Combinatorial Chemistry & High Throughput Screening - Volume 26, Issue 2, 2023

Asthma is a common complex disorder characterized by hyper-responsiveness and chronic inflammatory airway disease in children and adults worldwide. The prevalence of asthma is increasing with each passing year. Long non-coding RNAs (lncRNAs), regarded as a potentially promising path, have received increasing attention in exploring the biological regulation of chronic airway diseases, although they have no or limited protein-coding capacity. This review highlights the functional roles and clinical significance of lncRNAs in the pathogenesis of asthma and provides directions for diagnosing and treating asthma in the future.

Background: The Apiaceae or Umbelliferae is one of the largest families in terms of species representation in the plant kingdom. It is also a prominent family in the field of phytochemicals and pharmacology. The family is also quite prominent in the production of spices and condiments and food supplements in nutrition, aside from the potential of species in the family to induce apoptotic, antimicrobial, antitumor, and hepatoprotective activities. Objective: This work presents a detailed structural elucidation and functional aspects of phytochemicals from the Apiaceae or Umbelliferae family. Methods: Furthermore, the application of members of this family in traditional and modern pharmacology is emphasized. This review also highlights the linkage of phytochemicals used in the conventional system of medication for the development of novel therapeutics through a chain of pre-clinical and clinical trials. Conclusion: This study may represent a valuable step ahead in the clinical development of natural drugs for curing several ailments, including respiratory and virus-related diseases.

Introduction: The incidence of colorectal cancer is steadily increasing, and the detection of related molecular targets is critical for its diagnosis and treatment. Long noncoding RNA (lncRNA) can play a regulatory role before and after genome transcription, and epigenetic regulation is involved in the process of tumorigenesis and tumor development. Methods: In this study, qRT-PCR was performed to evaluate the expression of AK093407 in colon cancer and colon para-carcinoma tissues and HCT-15 and HCT-116 cells. SiRNA was transfected into HCT-15 and HCT-116 cells to knock down lncRNA-AK093407. Then, MTT assay was used to test cell proliferation, and flow cytometry was used to test apoptosis and cell cycle. The protein expression of caspase-3, caspase-8, caspase-9, bax, bcl-2, cyclin-A1, cyclin-B1, cyclin-D1, cyclin- E1, p21, p27, and p-Stat3 was determined by Western blot. Results: The results showed that the expression of AK093407 in human colon cancer tissue was higher than in para-carcinoma tissue. The amount of AK093407 in HCT-15 and HCT-116 cells was higher than that in normal colorectal epithelial NM460 cells. When AK093407 was silenced, the proliferation of HCT-15 and HCT-116 cells decreased, the apoptosis rate increased, the cell cycle was arrested in the G1/S phase, the expression of caspase-3, caspase-8, caspase-9, bax, cyclin-A1, cyclin- B1, p21, p27 increased, and the expression of bcl-2, cyclin-D1, cyclin-E1, p-Stat3 decreased. Conclusion: These results showed that knockdown of AK093407 could inhibit colon cancer cell proliferation, induce apoptosis and cell cycle arrest, influence the expression of vital factors in mitochondrial apoptosis pathway and cell cycle regulatory pathway, and may negatively regulate JAK/STAT3 through down-regulating p-Stat3.

