Combinatorial Chemistry & High Throughput Screening - Volume 26, Issue 7, 2023

The present COVID-19 pandemic is terrible for the respiratory system and is caused by severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2). It has affected millions of people globally and over 511.9 million cases and 6.2 million deaths have been reported across the world. Various drugs have been repurposed, however, no specific medicine has been approved by the FDA to combat this disease till date. In this condition, researchers have been attracted to natural and safe products to improve immunity to viral infections through inhibiting viral cell entry, replication, and modulation. Various natural products, probiotics, and nutrients have antimicrobial, antiviral, analgesic, anti-inflammatory, and antiproliferative activities, and some of the compounds are also utilized in traditional medicine in Ayurveda, Siddha, and other cultures. This review provides a clinical perspective on the application of herbs for the prevention of viral infections.

MicroRNAs (miRNAs) are small non-coding RNAs 19-25 nucleotides in size involved in gene regulation and diverse processes in tumor cells. Abnormal expression of miRNAs is closely related to carcinogenesis. MiR-96 is a salient cancer-related miRNA in a variety of tumors. Recent evidence indicates that miR-96 has been observed to be wrapped in exosome and associated with drug resistance or radio-chemosensitivity in cancers. miR-96 is also inextricably linked with the competing endogenous RNAs (ceRNAs) in cancers. Notably, miR-96 plays both a tumor suppressor role and plays a carcinogenic role in the same cancers. This review summarizes the critical role of cancer-related miR-96 in drug resistance or radio-chemosensitivity and ceRNA mechanisms of miR-96 in cancer. And we innovatively propose that miR-96 has a yin-yang effect in cancers. Based on these several major roles of miR-96 in cancer as described above, we speculate that the abnormal expression of miR-96 is likely to be novel potential therapeutic targets in cancers. It is expected to solve the treatment problems such as low chemoradiotherapy sensitivity, poor prognosis quality of life and easy recurrence in cancer patients.

Background: Liver Hepatocellular Carcinoma (LIHC) is characterized by high malignancy, poor prognosis, and high recurrence rate worldwide. The role of ferroptosis in tumorigenesis and progression has been confirmed in previous studies. However, the multi-omics analysis in liver cancer of ferroptosis-markers RPL8 remains to be elucidated. Methods: In this analysis, the RPL8 mRNA expression was analyzed via the GEPIA, TIMER and UALCAN databases. In addition, we verified the mRNA expression of RPL8 by qRT-PCR experiment. The Kaplan-Meier plotter, UALCAN, TCGAportal and HPA databases were applied to evaluate RPL8 on prognosis and clinicopathological parameters. Moreover, we used TIMER and Kaplan-Meier plotter to analyze the correlation of RPL8 to immune cell infiltration and immune cell type markers to prognosis. In addition, networks and function enrichment between RPL8 coexpression genes were analyzed by GeneMANIA, cBioportal and Metascape databases. What’s more, we used FerrDb and GEPIA databases to analyze the correlation of 23 Ferroptosis-related genes with RPL8. Results: The mRNA expression of RPL8 was over-expressed in multiple cancers. In addition, transcription and translation levels of RPL8 in LIHC were significantly higher than normal tissues. Furthermore, higher expression of RPL8 was closely related to shorter OS in LIHC patients. The analysis of Kaplan-Meier plotter proved that RPL8 expression was related to stage, Sorafenib treatment, alcohol consumption and hepatitis virus. Moreover, the results showed that the methylation expression level of RPL8 was significantly associated with age, gender, grade, stage and TP53 mutation of LIHC. RPL8 and its co-expression genes were primarily involved in liver regeneration and immune system process. Immune infiltration analysis showed the RPL8 expression had positively correlated with immune cells and immune subtypes in LIHC. Furthermore, qRT-PCR experiment validated the expression difference of RPL8 in liver cancer. Conclusion: Our findings elucidated that ferroptosis-markers RPL8 may play an important role in prognosis, and significantly correlate with ferroptosis-related genes, it also revealed the potential of RPL8 as a novel therapeutic target for LIHC treatment and prognosis assessment.

