Abstract: Sanhuang Xiexin Decoction (SXD) is commonly used to treat type 2 diabetes mellitus (T2DM) in clinical practice of traditional Chinese medicine (TCM). In order to elucidate the specific analysis mechanisms of SXD for T2DM, the method of network pharmacology was applied to this article. First, the effective ingredients of SXD were obtained and their targets were identified based on the TCMSP database. The T2DM-related targets screened from the GEO database were also collected by comparing the differential expressed genes between T2DM patients and healthy individuals. Then, the common targets in SXD-treated T2DM were obtained by intersecting the putative targets of SXD and the differential expressed genes of T2DM. And the protein-protein interaction (PPI) network was established using the above common targets to screen key genes through protein interactions. Meanwhile, these common targets were used for GO and KEGG analyses to further elucidate how they exert antidiabetic effects. Finally, a gene pathway network was established to capture the core one in common targets enriched in the major pathways to further illustrate the role of specific genes. Based on the data obtained, a total of 67 active compounds and 906 targets of SXD were identified. Four thousand one hundred and seventy-six differentially expressed genes with a P value < 0.005 and mid R:log2(fold change) | >0.5 were determined between T2DM patients and control groups. After further screening, thirty-seven common targets related to T2DM in SXD were finally identified. Through protein interactions, the top 5 genes (YWHAZ, HNRNPA1, HSPA8, HSP90AA1, and HSPA5) were identified. It was found that the functional annotations of target genes were associated with oxygen levels, protein kinase regulator, mitochondria, and so on. The top 20 pathways including the PI3K-Akt signaling pathway, cancers, HIF-1 signaling pathway, and JAK-STAT signaling pathway were significantly enriched. CDKN1A was shown to be the core gene in the gene-pathway network, and other several genes such as CCND1, ERBB2, RAF1, EGF, and VEGFA were the key genes for SXD against T2DM. Based on the network pharmacology approach, we identified key genes and pathways related to the prognosis and pathogenesis of T2DM and also provided a feasible method for further studying the chemical basis and pharmacology of SXD.

Abstract: Objective: To explore multiscale integrated analysis methods in identifying key regulators of esophageal cancer (ESCA). Methods: We downloaded the ESCA dataset from The Cancer Genome Atlas (TCGA) database, which contained RNA-seq data, miRNA-seq data, methylation data, and clinical phenotype information. Then, we combined ESCA-related genes from the NCBI-GENE and OMIM databases and RNA-seq dataset from TCGA to analyze differentially expressed genes (DEGs). Meanwhile, differentially expressed miRNAs (DEmiRNAs) and genes with differential methylation levels were identified. The pivot-module pairs were established using the RAID v2.0 database and TRRUST v2 database. Next, the multifactor-regulated functional network was constructed based on the above information. Additionally, gene corresponding targeted drug information was obtained from the DrugBank database. Moreover, we further screened regulators by assessing their diagnostic value and prognostic value, especially the value of distinguishing patients at TNM I stage from normal patients. In addition, the external database from the Gene Expression Omnibus (GEO) database was used for validation. Lastly, gene set enrichment analysis (GSEA) was performed to explore the potential biological functions of key regulators. Results: Our study indicated that CXCL8, CYP2C8, and E2F1 had excellent diagnostic and prognostic values, which may be potential regulators of ESCA. At the same time, the good early diagnosis ability of the three regulators also provided new insights for the diagnosis and early treatment of ESCA patients. Conclusion: We develop a multiscale integrated analysis and suggest that CXCL8, CYP2C8, and E2F1 are promising regulators with good diagnostic and prognostic values in ESCA.

Abstract: Background: Huangqi Guizhi Wuwu Decoction (HGWD) has been applied in the treatment of joint pain for more than 1000 years in China. Currently, most physicians use HGWD to treat rheumatoid arthritis (RA), and it has proved to have high efficacy. Therefore, it is necessary to explore the potential mechanism of action of HGWD in RA treatment based on network pharmacology and molecular docking methods. Methods: The active compounds of HGWD were collected, and their targets were identified from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and DrugBank database, respectively. The RA-related targets were retrieved by analyzing the differentially expressed genes between RA patients and healthy individuals. Subsequently, the compound-target network of HGWD was constructed and visualized through Cytoscape 3.8.0 software. Protein-protein interaction (PPI) network was constructed to explore the potential mechanisms of HGWD on RA using the plugin BisoGenet of Cytoscape 3.8.0 software. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed in R software (Bioconductor, clusterProfiler). Afterward, molecular docking was used to analyze the binding force of the top 10 active compounds with target proteins of VCAM1, CTNNB1, and JUN. Results: Cumulatively, 790 active compounds and 1006 targets of HGWD were identified. A total of 4570 differentially expressed genes of RA with a p value <0.05 and |log 2(fold change)| > 0.5 were collected. Moreover, 739 GO entries of HGWD on RA were identified, and 79 pathways were screened based on GO and KEGG analysis. The core target gene of HGWD in RA treatment was JUN. Other key target genes included FOS, CCND1, IL6, E2F2, and ICAM1. It was confirmed that the TNF signaling pathway and IL-17 signaling pathway are important pathways of HGWD in the treatment of RA. The molecular docking results revealed that the top 10 active compounds of HGWD had a strong binding to the target proteins of VCAM1, CTNNB1, and JUN. Conclusion: HGWD has important active compounds such as quercetin, kaempferol, and beta-sitosterol, which exert its therapeutic effect on multiple targets and multiple pathways.

