycemia and its complications. In Unani medicine, it is known as ziyābetus. Several drugs are prescribed in Unani medicine as single and compound formulations for this disease. Most of these drugs have been studied on scientific parameters and shown significant activity in reducing the symptoms and complications of diabetes. Objectives: Critical evaluation of Unani medicines for treating diabetes patients have been conducted. The aim of the study is to provide complete information on this subject with the action of the mechanism so that proper treatment should be done with prospective research. Methods: Unani literature was reviewed extensively via various search engines for the herbs, shrubs used for diabetes treatment. Ten drugs were selected for the present review. Results and Conclusion: There is convincing evidence to suggest that the selected drugs have promising actions against diabetes and its complications. In addition, none of the studies has reported any adverse effects with the drugs. Also, there is evidence to suggest that the method of usage described in Unani medicine may reduce or eliminate adverse events, if any. Further, there is a great need to do more research on making medicine more effective. Besides, the review article is useful for treating patients effectively by advancing the research.

Aims and Objectives: The intake of Stachys sieboldii MIQ. has been associated with relieving inflammation and maintaining optimal gut health function. We investigated the diversity and composition of microflora in feces of S. sieboldii MIQ.-fed mice. In addition, we evaluated the production of major cytokines (Interleukin-6 and -10) related to inflammation and fatty acid composition of several tissues. Materials and Methods: 16S ribosomal DNA sequencing-based microbiome taxonomic profiling analysis was performed using EzBioCloud data base. The total RNA from the mesenteric lymph node was isolated and then synthesized with prime script 1st strand cDNA synthesis kit. Quantitative real-time PCR was performed on cDNA samples using the SYBR™ Green PCR Master Mix. Results: Mice fed on S. sieboldii MIQ. showed significantly reduced counts of aerobic and coliform in the feces compared with control. 16S rDNA sequencing analysis of fecal samples showed that supplementation with S. sieboldii MIQ. increased beneficial intestinal microflora (Ruminococcaceae and Akkermansia muciniphila) and decreased the community of harmful microflora (Enterobacteriaceae, including Escherichia coli and Bacteroides sp.) in feces compared with that in the control (P<0.05 for all). Mice showed a significantly lower mRNA expression of cytokines IL-6 and IL-10 in mesenteric lymph node compared with that in control (P<0.05). The fecal fatty acid composition in the S. sieboldii MIQ. group showed a higher percentage of 6:0 and 18:2n-6 compared with that in the control group (P<0.05). The percentages of 6:0 and 20:3n-6 fatty acids were also significantly higher in the intestines of S. sieboldii MIQ. group (P<0.05). No differences were revealed between the two groups in terms of the percentages of total saturated, monounsaturated, n-6 and n-3 polyunsaturated fatty acids found in feces and tissues. Conclusion: The present results showed that supplementation of mice with S. sieboldii MIQ. increased beneficial gut microflora and decreased harmful microflora. Moreover, lower mRNA expression of pro-inflammatory cytokine IL-6, and anti-inflammatory cytokine IL-10 in the mesenteric lymph node of supplemented mice might be associated with the lower abundances of harmful fecal microflora.

Background: MicroRNAs (miRs) have been shown to play important roles in various cancers and may be a reliable prognostic marker. However, its prognostic value in endometrial carcinoma (UCEC) needs to be further explored. Objectives: The aim of this study was to create a miR-based signature to effectively predict the prognosis for patients with uterine corpus endometrial carcinoma (UCEC). Methods: Using UCEC data set in TCGA, we identified differentially expressed miRs between UCEC and healthy endometrial tissues. The LASSO method was used to construct a miR-based signature prognosis index for predicting prognosis in the training cohort. The miR-based signature prognosis index was validated in an independent test cohort. MiRNet tool was applied to perform functional enrichment analysis of this miR-based signature. Results: A total of 208 miRs were differentially expressed between UCEC and healthy endometrial tissues. Five miRs (miR-652, miR-3170, miR-195, miR-34a, and miR-934) were identified to generate a prognosis index (PI). The five-miR signature is a promising biomarker for predicting the 5-year-survival rate of UCEC with AUC = 0.730. The PI remained an independent prognostic factor adjusted by routine clinicopathologic factors. Using the PI, we could successfully identify the high-risk individuals, furthermore, it still worked in an independent test cohort. The five miRs involved in various pathways associated with cancer. Conclusion: We proposed and validated a five-miR signature that could serve as an independent prognostic predictor of UCECs.