Background: Hepatocellular Carcinoma (HCC) is one of the fastest-growing malignancies globally. The impact of surgical treatment is limited, and molecular targeted therapy has not yielded a consistent efficacy. This warrants for identification of novel molecular targets. The Anti- Silencing Function of 1B histone chaperone (ASF1B) was previously studied in numerous cancers. However, the understanding of its role in HCC is limited. Methods: The TIMER database was used to analyze the ASF1B expression in pan-cancer and paracarcinoma tissues. ASF1B expression in HCC was confirmed using the HCCDB database, Quantitative real-time PCR (q-PCR), and Western Blot (WB) assays. The relationship between clinicopathological parameters and ASF1B expression was analyzed using UALCAN, whereas the prognostic value of ASF1B was evaluated using the GEPIA database. Linkedomics and cBioPortal databases were used to validate the ASF1B co-expression associated with immune infiltration by the TIMER database. Moreover, cell proliferation after ASF1B-knockdown was determined through CCK8 and clone formation assays. Results: ASF1B was highly expressed in HCC tissues, and the expression levels were linked to tumor grade, race, and disease stage. Univariate and multivariate Cox models showed that ASF1B is an independent prognostic factor in HCC. CCK8 and clone formation assays demonstrated that ASF1B promotes cell proliferation. Gene co-expression analysis in Linkedomics demonstrated that HJURP, KIF2C, KIF4A, KIF18B, and KIFC1 expressions were closely associated with ASF1B and immune infiltrate cells. Conclusion: This study shows that ASF1B promotes the proliferation of HCC. Besides, ASF1B could be a potential prognostic biomarker for HCC patients.

Background: Pyroptosis is a novel form of programmed cell death in cancers, which regulates tumor cell invasion, proliferation, and metastasis, thereby affecting the prognosis of cancer patients. However, the role of Pyroptosis-Related Genes (PGs) in Hepatocellular Carcinoma (HCC) remains unclear. Methods: Somatic mutation, copy number variation, and expression of 41 PGs were assessed in HCC and normal liver from the TCGA dataset. The Least Absolute Shrinkage and Selection Operator (LASSO) was used to construct the prognostic model. K-M curves, ROC curves, nomograph, and univariate and multivariate Cox regression were conducted to evaluate the predictive value of PGs. Immune infiltration was analyzed by CIBERSOFT and ssGSEA algorithm. The expression of prognostic PGs was validated by qPCR. Results: Significant mutation and copy number variation of PGs were found in HCC. These genes were involved in an inflammatory response. In addition, 9 out of 41 PGs were differentially expressed in HCC and found to correlate significantly with patient survival. Then, these signature genes were selected to build a prognosis model and were utilized to stratify HCC patients into high and low PGs-score groups. It showed that the high-PGs group had a worse prognosis. Univariate and multivariate Cox regression verified that PGs-score was an independent risk factor for HCC. By ROC curves and nomogram, we showed that PGs-score effectively predicted the 1-, 3-, and 5-year survival of HCC patients and correlated with AFP level and disease stage. Immune infiltration analysis further showed that tumor immunity correlated with the PGs-score, and the expression of immune checkpoint molecule was significantly enhanced in the high PGs group. The PGs-score was also validated in the external validation cohort (ICGC). Finally, the expression of 9 signature genes was validated in normal liver and HCC cell lines. Conclusion: This study elucidated the aberrant regulation of PGs in HCC, and those pyroptosisrelated genes may be applied as a prognostic factor of HCC.

