Combinatorial Chemistry & High Throughput Screening - Volume 24, Issue 5, 2021

Cervical malignancy is known as one of the important cancers which is originated from cervix. This malignancy has been observed in women infected with papillomavirus who had regular oral contraceptives, multiple pregnancies, and sexual relations. Early and fast cervical cancer diagnosis is known as two important aspects of cervical cancer therapy. Several investigations indicated that early and fast detection of cervical cancer could be associated with better treatment process and increasing survival rate of patients with this malignancy. Imaging techniques are very important diagnosis tools that could be employed for diagnosis and following responses to therapy in various cervical cancer stages. Multiple lines of evidence indicated that utilization of imaging techniques is related to some limitations (i.e. high cost, and invasive effects). Hence, it seems that along with using imaging techniques, finding and developing new biomarkers could be useful in the diagnosis and treatment of subjects with cervical cancer. Taken together, many studies showed that a variety of biomarkers including, several proteins, mRNAs, microRNAs, exosomes and polymorphisms might be introduced as prognostic, diagnostic and therapeutic biomarkers in cervical cancer therapy. In this review article, we highlighted imaging techniques as well as novel biomarkers for the diagnosis of cervical cancer.

Background: Genus Berberis (family Berberidaceae), which contains about 650 species and 17 genera worldwide, has been used in folklore and various traditional medicine systems. Berberis Linn. is the most established group among genera with around 450-500 species across the world. This comprehensive review will not only help researchers for further evaluation but also provide substantial information for future exploitation of species to develop novel herbal formulations. Objective: The present review is focussed to summarize and collect the updated review of information of Berberis species reported to date regarding their ethnomedicinal information, chemical constituents, traditional/folklore use, and reported pharmacological activities on more than 40 species of Berberis. Conclusion: A comprehensive survey of the literature reveals that various species of the genus possess various phytoconstituents mainly alkaloids, flavonoid based compounds isolated from different parts of a plant with a wide range of pharmacological activities. So far, many pharmacological activities like anti-cancer, anti-hyperlipidemic, hepatoprotective, immunomodulatory, antiinflammatory both in vitro and in vivo and clinical study of different extracts/isolated compounds of different species of Berberis have been reported, proving their importance as a medicinal plant and claiming their traditional use.

Background: Diabetes is a chronic metabolic disease characterized by disorders of glucose and lipid metabolism. Its most serious microvascular complication is diabetic nephropathy (DN), which is characterized by varying degrees of proteinuria and progressive glomerulosclerosis, eventually progressing to end-stage renal failure. Objective: The aim of this research is to identify hub genes that might serve as genetic markers to enhance the diagnosis, treatment, and prognosis of DN. Methods: The procedures of the study include access to public data, identification of differentially expressed genes (DEGs) by GEO2R, and functional annotation of DEGs using enrichment analysis. Subsequently, the construction of the protein-protein interaction (PPI) network and identification of significant modules were performed. Finally, the hub genes were identified and analyzed, including clustering analysis, Pearson’s correlation coefficient analysis, and multivariable linear regression analysis. Results: Between the GSE30122 and GSE1009 datasets, a total of 142 DEGs were identified, which were mainly enriched in cell migration, platelet activation, glomerulus development, glomerular basement membrane development, focal adhesion, regulation of actin cytoskeleton, and the PI3K-AKT signaling pathway. The PPI network was composed of 205 edges and 142 nodes. A total of 10 hub genes (VEGFA, NPHS1, WT1, PODXL, TJP1, FYN, SULF1, ITGA3, COL4A3, and FGF1) were identified from the PPI network. Conclusion: The DEGs between DN and control glomeruli samples may be involved in the occurrence and development of DN. It was speculated that hub genes might be important inhibitory genes in the pathogenesis of diabetic nephropathy, therefore, they are expected to become the new gene targets for the treatment of DN.