Background & Aim: Significant evidence indicates that endocrine disrupted bisphenol A (BPA) seriously endangers human health. In males, BPA affects testis architecture and sperm quality, and ultimately reduces fertility. This study explored the therapeutic potential of Nigella sativa (NS) seed extract on testis and sperm abnormalities in BPA-exposed mice and characterized the underlying mechanism. Methods: Forty male Swiss albino mice (5.5 weeks old, N = 8 per group) were randomly divided into five groups: Group I, normal control, Group II, vehicle control (sterile corn oil); Group III, NS-exposed (oral 200 mg/kg); Group IV, BPA-exposed (oral 400 μg/kg body weight); Group V, BPA + NS-exposed mice. Animals were treated for 6 weeks and sacrificed for biochemical and histological examination. Results: The results indicated that BPA exposure results in significant testis and sperm abnormalities. Specifically, BPA promoted a marked reduction in the body and testis compared with the control group. Histopathological findings showed that BPA caused a widespread degeneration of spermatogenic cells of the seminiferous epithelium, decreased sperm counts and motility, and augmented sperm abnormalities, and whereas little alteration to sperm DNA was observed. In addition, BPA increased the levels of the lipid peroxidation marker, malondialdehyde (MDA), and reduced the levels of the antioxidant marker, reducing glutathione (GSH). Treatment with NS oil extract during BPA exposure significantly alleviated testis and sperm abnormalities, reduced MDA levels, and enhanced GSH levels. Conclusion: The results demonstrate that NS oil protects mice against BPA-induced sperm and testis abnormalities, likely by suppressing levels of the oxidative stress marker, MDA, and enhancing the levels of the antioxidant marker, GSH.

Background: The mutated genes in lung squamous cell carcinoma were investigated for their possible association with tumor mutation burden, microsatellite instability, and cancer prognosis. Objective: Our study aims to evaluate the value of the candidate genes as a potential biomarker of lung squamous cell carcinoma and pan-cancer analysis. Methods: The landscape of the tumor microenvironment and infiltrating lymphocytes in lung squamous cell carcinoma was calculated using ESTIMATE and CIBERSORT algorithm. Weighed gene co-expression network analysis was used to screen key modules related to immune cell infiltration. Somatic mutations were found by data analysis from the TCGA and ICGC databases. Mann-Whitney U test was used to evaluate the tumor mutation burden difference between patients with mutant and wild-type SVEP1 genes. The Kaplan-Meier method was used to examine the prognosis of the patients with mutations. The effects of SVEP1 expression on tumor mutation burden and immunity in different cancers were determined by pan-cancer analysis. Results: SVEP1 mutation was found to be associated with a higher tumor mutation burden and prognosis. SVEP1 mutation might be involved in the possible biological process of the anti-tumor immune response. SVEP1 is related to different degrees of immune infiltration in cancer. Moreover, the miRNA-SVEP1 targeting network was used to illuminate the possible mechanisms. Conclusion: SVEP1 mutation and its mRNA expression are related to tumor mutation burden and cancer immunity in lung squamous cell carcinoma. Our findings reveal the underlying mechanisms, indicating that SVEP1 may be a prognostic marker of lung squamous cell carcinoma.

Background: Uterine Corpus Endometrial Carcinoma (UCEC) is a common malignancy of the female genital tract. The sine oculis homeobox homolog 1 (SIX1) protein has been documented to be important for tumor progression. However, little is known about the relationship between SIX1 and the pathogenesis of UCEC. Objective: This study aimed to assess the prognostic value of biomarker SIX1 in UCEC by analyzing clinical traits, immune infiltration, and gene set enrichment analysis. Methods: The Wilcoxon signed-rank test and logistic regression were used to analyze the relationship between clinicopathological characteristics and SIX1. The Kaplan-Meier method was used to assess the relationship between clinicopathological characteristics and prognosis verified by immunohistochemistry (IHC). Then gene set enrichment analysis (GSEA) was performed to explore signaling pathways correlated with SIX1 expression in UCEC. Finally, the TIMER2 database was used to analyze the correlation between SIX1 and immune infiltration, and the effect of SIX1 expression on immune cells was calculated with the CIBERSORT algorithm. Results: We found that the expression of SIX1 in UCEC was up-regulated and correlated with a poor prognosis. Analysis showed that the expression of SIX1 was related to various clinical features and was an independent prognostic factor of UCEC. Enrichment analysis showed that SIX1 promoted the occurrence and development of UCEC by regulating multiple signaling pathways. The results of immune infiltration analysis showed that SIX1 has a complex correlation with immune infiltration. Conclusion: Our findings indicate that SIX1 is a promising biomarker for predicting the prognosis of UCEC and is a potential therapeutic target.