Objective: Considering the molecular complexity and heterogeneity of rheumatoid arthritis (RA), the identification of novel molecular contributors involved in RA initiation and progression using systems biology approaches will open up potential therapeutic strategies. The bioinformatics method allows the detection of associated miRNA-mRNA as both therapeutic and prognostic targets for RA. Methods: This research used a system biology approach based on a systematic re-analysis of the RA-related microarray datasets in the NCBI Gene Expression Omnibus (GEO) database to find out deregulated miRNAs. We then studied the deregulated miRNA-mRNA using Enrichr and Molecular Signatures Database (MSigDB) to identify novel RA-related markers followed by an overview of miRNA-mRNA interaction networks and RA-related pathways. Results: This research mainly focused on mRNA and miRNA interactions in all tissues and blood/serum associated with RA to obtain a comprehensive knowledge of RA. Recent systems biology approach analyzed seven independent studies and presented important RA-related deregulated miRNAs (miR-145-5p, miR-146a-5p, miR-155-5p, miR-15a-5p, miR-29c-3p, miR- 103a-3p, miR-125a-5p, miR-125b-5p, miR-218); upregulation of miR-125b is shown in the study (GSE71600). While the findings of the Enrichr showed cytokine and vitamin D receptor pathways and inflammatory pathways. Further analysis revealed a negative correlation between the vitamin D receptor (VDR) and miR-125b in RA-associated gene expression. Conclusion: Since vitamin D is capable of regulating the immune homeostasis and decreasing the autoimmune process through its receptor (VDR), it is regarded as a potential target for RA. According to the results obtained, a comparative correlation between negative expression of the vitamin D receptor (VDR) and miR-125b was suggested in RA. The increasing miR-125b expression would reduce the VitD uptake through its receptor.

Aim and Objectives: The focus of the present work is to synthesize ZnO/C composite using dextrose as carbon source by combustion method and study the comparative evaluation on one-pot synthesis of β-acetamido- β-(phenyl) propiophenone over ZnO nanoparticles and ZnO/C composite catalyst. Materials and Methods: The ZnO nanoparticles has been synthesized by sol-gel method using zinc nitrate and NaOH and ZnO/Carbon composites by combustion method using zinc nitrate and dextrose as carbon source. The resulting gel was placed in a preheated muffle furnace at 400oC. The solution boils and ignites with a flame. On cooling highly amorphous powder of ZnO/Carbon composite is obtained. Results: The XRD patterns reveal the hexagonal phase with Wurtzite structure and the nanocrystalline nature of the catalysts. The SEM image of ZnO/C composite showed that it contains spherical particles with an average size of 41 nm. The average particle size of the composite was around 60nm by DLS method. The catalytic activity of the ZnO/Carbon composites has been analyzed by one-pot four-component condensation of benzaldehyde, acetophenone, acetyl chloride and acetonitrile. The feed molar ratio of 1:1 (Bz:AP) and catalyst loading of 30 mol% is found to be the optimal condition for β-acetamido ketone conversion over ZnO/carbon composite. Conclusion: The substantial catalytic activity of the synthesized ZnO/C composite materials was tested by one-pot four-component condensation of benzaldehyde (Bz), acetophenone (AP), acetyl chloride (AC) and acetonitrile (AN) which showed a high β-acetamido ketone conversion under the optimized reaction conditions. It has also been found that the catalyst is very stable and reusable.

Background: Several compounds have been synthesized as a therapeutic alternative for heart failure; however, its preparation requires special conditions. Objective: The aim of this study, was to synthesize some aniline derivatives (4-9) from 3- ethynylaniline to evaluate their biological activity against heart failure. Methods: The synthesis of aniline derivatives involved a series of reactions such as etherification, addition, and cyclization. The structure of all compounds obtained was confirmed by spectroscopic and spectrometric methods. In addition, to evaluate the biological activity of compounds, an ischemia/reperfusion injury model was used. Results: The results showed that compound 8 decreases heart failure, which translates into a decrease in the infarction area compared to compounds 4-7 and 9. Conclusion: This study reports a facile method for the preparation of aniline derivatives. This method offers some advantages such as; a simple procedure, low cost, and easy work up. In addition, compound 8 showed an interesting biological activity against heart failure. This phenomenon is particularly interesting because the biological activity induced by this compound could involve a molecular mechanism that is different from other drugs used for the treatment of heart failure.