Background: Hepatocellular carcinoma (HCC) is a common type of cancer with a high mortality rate and is usually detected at the middle or late stage, missing the optimal treatment period. The current study aims to identify potential long non-coding RNA (lncRNAs) biomarkers that contribute to the diagnosis and prognosis of HCC. Methods: The differentially expressed lncRNAs (DElncRNAs) in HCC patients were detected from the Cancer Genome Atlas (TCGA) dataset. LncRNAs signature was screened by LASSO regression, univariate, and multivariate Cox regression. The models for predicting diagnosis and prognosis were established, respectively. The prognostic model was evaluated by Kaplan-Meier survival curve receiver operating characteristic (ROC) curve and stratified analysis. The diagnostic model was validated by ROC. The lncRNAs signature was further demonstrated by functional enrichment analysis. Results: We found the 13-lncRNAs signature that had a good performance in predicting prognosis and could help to improve the value of diagnosis. In the training set, testing set, and entire cohort, the low-risk group had longer survival than the high-risk group (median OS: 3124 vs. 649 days, 2456 vs. 770 days and 3124 vs. 755 days). It performed well in 1-, 3-, and 5-year survival prediction. 13-lncRNAs-based risk score, age, and race were good predictors of prognosis. The AUC of diagnosis was 0.9487, 0.9265, and 0.9376, respectively. Meanwhile, the 13-lncRNAs were involved in important pathways, including the cell cycle and multiple metabolic pathways. Conclusion: In our study, the 13-lncRNAs signature may be a potential marker for the prognosis of HCC and improve the diagnosis.

Background: Diabetes mellitus is one of the most common endocrine metabolic disorder- related diseases. The application of herbal medicine to control glucose levels and improve insulin action might be a useful approach in the treatment of diabetes. Mulberry leaves (ML) have been reported to exert important activities of anti-diabetic. Objective: In this work, we aimed to explore the multi-targets and multi-pathways regulatory molecular mechanism of Mulberry leaves (ML, Morus alba Linne) acting on diabetes. Methods: Identification of active compounds of Mulberry leaves using Traditional Chinese Medicine Systems Pharmacology (TCMSP) database was carried out. Bioactive components were screened by FAF-Drugs4 website (Free ADME-Tox Filtering Tool). The targets of bioactive components were predicted from SwissTargetPrediction website, and the diabetes related targets were screened from GeneCards database. The common targets of ML and diabetes were used for Gene Ontology (GO) and pathway enrichment analysis. The visualization networks were constructed by Cytoscape 3.7.1 software. The biological networks were constructed to analyze the mechanisms as follows: (1) compound-target network; (2) common target-compound network; (3) common targets protein interaction network; (4) compound-diabetes protein-protein interactions (ppi) network; (5) target-pathway network; and (6) compound-target-pathway network. At last, the prediction results of network pharmacology were verified by molecular docking method. Results: 17 active components were obtained by TCMSP database and FAF-Drugs4 website. 51 potential targets (11 common targets and 40 associated indirect targets) were obtained and used to build the PPI network by the String database. Furthermore, the potential targets were used for GO and pathway enrichment analysis. Eight key active compounds (quercetin, Iristectorigenin A, 4- Prenylresveratrol, Moracin H, Moracin C, Isoramanone, Moracin E and Moracin D) and 8 key targets (AKT1, IGF1R, EIF2AK3, PPARG, AGTR1, PPARA, PTPN1 and PIK3R1) were obtained to play major roles in Mulberry leaf acting on diabetes. And the signal pathways involved in the mechanisms mainly include AMPK signaling pathway, PI3K-Akt signaling pathway, mTOR signaling pathway, insulin signaling pathway and insulin resistance. The molecular docking results show that the 8 key active compounds have good affinity with the key target of AKT1, and the 5 key targets (IGF1R, EIF2AK3, PPARG, PPARA and PTPN1) have better affinity than AKT1 with the key compound of quercetin. Conclusion: Based on network pharmacology and molecular docking, this study provided an important systematic and visualized basis for further understanding of the synergy mechanism of ML acting on diabetes.