Background: Currently, there are no effective differentiation-inducing agents for gliomas. Drug repositioning is a time-saving, low-risk, and low-cost drug development strategy. In this study, drugs that could induce the differentiation of glioma cells were searched by using a drug repositioning strategy. Methods: Data mining was used to screen for differentially expressed genes (DEGs). The STRING 11.0 database was used for enrichment analysis. The Connectivity Map database was used for drug screening. The ChEMBL and STITCH databases were used to search for drug targets. The SwissDock database was used for molecular docking. Results: A total of 45 DEGs were identified. The biological processes in which the DEGs were enriched mainly involved nervous system development and the regulation of biological processes. The enriched molecular functions mainly involved transcription-related molecular binding. The enriched cellular components mainly involved membrane-bound organelles and cellular protrusions. The enriched local network clusters mainly involved autophagy, the retinoic acid signalling pathway, and DNA methylation. The drug screening results showed that the drug with the highest score was acenocoumarol. A total of 12 acenocoumarol targets were obtained, among which histone deacetylase 1 (HDAC1) was the target with the highest degree value; the lowest ΔG value for acenocoumarol docked with HDAC1 was -7.52 kcal/mol, which was between those of the HDAC1 inhibitors romidepsin and vorinostat. Conclusion: Acenocoumarol may be a potential differentiation-inducing agent for glioma cells.

Background: The clinical value of pyroptosis-related genes (PRGs) in lung adenocarcinoma (LUAD) remains obscure. Objective: The study attempts to explore PRGs in LUAD, which will enable an understanding of LUAD from the perspective of PRGs. Methods: Lung adenocarcinoma patients were diagnosed using pathology, and their clinical information was collected from several public databases. A PRGs prognostic signature (PPS) for LUAD patients was established based on a multivariate Cox regression analysis. The differential expression of PRGs was identified using standardized mean differences in 6,958 samples. The area under the curve (AUC) was used to evaluate the predictive effects of the PPS to determine the survival rate of LUAD patients. Decision curve analysis was utilized to assess the clinical significance of the PPS in LUAD. Results: The PPS consists of five PRGs, namely CASP3, CASP9, GSDMB, NLRP1, and TNF. The prognostic effect of the PPS is evident in all the predicted one-, three-, and five-year survival rates (AUCs ≥ 0.58). The PPS represents an independent risk factor for the prognosis of LUAD patients (hazard ratio > 1; 95% confidence interval excluding 1). The PPS risk score can predict the prognosis of LUAD patients more accurately than PRGs of the PPS and multiple clinical parameters, such as age, tumor stage, and clinical stage. The decision curve analysis revealed that the nomogram based on the PPS and clinical parameters might result in better clinical decisions. Conclusion: The PPS makes it feasible to distinguish LUAD from non-LUAD. Thus, the underlying significance of the PPS in distinguishing LUAD from non-LUAD is promising.