Background: Endometrial cancer (EC) is a common gynecological malignancy worldwide. Immunity is closely related to the occurrence and prognosis of EC. At the same time, immune-related genes have great potential as prognostic markers in many types of cancer. Objective: Therefore, we attempt to develop immune-related gene markers to enhance prognosis prediction of EC. Methods: 542 samples of EC gene expression data and clinical follow-up information were downloaded from The Cancer Genome Atlas (TCGA). The samples were randomly divided into two groups, one group as a training set (N=271), and one set as a validation set. (N=271). In the training set, the gene pairs were established based on the relative expression levels of 271 immune genes, and the prognosis-related gene pairs were screened. The lasso was used to select the features, and finally, the robust biomarkers were screened. Finally, the prognostic model of the immune gene pair was established and verified by the validation data set. Results: 10030 immune gene pair (IRGPs) were obtained, and univariate survival analysis was used to identify 1809 prognostic-related IRGPs (p<0.05). 5-IRGPs were obtained by lasso regression feature selection, and multivariate regression was used to establish 5-IRGPs signature, 5-IRGPs signature is an independent prognostic factor for EC patients, and could be risk stratified in patients with TCGA datasets, age, ethnicity, stage, and histological classification (p<0.05). The mean AUC of survival in both the training set and the validation set was greater than 0.7, indicating that 5-IRGPs signature has superior classification performance in patients with EC. In addition, 5-IRGPs have the highest average C index (0.795) compared to the prognostic characteristics of the three endometrial cancers reported in the past and Stage and Age. Conclusion: This study constructed a 5-IRGPs signature as a novel prognostic marker for predicting survival in patients with EC.

Aims: The main aim of the study was to examine the feasibility and benefits of adsorption onto multi-walled carbon nanotubes (MWCNTs) coupled with cloud point extraction (CPE) for the removal of Rhodamine B (RB) from aqueous solutions. Background: MWCNTs offer the particular features of the ideal adsorbents for the organic dyes such as hollow tubular structure and specific surface area. Nevertheless, they suffer from the drawbacks of low dispersion in the aqueous solutions and separation inconvenience from the media. Cloud point extraction, combined with the adsorption onto MWCNTs can be a promising method to overcome the problems. Objective: In the study, adsorption onto MWCNTs coupled with CPE was applied for RB removal from aqueous solutions. The process was optimized by the response surface modeling method. Moreover, the applicability of the proposed method in the real sample analyses was investigated. Methods: MWCNTs were used as adsorbent and Triton X-100 (TX-100) as the nonionic surfactant for CPE process. The experiments were carried out based on a Box-Behnken design (BBD) with the input variables of MWCNTs dosage (0.6-1.2 mg), solution pH (3-9), clouding time (20-40 min) and TX-100 concentration (10-20 v/v%) using 5 mg L-1 RB solutions. Result: Regression analyses resulted in a statistically significant quadratic model (R²=0.9718, F=24.96, p<0.0001) by which the optimum levels of the variables were predicted as: MWCNTs dosage of 0.7 mg, pH=3, clouding time of 39.9 minutes and TX-100 concentration of 19.91% (v/v). The predicted conditions were experimentally validated by achieving an RB removal of 94.24%. Conclusion: Based on the results, the combination of the environmentally friendly technique of CPE with adsorption onto MWCNTs allows the efficient removal of RB from water samples and the method can be effectively optimized by the response surface modeling.