Background: Dental pulp stem cells (DPSCs) refer to a type of stem cells, which is characterized by great differentiation potential and is easy to obtain. DPSCs are able to be employed for treating immune diseases and tissue regeneration. However, the differentiation ability exhibited by aging DPSCs is reduced, thereby limiting the application. As speculated by the microarray analysis, different expressions of miRNAs might be involved in DPSC senescence, whereas comprehensive transcriptome level detection has been rare. Objective and Methods: To gain insights into the molecular mechanisms involved, RNA-sequencing, pathway enrichment and Gene Ontology Analysis were conducted on aging and young DPSCs. Results: In this study, the differences in long non-coding RNA (lncRNA) and messenger RNA (mRNA expressions) of the aging and young DPSCs were demonstrated, and the vital factors and the relevant pathways were speculated. On the whole, 18950 mRNAs and 21854 lncRNAs were detected, among which 14 mRNAs and 7 lncRNAs were differentially expressed. Furthermore, hsa-miR-6724-5p may be a vital node in the aging process of DPSCs, and its target genes was involved in the dopaminergic synapse. Conclusion: In brief, the aging of DPSCs was significantly dependent of differentially expressed genes (DEGs) which is related to dopaminergic synapse. However, the specific function and internal relationship of the DEGs should be verified in depth.

Importance: Accurate pre-treatment prediction of distant metastasis in patients with Nasopharyngeal Carcinoma (NPC) enables the implementation of appropriate treatment strategies for high-risk individuals. Purpose: To develop and assess a Convolutional Neural Network (CNN) model using pre-therapy Magnetic Resonance (MR) imaging to predict distant metastasis in NPC patients. Methods: We retrospectively reviewed data of 441 pathologically diagnosed NPC patients who underwent complete radiotherapy and chemotherapy at Renmin Hospital of Wuhan University (Hubei, China) between February 2012 and March 2018. Using Adobe Photoshop, an experienced radiologist segmented MR images with rectangular regions of interest. To develop an accurate model according to the primary tumour, Cervical Metastatic Lymph Node (CMLN), the largest area of invasion of the primary tumour, and image segmentation methods, we constructed intratumoural and intra-peritumoural datasets that were used for training and test of the transfer learning models. Each model’s precision was assessed according to its receiver operating characteristic curve and accuracy. Generated high-risk-related Grad-Cams demonstrated how the model captured the image features and further verified its reliability. Results: Among the four models, all intra-peritumoural datasets performed better than the corresponding intratumoural datasets, with the CMLN intra-peritumoural dataset exhibiting the best performance (average area under the curves (AUCs) = 0.88). There was no significant difference between average AUCs of the Max and NPC tumour datasets. AUCs of the eight datasets for the four models were higher than those of the Tumour-Node-Metastasis staging system (AUC=0.67). In most datasets, the xception model had higher AUCs than other models. The efficientnet-b0 and xception models efficiently extracted high-risk features. Conclusion: The CNN model predicted distant metastasis in NPC patients with high accuracy. Compared to the primary tumour, the CMLN better predicted distant metastasis. In addition to intratumoural data, peritumoural information can facilitate the prediction of distant metastasis. With a larger sample size, datasets of the largest areas of tumour invasion may achieve meaningful accuracy. Among the models, xception had the best overall performance.

Background: Sorafenib is the most widely used systematic therapy drug for treating unresectable Hepatocellular Carcinoma (HCC) but showed dissatisfactory efficacy in clinical applications. Objective: We conducted a combinational quantitative small-molecule high-throughput screening (qHTS) to identify potential candidates to enhance the treatment effectiveness of sorafenib. Methods: First, using a Hep3B human HCC cell line, 7051 approved drugs and bioactive compounds were screened, then the primary hits were tested with/without 0.5 μM sorafenib respectively, the compound has the half maximal Inhibitory Concentration (IC50) shift value greater than 1.5 was thought to have the synergistic effect with sorafenib. Furthermore, the MEK inhibitor PD198306 was selected for the further mechanistic study. Results: 12 effective compounds were identified, including kinase inhibitors targeting MEK, AURKB, CAMK, ROCK2, BRAF, PI3K, AKT and EGFR, and a μ-opioid receptor agonist and a Ltype calcium channel blocker. The mechanistic research of the combination of sorafenib plus PD198306 showed that the two compounds synergistically inhibited MEK-ERK and mTORC1- 4EBP1 and induced apoptosis in HCC cells, which can be attributed to the transcriptional and posttranslational regulation of MCL-1 and BIM. Conclusion: Small-molecule qHTS identifies MEK inhibitor PD1938306 as a potent sorafenib enhancer, together with several novel combination strategies that are valuable for further studies.