Background: Nanoscale metal oxide catalysts have been extensively employed in organic reactions because they have been found to influence the chemical and physical properties of bulk material. The chromene (benzopyran) nucleus constitutes the core structure in a major class of many biologically active compounds, and interest in their chemistry consequently continues because of their numerous biological activities. The xanthene (dibenzopyran) derivatives are classified as highly significant compounds which display a number of various bioactive properties. Pyrimidinones have also gained interest due to their remarkable biological utilization, such as antiviral, antibacterial, antihypertensive, antitumor, and calcium blockers effects. Objective: The aim of this work presented herein was to prepare activated carbon/MoO3 nanocomposite and explore its role as a green and recyclable catalyst for the synthesis of chromeno[d]pyrimidinediones and xanthenones under ethanol-drop grinding at room temperature. Methods: The activated carbon/MoO3 nanocomposite was prepared successfully via a simple route in which the carbonization of gums as new natural precursors was used for the synthesis of activated carbon. This nanocomposite was then effectively used in a reaction of 3,4-methylenedioxyphenol, aromatic aldehydes, and active methylene compounds, including 1,3-dimethylbarbituric acid and dimedone, to synthesize a series of chromeno[d]pyrimidinediones and xanthenones in high yields. The synthesized catalyst was characterized by Fourier transform infrared spectroscopy (FT-IR), Powder x-ray diffractometry (XRD), Scanning electron microscope (SEM), Raman spectroscopy, and also by TGA analysis. Confirmation of the structures of compounds 5(a-g) and 6(a-g) were also established with IR, 1H NMR, and 13C NMR spectroscopic data and also by elemental analyses. Results: A number of 6,8-dimethyl-10-phenyl-6,10-dihydro-7H-[1,3]dioxolo[4´,5´:6,7]chromeno[2,3- d]pyrimidine-7,9(8H)-diones and 7,7-dimethyl-10-(4-methylphenyl)-6,7,8,10-tetrahydro-9H-[1,3]dioxolo[ 4,5-b]xanthen-9-ones were effectively synthesized using activated carbon/MoO3 nanocomposite (0.05 gr) as a catalyst under ethanol-drop grinding at room temperature. The desired products were obtained in high yields (93-97%) within short reaction times (15-20 min). Conclusion: This paper investigates the catalytic potential of the synthesized activated carbon/MoO3 nanocomposite for the preparation of chromeno[d]pyrimidinediones and xanthenones under the ethanol-drop grinding procedure. The mildness of the reaction conditions, high yields of products, short reaction times, experimental simplicity, and avoiding the use of harmful solvents or reagents makes this procedure preferable for the synthesis of these compounds.

Aims and Objectives: Microwave-assisted condensation of acetophenone 1 and aromatic aldehydes 2 gave chalcone analogs 3, which were cyclized to pyrazole derivatives 6a-f via the reaction with hydrazine hydrate and oxalic acid in the presence of the catalytic amount of acetic acid in ethanol. Materials and Methods: The structural features of the synthesized compounds were characterized by melting point, FT-IR, ¹H, ¹³C NMR and elemental analysis. Results: The antibacterial activities of the synthesized pyrazoles were evaluated against three gram-positive bacteria, such as Enterococcus durans, Staphylococcus aureus, Bacillus subtilis and two gram-negative bacteria such as Escherichia coli and Salmonella typhimurium. Conclusion: All the synthesized pyrazoles showed relatively high antibacterial activity against S. aureus strain, and none of them demonstrated antibacterial activity against E. coli.

Background and Objective: Qishen Yiqi formula (QSYQ) is used to treat cardiovascular disease in the clinical practice of traditional Chinese medicine. However, few studies have explored whether QSYQ affects pulmonary arterial hypertension (PAH), and the mechanisms of action and molecular targets of QSYQ for the treatment of PAH are unclear. A bioinformatics/network topology-based strategy was used to identify the bioactive ingredients, putative targets, and molecular mechanisms of QSYQ in PAH. Methods: A network pharmacology-based strategy was employed by integrating active component gathering, target prediction, PAH gene collection, network topology, and gene enrichment analysis to systematically explore the multicomponent synergistic mechanisms. Results: In total, 107 bioactive ingredients of QSYQ and 228 ingredient targets were identified. Moreover, 234 PAH-related differentially expressed genes with a |fold change| >2 and an adjusted P value < 0.005 were identified between the PAH patient and control groups, and 266 therapeutic targets were identified. The pathway enrichment analysis indicated that 85 pathways, including the PI3K-Akt, MAPK, and HIF-1 signaling pathways, were significantly enriched. TP53 was the core target gene, and 7 other top genes (MAPK1, RELA, NFKB1, CDKN1A, AKT1, MYC, and MDM2) were the key genes in the gene-pathway network based on the effects of QSYQ on PAH. Conclusion: An integrative investigation based on network pharmacology may elucidate the multicomponent synergistic mechanisms of QSYQ in PAH and lay a foundation for further animal experiments, human clinical trials and rational clinical applications of QSYQ.