Aim And Objectives: Phytophthora infestans (Mont.) de Bary, the fungal pathogen causes late blight, which results in devastating economic loss among the Solanaceae. The bacillus lipopeptides show the antagonistic activity against the many plant pathogens, among bacillus lipopeptides reported as the antifungal gene. Hence, to understand the in silico antifungal activity, we have selected gene iturin A (AXN89987) produced by Bacillus spp to check the molecular dynamics study with the effector proteins of the P. infestanse. In this concern, known effector proteins of P. infestans were subjected to the protein-protein interaction followed by simulation. Materials and Methods: Iturin A gene was amplified using the soil bacterium Bacillus subtilis with gene-specific primers, cloned into pTZ 57R/T vector and confirmed by sequencing. To get better insights, the protein model was developed for Iturin A using Modeller 9.17, using PDB structure of ID 4MRT (Phosphopantetheine transferase Sfp) and 1QR0 (4’-phosphopantetheinyl moiety of coenzyme A) as a template, it shared the identity 72% and expected P-value: 3e-121, respectively. The model quality was assessed using ProSA and PROCHECK programs. Results: The potency of modelled protein against effector proteins of P. infestans were evaluated in silico using the HADDOCK server and the results showed the high affinity of towards the effector protein Host ATG8 (PDB-5L83). Finally, the simulation was performed to the docked conformation of with Host ATG8 to further understand the stability of the complex using the Desmond program. Conclusion: Altogether, the protein-protein interaction and simulation study propose a new methodology and to uncover possible antifungal activity of iturin A against effector proteins of P. infestans.

Background: Lung cancer is one of the malignancies exhibiting the fastest increase in morbidity and mortality, but the cause is not clearly understood. The goal of this investigation was to screen and identify relevant biomarkers of lung cancer. Methods: Publicly available lung cancer data sets, including GSE40275 and GSE134381, were obtained from the GEO database. The repeatability test for data was done by principal component analysis (PCA), and a GEO2R was performed to screen differentially expressed genes (DEGs), which were all subjected to enrichment analysis. Protein-protein interactions (PPIs), and the significant module and hub genes were identified via Cytoscape. Expression and correlation analysis of hub genes was done, and an overall survival analysis of lung cancer was performed. A receiver operating characteristic (ROC) curve analysis was performed to test the sensitivity and specificity of the identified hub genes for diagnosing lung cancer. Results: The repeatability of the two datasets was good and 115 DEGs and 10 hub genes were identified. Functional analysis revealed that these DEGs were associated with cell adhesion, the extracellular matrix, and calcium ion binding. The DEGs were mainly involved with ECM-receptor interaction, ABC transporters, cell-adhesion molecules, and the p53 signaling pathway. Ten genes including COL1A2, POSTN, DSG2, CDKN2A, COL1A1, KRT19, SLC2A1, SERPINB5, DSC3, and SPP1 were identified as hub genes through module analysis in the PPI network. Lung cancer patients with high expression of COL1A2, POSTN, DSG2, CDKN2A, COL1A1, SLC2A1, SERPINB5, and SPP1 had poorer overall survival times than those with low expression (p <0.05). The CTD database showed that 10 hub genes were closely related to lung cancer. Expression of POSTN, DSG2, CDKN2A, COL1A1, SLC2A1, SERPINB5, and SPP1 was also associated with a diagnosis of lung cancer (p<0.05). ROC analysis showed that SPP1 (AUC = 0.940, p = 0.000*, 95%CI = 0.930-0.973, ODT = 7.004), SLC2A1 (AUC = 0.889, p = 0.000*, 95%CI = 0.791-0.865, ODT = 7.123), CDKN2A (AUC = 0.730, p = 0.000*, 95%CI = 0.465-1.000, ODT = 6.071) were suitable biomarkers. Conclusion: Microarray technology represents an effective method for exploring genetic targets and molecular mechanisms of lung cancer. In addition, the identification of hub genes of lung cancer provides novel research insights for the diagnosis and treatment of lung cancer.

Aim and Objective: Sleep bruxism is a complicated disease, and its cause remains controversial. If the etiology of bruxism is resolved, the treatment can be adjusted to the prevailing aetiological factor. Thus, the aim of this study was to evaluate the oxidative stress level and serum prolidase activity in patients with sleep bruxism. Materials and Methods: Seventy healthy subjects and 51 patients with sleep bruxism were included in this study, and blood samples from all patients were collected. Serum samples were analyzed for total antioxidant status (TAS), total oxidant status (TOS), oxidative stress index (OSI), and prolidase activity. Results: The prolidase, TOS, and OSI levels were significantly higher in patients with bruxism than in the healthy controls (p = 0.001, p = 0.001, p = 0.001, respectively). The TAS level was significantly lower in bruxism patients than in healthy controls (p = 0.003). Conclusion: The increased TOS, OSI, and prolidase levels and decreased TAS levels could be assumed to result in oxidative injury in patients with sleep bruxism. However, the study could not determine whether oxidative imbalance and increased serum prolidase levels could be a cause or a result of bruxism.

