Combinatorial Chemistry & High Throughput Screening - Volume 24, Issue 10, 2021

Background: The use of nanoparticles has markedly increased in biomedical sciences. The silver nanoparticles (AgNPs) have been investigated for their applicability to deliver chemotherapeutic/antibacterial agents to treat cancer or infections disease. However, the existing chemical and physical methods of synthesizing AgNPs are considered inefficient, expensive and toxic. Methods: Natural products have emerged as viable candidates for nanoparticle production, including the use of Terfezia boudieri (T. boudieri), a member of the edible truffle family. Accordingly, our goal was to synthesize AgNPs using an aqueous extract of T. boudieri (green synthesized AgNPs). Since certain infectious agents are linked to cancer, we investigated their potential as anti-cancer and antibacterial agents. Results: The synthesis of AgNPs was confirmed by the presence of an absorption peak at 450nm by spectroscopy. The physico-chemical properties of green synthesized AgNPs were analyzed by UV-Vis, FT-IR, XRD, SEM, and TEM. In addition, their potential to inhibit cancer cell (proliferation and the growth of infectious bacteria were investigated. Conclusion: The size of nanoparticles ranged between 20-30nm. They exerted significant cytotoxicity and bactericidal effects in a concentration and time-dependent manner compared to T. boudieri extract alone. Interestingly, the synthesis of smaller AgNPs was correlated with longer synthesis time and enhanced cytotoxic and bactericidal properties.

Background: Hepatoma is a common malignancy in the world with high morbidity and mortality. The treatment of hepatoma is limited by its poor response to many chemotherapeutic agents. Although paclitaxel (PTX) is widely used in clinical chemotherapy, the low sensitivity to hepatoma restricts its application. Combination therapy is a promising approach to resolve this dilemma. Objective: To evaluate the interaction between paclitaxel, bufalin (BFL) and cinobufagin (CBF), and explore the optimum combination efficiently. Methods: HepG2 cells were treated with PTX, BFL and CBF individually or in combination. Their interactions were evaluated by two classical models (Chou-Talalay model and Bliss independence). Response surface methodology (RSM) was used to explore the optimum combination. Furthermore, the optimum drug combination was verified by the morphological experiment. Results: Synergistic effects were observed when cells were exposed to binary mixtures of PTX+CBF and BFL+CBF. Although the interaction of PTX and BFL was summative, a strong synergistic effect was observed when cells were exposed to ternary mixtures of PTX+BFL+CBF. The interaction results of RSM were consistent with classical models, but more efficient. Moreover, the optimum combination dose was given by RSM without the combinatorial explosion of exhaustive testing. Conclusion: The combination of BFL and CBF synergistically enhanced the potency of PTX against HepG2 cells. RSM could give an accurate evaluation for drug interactions and efficient prediction of optimum combination.

Background: Colorectal cancer (CRC) is the fourth most prevalent cancer in the world. However, the molecular mechanism underlying CRC is largely unknown. Objective: To explore the pathogenic mechanism of CRC and to facilitate better diagnosis and treatment of this disease. Methods: Differentially expressed miRNAs (DEMs) and genes (DEGs) in CRC vs. Control samples from the miRNA expression data in GSE115513 and the miRNA and mRNA expression data in the TCGA-COAD dataset were screened, followed by the construction of the miRNAmRNA regulatory network. Functional and pathway enrichment analysis, protein-protein interaction (PPI) analysis, and survival analysis were then performed for these DEGs and DEMs. Results: We identified 64 DEMs from the GSE115513 dataset and 265 DEMs and 2218 DEGs from the TCGA-COAD dataset. miR-27a-3p was a hub DEM with the highest degree in the miRNA-mRNA network, while GRIN2B and PCDH10 were hub DEGs targeted by multiple miRNAs, including miR-27a-3p. SNAP25 and GRIN2B were also hub DEGs with the highest degree of interactions in the PPI network. These DEMs and DEGs were significantly enriched in multiple KEGG pathways, including proteoglycans expression and cAMP signaling pathway in cancer. Finally, seven DEGs, including FJX1 Dsc2, and hsa-miR-375, were revealed to be correlated with CRC prognosis. Conclusion: Aberrant expressions of genes and miRNAs were involved in the pathogenesis of CRC, probably by regulating proteoglycans expression and cAMP signaling. miR-27a-3p, PCDH10, GRIN2B, FJX1, Dsc2, and hsa-miR-375 were identified as potential targets for understanding the pathogenic mechanism of CRC. In addition, FJX1, Dsc2 and hsa-miR-375 were identified as potential predictive markers for CRC prognosis.