The Batman-TCM research platform based on network pharmacology was used to predict the reverse targets of 11 active components of blueberry. The anti-inflammatory target genes of these components were extracted by comparing them with the anti-inflammatory drug target genes in the GeneCards database. GO enrichment and KEGG pathway, as well as protein interaction analysis of these anti-inflammatory target genes, were carried out using the String database. The antiinflammatory component-target-action pathway map of blueberry was constructed using the Cytoscape software. The molecular docking between seven components and two targets was validated using the Autodock-vina program. The results showed that 7 components had anti-inflammatory activity and acted on 84 anti-inflammatory targets. KEGG and GO analysis showed that the main active components of blueberry could inhibit inflammation by inhibiting the production of inflammatory factors and enhancing immunity. Network analysis revealed that the main anti-inflammatory targets of blueberry active components were TNF, ESR1, AGTR1, and IGF1. Based on molecular docking analysis, the main components of blueberry integrate with 2 important targets in inflammatory networks. Collectively, we characterized the anti-inflammatory effect of blueberry by multi-component, multi-target, and multi-pathway. The molecular mechanism of the multi-target effect of blueberry was preliminarily expounded, thereby providing a scientific basis for exploring the material basis and mechanism of the anti- inflammatory action of blueberry. Background: Non-steroidal anti-inflammatory drugs, such as aspirin, have beneficial effects in the treatment of inflammation but they often have undesired side effects. In contrast, various natural remedies, with their unique natural, safe and effective ingredients, have achieved good effects in the treatment of inflammation and become widely used for anti-inflammatory medication. Objective: To provide scientific basis for exploring the material basis and mechanism of antiinflammatory action of blueberry. Methods: The anti-inflammatory target genes of these components were extracted by comparing them with the anti-inflammatory drug target genes in the GeneCards database. GO enrichment and KEGG pathway, as well as protein interaction analysis of these anti-inflammatory target genes, were carried out by using the String database. The anti-inflammatory component-target-action pathway map of blueberry was constructed using the Cytoscape software. The molecular docking between seven components and two targets was validated using the Autodock-vina program. The results showed that 7 components had anti-inflammatory activity and acted on 84 anti-inflammatory targets. Results: 7 components had anti-inflammatory activity and acted on 84 anti-inflammatory targets. KEGG and GO analysis showed that the main active components of blueberry could inhibit inflammation by inhibiting the production of inflammatory factors and enhancing immunity. Network analysis revealed that the main anti-inflammatory targets of blueberry active components were TNF, ESR1, AGTR1 and IGF1. Based on molecular docking analysis, the main components of blueberry integrate with 2 important targets in inflammatory networks. Conclusion: The molecular mechanism of the multi-target effect of blueberry was preliminarily expounded, thereby providing a scientific basis for exploring the material basis and mechanism of antiinflammatory action of blueberry.

Background: Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart disease in clinical practice. It is mainly due to cardiovascular hypoplasia during embryonic development. The study aimed to find the etiology of TOF. Methods: Through the mRNA expression profile analysis of the GSE35776 dataset, differentially expressed genes (DEGs) were found, and the functional analysis and protein-protein interaction (PPI) network analysis were then performed on DEGs. Likewise, the hub genes and functional clusters of DEGs were analyzed using the PPI network. Differentially expressed miRNAs were analyzed from the GSE35490 dataset, followed by miRNet predicted transcription factors (TFs) and target genes. The key TF-miRNA-gene interaction mechanism was explored through the found significant difference between genes and target genes. Results: A total of 191 differentially expressed genes and 57 differentially expressed miRNAs were identified. The main mechanisms involved in TOF were mitochondria-related and energy metabolism- related molecules and pathways in GO and KEGG analysis. This discovery was identical in TFs and target genes. The key miRNAs, hsa-mir-16 and hsa-mir-124, were discovered by the Venn diagram. A co-expression network with the mechanism of action centered on two miRNAs was made. Conclusion: Hsa-mir-16 and hsa-mir-124 are the key miRNAs of TOF, which mainly regulate the expression of NT5DC1, ECHDC1, HSDL2, FCHO2, and ACAA2 involved in the conversion of ATP in the mitochondria and the metabolic rate of fatty acids (FA). Our research provides key molecules and pathways into the etiology of TOF, which can be used as therapeutic targets.

Background: COVID-19 (Coronavirus Disease 2019) caused by SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) has infected millions of people and caused hundreds of thousands of deaths worldwide. However, until now no specific drug for SARS-CoV-2 infection has been found. This prompted many researchers to explore compounds as anti-SARS-CoV-2 candidates. One of the efforts to deal with the spread of the COVID-19 virus is to increase the body's immune system (immune). Medicinal plants are known to have the ability as immune-modulators, one of which is Betel leaf (Piper betle L.) which has good activity as antibacterial, antioxidant, and anti-viral with other pharmacological effects. An in silico approach in drug development was used to search for potential antiviral compounds as inhibitors of SARS-CoV-2 Mpro Protein, RBD, and Non-structural Protein (NSP15). Objective: This study aimed to determine the potential of Betel leaf compounds as immunemodulators and good inhibitory pathways against COVID-19. Methods: In this study, a potential screening of steroid class compounds, namely 24- propilcholesterol was carried out as an anti-SARS-CoV-2 candidate, using an in silico approach with molecular docking simulations for three receptors that play an important role in COVID-19, namely Mpro SARS-CoV-2, RBD SARS-CoV-2 and a non-structural protein (NSP15) and were compared with Azithromycin, Favipiravir and Ritonavir as positive controls. Results: Based on the results of molecular docking simulations, compound from Betel leaf, 24- Propylcholesterol, showed high binding affinity values for spike glycoprotein RBD and nonstructural protein 15 (NSP15), namely -7.5 and -7.8 kcal/mol. Meanwhile, a native ligand of Mpro, inhibitor N3, has a higher binding affinity value than 24-propylcholesterol -7.4 kcal/mol. Conclusion: 24-Propylcholesterol compound predicted to have potential as an anti-SARS-CoV-2 compound. However, it is necessary to carry out in vitro and in vivo studies to determine the effectiveness of the compound as an anti-SARS-CoV-2.