Aims: To predict potential drugs for COVID-19 by using molecular docking for virtual screening of drugs approved for other clinical applications. Background: SARS-CoV-2 is the betacoronavirus responsible for the COVID-19 pandemic. It was listed as a potential global health threat by the WHO due to high mortality, high basic reproduction number, and lack of clinically approved drugs and vaccines. The genome of the virus responsible for COVID-19 has been sequenced. In addition, the three-dimensional structure of the main protease has been determined experimentally. Objective: To identify potential drugs that can be repurposed for treatment of COVID-19 by using molecular docking based virtual screening of all approved drugs. Methods: A list of drugs approved for clinical use was obtained from the SuperDRUG2 database. The structure of the target in the apo form, as well as structures of several target-ligand complexes, were obtained from RCSB PDB. The structure of SARS-CoV-2 Mpro determined from X-ray diffraction data was used as the target. Data regarding drugs in clinical trials for COVID-19 was obtained from clinicaltrials.org. Input for molecular docking based virtual screening was prepared by using Obabel and customized python, bash, and awk scripts. Molecular docking calculations were carried out with Vina and SMINA, and the docked conformations were analyzed and visualized with PLIP, Pymol, and Rasmol. Results: Among the drugs that are being tested in clinical trials for COVID-19, Danoprevir and Darunavir were predicted to have the highest binding affinity for the Main protease (Mpro) target of SARS-CoV-2. Saquinavir and Beclabuvir were identified as the best novel candidates for COVID-19 therapy by using Virtual Screening of drugs approved for other clinical indications. Conclusion: Protease inhibitors approved for treatment of other viral diseases have the potential to be repurposed for treatment of COVID-19.

Background: Alzheimer’s disease is a neurological condition causing cognitive inability and dementia. The pathological lesions and neuronal damage in the brain are caused by self-aggregated fragments of mutated Amyloidal precursor protein (APP). Objective: The controlled APP processing by inhibition of secretase is the strategy to reduce Aβ load to treat Alzheimer’s disease. Methods: A QSAR study was performed on 55 Pyrrolidine based ligands as BACE-1 inhibitors with an activity magnitude greater than 4 of compounds. Results: In the advent of designing new BACE-1 inhibitors, the pharmacophore model with correlation (r = 0.90) and root mean square deviation (RMSD) of 0.87 was developed and validated. Further, the hits retrieved by the in-silico approach were evaluated by docking interactions. Conclusion: Two structurally diverse compounds exhibited Asp32 and Thr232 binding with the BACE-1 receptor. The aryl-substituted carbamate compound exhibited the highest fit value and docking score. The biological activity evaluation by in-vitro assay was found to be >0.1μM.

Background: The presence of plasmid mediated mcr-1 gene in multidrug resistant Gram-negative bacteria poses a serious public health concern in today’s world. Objective: The present study was aimed to detect the presence of plasmid mediated mcr-1 encoding resistance to colistin in multiple drug resistant (MDR) E. coli and K. pneumoniae isolates. Methods: A total of 180 clinical isolates of E. coli (n=120) and K. pneumoniae (n=60) were isolated from different clinical specimens, i.e., urine, blood, stool and pus, from diagnostic labs of two major public sector tertiary care hospitals in Peshawar, Pakistan. MDR profile of these isolates was assessed through Kirby-Baur disc diffusion method. All isolates were screened for colistin resistance by dilution methods. Colistin resistant isolates were subjected to PCR for mcr-1 detection and confirmation was done by Sanger sequencing method. Results: Overall, 83.3% (100/120) E. coli and 93.3% (56/60) K. pneumoniae were detected as MDR. Colistin resistance was found in 23.3% (28/120) E. coli and 40% (24/60) K. pneumoniae isolates, whereas mcr-1 gene was detected in 10 out of 52 colistin resistant isolates, including six E. coli and four K. pneumoniae isolates. Minimum inhibitory concentrations (MICs) of colistin in these ten mcr-1 positive isolates ranged from 4μg/ml to 16μg/ml. All mcr-1 positive isolates showed 99% sequence similarity when compared with other present sequences in GenBank. Conclusion: Hence, our study confirms the presence of mcr-1 mediated colistin resistance in the studied area. Therefore, urgently larger scale surveillance studies are recommended to investigate prevalence of mcr-1 mediated colistin resistance and to prevent its further spread in the area.