Aims: Based on protein sequence information, a simple and effective method was used to analyze protein sequence similarity and predict DNA-binding protein. Background: It is absolutely necessary that we generate computational methods of low complexity to accurate infer protein structure, function, and evolution in the rapidly growing number of molecular biology data available. Objective: It is important to generate novel computational algorithms for analyzing and comparing protein sequences with the rapidly growing number of molecular biology data available. Methods: Based on global and local position representation with the curves of Fermat spiral and normalized moments of inertia of the curve of Fermat spiral, respectively, moreover, composition of 20 amino acids to get the numerical characteristics of protein sequences. Results: It has been applied to analyze the similarity/dissimilarity of nine ND5 proteins, the analysis results are consistent with the biological evolution theory. Furthermore, we employ the Logistic regression with 5-fold cross-validation to establish the prediction of DNA-binding proteins model, which outperformed the DNAbinder, iDNA-prot, DNA-prot and gDNA-prot by 0.0069-0.609 in terms of F-measure, 0.293-0.898 in terms of MCC in unbalanced dataset. Conclusion: These results show that our method, namely FermatS, is effective to compare, recognition and prediction the protein sequences.

Background: Zanthoxylum bungeanum Maxim., a traditional Chinese herbal medicine, has been reported to possess therapeutic effects on diseases induced by oxidative stress (DOS), such as atherosclerosis and diabetes complication. However, the active components and their related mechanisms are still not systematically reported. Objective: The current study was aimed to explore the main active ingredients and their molecular mechanisms of Z. bungeanum for treating DOS using network pharmacology combined with molecular docking simulation. Methods: The active components of Z. bungeanum pericarps, in addition to the interacting targets, were identified from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. These components were filtered using the parameters of oral bioavailability and drug-likeness, and the targets related to DOS were obtained from the Genecards and OMIM database. Furthermore, the overlapping genes were obtained, and a protein-protein interaction was visualized using the STRING database. Next, the Cytoscape software was employed to build a disease/drug/component/target network, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using R software. Finally, the potential active compounds and their related targets were validated using molecular docking technology. Results: A total of 61 active compounds, 280 intersection genes, and 105 signaling pathways were obtained. Functional enrichment analysis suggested that DOS occurs possibly through the regulation of many biological pathways, such as AGE-RAGE and HIF-1 signaling pathways. Thirty of the identical target genes showed obvious compact relationships with others in the STRING analysis. Three active compounds, quercetin, diosmetin, and beta-sitosterol, interacting with the four key targets, exhibited strong affinities. Conclusion: The findings of this study not only indicate the main mechanisms involving in oxidative stress-induced diseases but also provide the basis for further research on the active components of Z. bungeanum for treating DOS.