Background: The “Ruan Jian Qing Mai (RJQM) recipe” is a traditional Chinese medicine (TCM), which has been found to have significant curative effects on diabetic ulcers in the clinic for a long time. Previous research has shown that RJQM can improve diabetic skin wound healing and promote angiogenesis. However, the active ingredients of the RJQM recipe and its pharmacological mechanism of treatment for diabetic skin wound healing still remain unclear.This study aims to investigate the effect of the RJQM recipe on diabetic wound healing, and to identify the possible active ingredients and their mechanism. Methods: First, a skin injury model was established in diabetic mice, and wound healing was evaluated by hematoxylin-eosin (HE) staining, quantitative reverse transcription-polymerase chain reaction (RT-qPCR), and western blot analysis. Second, the chemical constituents of the RJQM recipe were analyzed and identified by ultra pressure liquid chromatography-mass spectrometry (UPLC-MS). Finally, the possible targets of drug treatment for diabetic skin injury were analyzed by network pharmacology and verified by in vitro experiments using cell culture. Results: (1) In the full-thickness skin injury model, the skin wound healing rate and healing area were significantly increased in mice treated with the RJQM recipe compared with those of the model group. The results of immunofluorescence staining showed that the RJQM recipe could increase the expression of VEGF protein and promote the proliferation of vascular smooth muscle cells and the formation of microvessels, and RT-qPCR results found that the mRNA expression of angiogenesis-related factors in the RJQM recipe group was significantly higher than that in the model group. (2) A total of 25 compounds were identified by UPLC-MS. (3) According to the results of network pharmacology, the therapeutic effect of the RJQM recipe on diabetic skin injury may be related to S6 (quercetin), S1 (typhaneoside), S18 (isoliquiritigenin), protein kinase B-α (Akt1), phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), insulin-like growth factor I receptor (IGF1R), vascular endothelial growth factor-a (VEGF-a), signal transducer and activator of transcription-3 (STAT3) and phosphoinositide 3-kinase-protein kinase B (PI3K-Akt) signaling pathways. Based on the predictions by network pharmacology, we proved that the drug could treat diabetic skin damage by activating the PI3K-Akt-VEGF signaling pathway. Conclusion: The RJQM recipe promotes the formation of granulation tissue during the process of wound healing and exerts a good therapeutic effect on diabetic skin wound healing.