Aim and Objective: Maxingyigan (MXYG) decoction is a traditional Chinese medicine (TCM) prescription. However, how MXYG acts against coronavirus disease 2019 (COVID-19) is not known. We investigated the active ingredients and the therapeutic targets of MXYG decoction against COVID-19. Methods: A network pharmacology strategy involving drug-likeness evaluation, prediction of oral bioavailability, network analyses, and virtual molecular docking was used to predict the mechanism of action of MXYG against COVID-19. Results: Thirty-three core COVID-19-related targets were identified from 1023 gene targets through analyses of protein–protein interactions. Eighty-six active ingredients of MXYG decoction hit by 19 therapeutic targets were screened out by analyses of a compound–compound target network. Via network topology, three “hub” gene targets (interleukin (IL-6), caspase-3, IL-4) and three key components (quercetin, formononetin, luteolin) were recognized and verified by molecular docking. Compared with control compounds (ribavirin, arbidol), the docking score of quercetin to the IL-6 receptor was highest, with a score of 5. Furthermore, the scores of three key components to SARS-CoV-2 are large as 4, 5, and 5, respectively, which are even better than those of ribavirin at 3. Bioinformatics analyses revealed that MXYG could prevent and treat COVID-19 through anti-inflammatory and immunity-based actions involving activation of T cells, lymphocytes, and leukocytes, as well as cytokine-cytokine-receptor interaction, and chemokine signaling pathways. Conclusion: The hub genes of COVID-19 helped to reveal the underlying pathogenesis and therapeutic targets of COVID-19. This study represents the first report on the molecular mechanism of MXYG decoction against COVID-19.

Background: As a well-known herb used in the treatment of colon adenocarcinoma (COAD), Spica Prunellae (SP) shows favorable clinical effect and safety in China for many years, but its active ingredients and therapeutic mechanisms against COAD remain poorly understood. Therefore, this study aims to uncover active ingredients and mechanisms of SP in the treatment of COAD using a combined approach of network pharmacology and bioinformatics. Methods: A comprehensive approach mainly comprised of target prediction, network construction, pathway and functional enrichment analysis, and hub genes verification was adopted in the current study. Results: We collected 102 compounds-related genes and 3549 differently expressed genes (DEGs) following treatment with SP, and 64 disease-drug target genes between them were recognized. In addition, a total of 25 active ingredients in SP were identified. Pathway and functional enrichment analyses suggested that the mechanisms of SP against COAD might be to induce apoptosis of colon cancer cells by regulating PI3K-Akt and TNF signaling pathways. Recognition of hub genes and core functional modules was performed by constructing protein-protein interaction (PPI) network, from which TP53, MYC, MAPK8 and CASP3 were found as the hub target genes that might play an important part in therapy for COAD. Subsequently we further compared the differential expression level and assessed the prognostic value of these four hub genes. These result of verification suggested that SP exerted therapeutic effects against COAD via a PPI network involving TP53, MYC, MAPK8 and CASP3. Conclusion: In this study, active ingredients and mechanisms of SP in the treatment of COAD were systematically discussed, which provided the foundation for further experimental studies and might act to promote its appropriate clinical application.

Background: Complications are the main cause of the disease burden of diabetes. Genes determining the development and progression of diabetic complications remain to be identified. Diabetic neuropathy is the most common and debilitating complication and mainly affects the nerves of legs and feet. In this study, we attempted to identify diabetic neuropathy-specific genes from reliable large-scale genome-wide association studies (GWASs) for diabetes perse. Methods: Taking advantage of publicly available data, we initially converted the GWAS signals to transcriptomic profiles in the tibial nerve using the functional summary-based imputation (FUSION) algorithm. The FUSION-derived genes were then checked to determine whether they were differentially expressed in the sciatic nerve of mouse models of diabetic neuropathy. The dysregulated genes identified in the sciatic nerve were explored in the blood of patients with diabetes. Results: We found that eleven out of 452 FUSION-derived genes were regulated by diabetes GWAS loci and were altered in the sciatic nerve of mouse models with early-stage neuropathy. Among the eleven genes, significant (P-value<0.05) expression alterations of HSD17B4, DHX32, MERTK, and SFXN4 could be detected in the blood of human patients. Conclusions: Our analyses identified genes with an effect in the sciatic nerve and provided the possibility of noninvasive early detection of diabetic neuropathy.