Background: Novel coronavirus SARS-CoV-2 is responsible for the COVID-19 pandemic. It was first reported in Wuhan, China, in December 2019, and despite the tremendous efforts to control the disease, it has now spread almost all over the world. The interaction of SARSCoV- 2spike protein and its acceptor protein ACE2 is an important issue in determining viral host range and cross-species infection, while the binding capacity of spike protein to ACE2 of different species is unknown. Objective: The present study has been conducted to determine the susceptibility of livestock, poultry and pets to SARS-CoV-2. Methods: We evaluated the receptor-utilizing capability of ACE2s from various species by sequence alignment, phylogenetic clustering and protein-ligand interaction studies with the currently known ACE2s utilized by SARS-CoV-2. Result: In-silico study predicted that SARS-CoV-2 tends to utilize ACE2s of various animal species with varied possible interactions. The probability of the receptor utilization will be greater in horse and poor in chicken, followed by ruminants. Conclusion: Present study predicted that SARS-CoV-2 tends to utilize ACE2s of various livestock and poultry species with greater probability in equine and poor in chicken. The study may provide important insights into the animal models for SARS-CoV-2 and animal management for COVID- 19 control.

Background: Drakshasava is one of the commercial Ayurvedic medicines from India, prepared from grapes and spices. It is believed to address health imbalances and claimed to be beneficial for weakness, bleeding disorders, and various inflammatory diseases. It has been reported to possess pharmacological activities such as diuretic, cardioprotective, and antimicrobial. Being a polyherbal mixture, it faces challenges in its standardization and quality control. Objective: The aim of the present study is to develop a validated UPLC-MS/MS method for simultaneous quantification of 10 polyphenolic biomarkers in Drakshasava. It explores the effect of Vitis vinifera L. and additional herbs on fermentation with respect to bioactive compounds through the successive addition method. Methods: The MS methods were optimized in multiple-reaction monitoring (MRM) mode with ESI while chromatographic separation was achieved on an Acquity UPLC BEH C18 column using both isocratic and gradient elution in water and acetonitrile containing 0.1% formic acid. Results: The developed method was validated as per ICH-Q2B guidelines and found to be within the assay variability limits. Gallic acid was found to be the most abundant marker in all the samples followed by resveratrol. The content of all the markers has been found to be increased significantly post-fermentation, compared to decoction except kaempferol. The successive addition of prashpeka drvya (minor herbs) in the formulation showed variability at different stages with respect to the selected markers and did not exhibit major changes in the chemical profiling of the final product. Conclusion: The developed method was found to be rapid, accurate, reliable, and highly sensitive for the simultaneous quantification of selected biomarkers in Drakshasava. The research is the first chemometric report on the standardization of Drakshasava by validated UPLC-MS/MS method. It may prove to be a useful tool for the development of new phytopharmaceutical drugs and further quality control of other polyherbal formulations.

Background: SARS-CoV-2 has been shown to bind the host cell ACE2 receptor through its spike protein receptor binding domain (RBD), required for its entry into the host cells. Objective: We have screened phytocompounds from a medicinal herb, Tinospora cordifolia for their capacities to interrupt the viral RBD and host ACE2 interactions. Methods: We employed molecular docking to screen phytocompounds in T. cordifolia against the ACE2-RBD complex, performed molecular dynamics (MD) simulation, and estimated the electrostatic component of binding free energy. Results: ‘Tinocordiside’ docked very well at the center of the interface of ACE2-RBD complex, and was found to be well stabilized during MD simulation. Tinocordiside incorporation significantly decreased the electrostatic component of binding free energies of the ACE2-RBD complex (23.5 and 17.10 kcal/mol in the trajectories without or with the ligand, respectively). As the basal rate constant of protein association is in the order of 5 (10⁵ to 10⁶ M^-1S^-1), there might be no big conformational change or loop reorganization, but involves only local conformational change typically observed in the diffusion-controlled association. Taken together, the increase in global flexibility of the complex clearly indicates the start of unbinding process of the complex. Conclusion: It indicates that such an interruption of electrostatic interactions between the RBD and ACE2, and the increase in global flexibility of the complex would weaken or block SARSCoV- 2 entry and its subsequent infectivity. We postulate that natural phytochemicals like Tinocordiside could be viable options for controlling SARS-CoV-2 contagion and its entry into host cells.