Background: Nature has bestowed mother Earth with an array of herbals utilized as therapeutics for various human ailments since the origin of life. Bryonia laciniosa (family: Cucurbitaceae) is one such herb, which finds its mention in various traditional systems of medicine and has attracted current researchers due to its significant therapeutic value. Objective: The current article aims to present a literature metasynthesis on Bryonia laciniosa. Methods: The authors performed scholarly searches for peer-reviewed findings on Bryonia laciniosa and incorporated all the data related to the phytochemical and therapeutic profile of the drug. Results: This compilation comprises of Phytochemical and Pharmacological profile of Bryonia laciniosa elaborating its traditional significance and recent researches related to its biological activities. The plant exhibits its potential as an antimicrobial, anti-inflammatory, analgesic, antipyretic, anticonvulsant, anti-asthmatic, anticancer, antioxidant, antidiabetic, and aphrodisiac agent. It also displays its benefits in wound healing and ulcerative colitis. Conclusion: The presence of flavonoids, saponins, terpenoids, anthocyanins, coumarins, alkaloids, polyphenols, tannins and emodins in this plant is responsible for its various pharmacological activities. The retrospective study provides direction for existing research as well as future studies to support the domain of pharmaceutical and medical sciences.

Background: Psoriasis is an immune-mediated skin disorder caused by the proliferation of keratinocytes. Although psoriasis is generally diagnosed based on clinical manifestations, sensitive biomarkers are needed to help diagnose psoriasis early with atypical presentations. MicroRNAs play a functional role in the development of psoriasis, and they are stable and suitable as biomarkers in psoriasis. Material and Methods: The GSE50790 and GSE53552 datasets from the Gene Expression Omnibus (GEO) database were used to identify Differentially Expressed Genes (DEGs) between the control group and the lesional group. DEGs were processed for enrichment analysis to explore the functions, and a Protein-Protein Interaction (PPI) network was constructed to obtain gene clusters. The signalling pathway associated with gene cluster 1 was processed to further identify related genes. Hub genes were obtained through the intersection of cluster 1 and the related genes. Hub genes were used to predict the miRNAs through a gene-miRNA interaction network. The relative expression of miRNAs was measured by qRT-PCR to identify the suitability of miRNAs as biomarkers. Results: Bioinformatics analysis revealed that the chemokine signalling pathway is involved in the development of psoriasis. Five related miRNAs were mined from the datasets, and qRT-PCR showed that hsa-miR-612 (p=0.0015), hsa-miR-3194-5p (p=0.0078) and hsa-miR-4316 (p<0.0001) may be potential biomarkers in psoriasis.

Background: Ningnanmycin is a new antibiotic pesticide with good bactericidal and antiviral efficacy, which is widely used in the control of fruit and vegetable diseases, and the excessive pesticide residues pose a serious threat to the environment and human health. Methods: In this study, we used fluorescence spectrometer to scan the three-dimensional spectrum of ningnanmycin samples. We used a BP neural network to complete the regression analysis of content prediction based on the fluorescence spectra. After that, the prediction performance of the BP neural network was compared with the exponential fitting method. Results: The results of the BP neural network modeling based on the obtained samples showed that the mean square error of the prediction results of the test set is less than 10^-4, the R-square is greater than 0.99, the average recovery is 99.11%, and the model performance of the BP neural network is better than exponential fitting. Conclusion: Studies have shown that fluorescence spectroscopy combined with BP neural network can effectively predict the concentration of ningnanmycin.