Background: Osteoarthritis (OA) is a worldwide chronic disease of the articulating joints. An increasing body of data demonstrates the immune system's involvement in osteoarthritis. The molecular mechanisms of OA are still unclear. This study aimed to search for OA immunerelated hub genes and determine appropriate diagnostic markers to help the detection and treatment of the disease. Methods: Gene expression data were downloaded from the GEO database. Firstly, we analyzed and identified the differentially expressed genes (DEGs) using R packages. Meanwhile, ssGSEA was used to determine the activation degree of immune-related genes (IRGs), and WGCNA analysis was applied to search for co-expressed gene modules associated with immune cells. Then, critical networks and hub genes were found in the PPI network. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Gene and Genomes (KEGG) pathway enrichment analyzed the biological functions of genes. The ability of the hub genes to differentiate OA from controls was assessed by the area under the ROC curve. A miRNA and transcription factor (TF) regulatory network was constructed according to their relationship with hub genes. Finally, the validation of hub genes was carried out by qPCR. Results: In total, 353 DEGs were identified in OA patients compared with controls, including 222 upregulated and 131 downregulated genes. WGCNA successfully identified 34 main functional modules involved in the pathogenesis of OA. The most crucial functional module involved in OA included 89 genes. 19 immune-related genes were obtained by overlapping DEGs with the darkgrey module. The String database was constructed using the protein-protein interaction (PPI) network of 19 target genes, and 7 hub genes were identified by MCODE. ROC curve showed that 7 hub genes were potential biomarkers of OA. The expression levels of hub genes were validated by qPCR, and the results were consistent with those from bioinformatic analyses. Conclusion: Immune-related hub genes, including TYROBP, ITGAM, ITGB2, C1QC, MARCO, C1QB, and TLR8, may play critical roles in OA development. ITGAM had the highest correction on immune cells.

Background: The clinical diagnosis of major depressive disorder (MDD) mainly relies on subjective assessment of depression-like behaviors and clinical examination. In the present study, we aimed to develop a novel diagnostic model for specially predicting MDD. Methods: The human brain GSE102556 DataSet and the blood GSE98793 and GSE76826 Data Sets were downloaded from the Gene Expression Omnibus (GEO) database. We used a novel algorithm, random forest (RF) plus artificial neural network (ANN), to examine gene biomarkers and establish a diagnostic model of MDD. Results: Through the “limma” package in the R language, 2653 differentially expressed genes (DEGs) were identified in the GSE102556 DataSet, and 1786 DEGs were identified in the GSE98793 DataSet, and a total of 100 shared DEGs. We applied GSE98793 TrainData 1 to an RF algorithm and thereby successfully selected 28 genes as biomarkers. Furthermore, 28 biomarkers were verified by GSE98793 TestData 1, and the performance of these biomarkers was found to be perfect. In addition, we further used an ANN algorithm to optimize the weight of each gene and employed GSE98793 TrainData 2 to build an ANN model through the neural net package by R language. Based on this algorithm, GSE98793 TestData 2 and independent blood GSE76826 were verified to correlate with MDD, with AUCs of 0.903 and 0.917, respectively. Conclusion: To the best of our knowledge, this is the first time that the classifier constructed via DEG biomarkers has been used as an endophenotype for MDD clinical diagnosis. Our results may provide a new entry point for the diagnosis, treatment, outcome prediction, prognosis and recurrence of MDD.

Background: Nimbamrithadhi Panchathiktha Kashayam (NPK) is an Ayurvedic formulation of potent plant ingredients with immune-modulating effects and anti-viral activities. Objectives: The present study is intended to identify the key target involved in immune and inflammatory response against SARS-COV-2 via network pharmacology and also investigates the potent phytoconstituent within NPK in combating or modulating target response via molecular docking. Methods: Active phytoconstituents of NPK were filtered based on overall bioavailability and druglikeness by Lipinski’s and ADMETOX prediction. Results: Results indicate that IRF 7 can be selected as an efficient target in regulating immunomodulatory and anti-viral activity via network pharmacology. Molecular docking studies show that apigenin (22.22 Kcal /mol), thiamine (24.89 Kcal /mol) and esculetin (25.21 Kcal /mol) within Nimbamrithadhi Panchathiktha Kashayam(NPK) possess better binding affinity in comparison with standard drug gemcitabine (14.56 Kcal /mol). Even though docking score is more for Esculetin and Thiamine, Apigenin within Solanum Virgianum (Yellow nightshade) and Azadirachta Indica (Neem) is considered as the active phytoconstituent in modulating immune responses and anti-viral activities based on the number and nature of amino acid interaction. Conclusion: To the best of our knowledge, no scientific validation has been done on NPK against COVID-19. The study indicates that NPK can be a better alternative prophylaxis strategy against SARS-COV-2 infection if further validated via suitable preclinical studies.