Aim: The aim of the study was to explore the efficacy as well as the mechanism of action of Pitongshu (PTS) on rats with functional dyspepsia (FD) induced by iodoacetamide gavage and tail clamping. Methods: The bioactive components of PTS were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), whereas the potential targets of PTS were obtained from the Similarity Ensemble Approach (SEA), TCMSP, and Swiss Target Prediction Database. The disease targets were obtained from the DisGeNET database, whereas Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the R Software. The method of iodoacetamide gavage combined with tail clamping was used to establish the FD rat model in this study. Body weight, food intake, gastrointestinal motility, gastric acidity and secretion, and the mechanical pain threshold of rats were measured. The open-field test was also performed. The stomach and duodenum were histologically observed. The levels of serotonin (5-HT), Calcitonin Gene-Related Peptide (CGRP), Motilin (MTL), and Gastrin (GAS) in gastric tissues were detected by ELISA. Results: A total of 139 bioactive components and 17 potential targets of PTS were identified through a network pharmacology approach. The results of GO and KEGG enrichment analyses indicated that PTS could reduce the 5-HT secretion of gastric tissues through the serotonergic synaptic pathway and alleviate the symptoms of FD, indicating that PTS plays a therapeutic role. The results of animal experiments showed that PTS could increase body weight and food intake, improve autonomous activity, and decrease gastric acidity and secretion in FD rats. Furthermore, gastric sensitivity increased in FD rats, and PTS treatment could significantly decrease it. The results of ELISA showed that the overexpression of 5-HT and CGRP was decreased after PTS treatment in FD rats. Lastly, PTS could significantly improve gastrointestinal motility, as well as the levels of GAS and MTL in FD rats. Conclusion: PTS may reduce 5-HT secretion by regulating the serotonergic synaptic pathway, thereby reducing visceral sensitivity and alleviating the symptoms of FD.

Background: The lack of anti-COVID-19 treatment to date warrants urgent research into potential therapeutic targets. Virtual drug screening techniques enable the identification of novel compounds that target the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Main Protease (M^pro). Objective: The binding of the halogenated compounds to M^pro may inhibit the replication and transcription of SARS-CoV-2 and, ultimately, stop the viral life cycle. In times of dire need for anti- COVID-19 treatment, this study lays the groundwork for further experimental research to investigate these compounds' efficacy and potential medical uses to treat COVID-19. Methods: New heterocyclic compounds were synthesized through the first reaction of cyclohexane- 1, 3-dione (1a) or dimedone (1b) with trichloroacetonitrile (2) to give the 2,2,2-trichloroethylidene) cyclohexane-1,3-dione derivatives 3a and 3b, respectively. The latter compounds underwent a series of heterocyclization reactions to produce biologically active compounds. Results: Novel compounds, including fused thiophene, pyrimidine and pyran derivatives, were synthesized and tested against human RNA N7-MTase (hRNMT) and selected viral N7-MTases such as SARS-CoV nsp14 and Vaccinia D1-D12 complex to evaluate their specificity and their molecular modeling was also studied in the aim of producing anti-COVID-19 target molecules. Conclusion: The results showed that compounds 10a, 10b, 10c, 10e, 10f, 10g and 10h showed high % inhibitions against SARs-Covnsp 14. Whereas compounds 5a, 7a, 8b, 10a, 10b, 10c and 10i showed high inhibitions against hRNMT. This study explored the binding affinity of twenty-two halogenated compounds to the SARS-CoV-2 M^Pro and discovered fifteen compounds with higher binding affinity than Nelfinavir, of which three showed remarkable results. c-Met kinase inhibitions of 10a, 10f, 10g and 10h showed that all compounds exhibited higher inhibitions than the reference Foretinib.