Abstract: Background: Bacterial and fungal infections are common and often contribute to death in patients undergoing extracorporeal membrane oxygenation (ECMO). Drug disposition is altered during ECMO, and adsorption in the circuit is an established causative factor. Vancomycin and voriconazole are widely used, despite the lack of evidence-based prescription guidelines. Objective: The objective of this study was to determine the extraction of voriconazole and vancomycin by the Xenios/Novalung ECMO circuits. Methods: We have set up nine closed-loop ECMO circuits, consisting of four different iLAActivve ((R)) kits for neonatal, pediatric, and adult support: three iLA-ActivveMiniLung ((R)) petite kits, two iLA-ActivveMiniLung ((R)) kits, two iLA-ActivveiLA ((R)) kits, and two iLA-Activve X-lung ((R)) kits. The circuits were primed with whole blood and maintained at physiologic conditions for 24 h. Voriconazole and vancomycin were injected as a single-bolus age-related dose into the circuits. Pre-membrane (P2) blood samples were obtained at baseline and after drug injection at 2, 10, 30, 180, 360 min, and 24 h. A control sample at 2 min was collected for spontaneous drug degradation testing at 24 h. Results: Seventy-two samples were analyzed in triplicate. The mean percentage of drug recovery at 24 h was 20% for voriconazole and 62% for vancomycin. Conclusions: The extraction of voriconazole and vancomycin by contemporary ECMO circuits is clinically relevant across all age-related circuit sizes and may result in reduced drug exposure in vivo.

Abstract: Cytochrome P450 aromatase 19A1 (CYP19A1) is a critical enzyme in estrogen synthesis. However, the effect of CYP19A1 on cell growth and hormone secretion of buffalo follicular granulosa cells (BFGCs) is poorly understood. The objective of this study was to assess the role of CYP19A1 in cell proliferation and hormone secretion of BFGCs by knocking down CYP19A1 mRNA expression. The mRNA expression level of CYP19A1 gene was knocked down in BFGCs using the siCYP19A1-296 fragment with the best interference efficiency of 72.63%, as affirmed by real-time quantitative PCR (qPCR) and cell morphology analysis. The CYP19A1 knockdown promoted the proliferation of BFGCs through upregulating the mRNA expression levels of six proliferation-related genes (CCND1, CCNE1, CCNB1, CDK2, CDKN1A, and CDKN1B). Moreover, CYP19A1 knockdown increased (P < 0.05) the concentrations of progesterone secretion (P4) in BFGCs through increasing the mRNA expression levels of three steroidogenic genes (HSD17B1, HSD17B7, and CYP17A1). Our data further found that the FSH could inhibit the mRNA expression level of CYP19A1 in BFGCs, while LH obtains the opposite effect. These findings showed that the CYP19A1 knockdown had a regulatory role in the hormone secretion and cell proliferation in BFGCs.

Abstract: It has been noticed that the efficiency of drug development has been decreasing in the past few decades. To overcome the situation, protein-protein interactions (PPIs) have been identified as new drug targets as early as 2000. PPIs are more abundant in human cells than single proteins and play numerous important roles in cellular processes including diseases. However, PPIs have very different physicochemical features from the conventional drug targets, which make targeting PPIs challenging. Therefore, as of now, only a small number of PPI inhibitors have been approved or progressed to a stage of clinical trial. In this article, we first overview previous works that analyzed differences between PPIs with PPI targeting ligands and conventional drugs with their binding pockets. Then, we constructed an up-to-date list of PPI targeting drugs that have been approved or are currently under clinical trial and have bound drug-target structures available. Using the dataset, we analyzed the PPIs and their ligands using several scores of druggability. Druggability scores showed that PPI sites and their drugs targeting PPIs are less druggable than conventional binding pockets and drugs, which also indicates that PPI drugs do not follow the conventional rules for drug design, such as Lipinski's rule of five. Our analyses suggest that developing a new rule would be beneficial for guiding PPI-drug discovery.

Abstract: In the golden age of pharmaceutical nanocarriers, we are witnessing a maturation stage of the original concepts and ideas. There is no doubt that nanoformulations are extremely valuable tools for drug delivery applications; the current challenge is how to optimize them to ensure that they are safe, effective and scalable, so that they can be manufactured at an industrial level and advance to clinical use. In this context, lipid nanoparticles have gained ground, since they are generally regarded as non-toxic, biocompatible and easy-to-produce formulations. Pharmaceutical applications of lipid nanocarriers are a burgeoning field for the transport and delivery of a diversity of therapeutic agents, from biotechnological products to small drug molecules. This review starts with a brief overview of the characteristics of solid lipid nanoparticles and discusses the relevancy of performing systematic preformulation studies. The main applications, as well as the advantages that this type of nanovehicles offers in certain therapeutic scenarios are discussed. Next, pharmacokinetic aspects are described, such as routes of administration, absorption after oral administration, distribution in the organism (including brain penetration) and elimination processes. Safety and toxicity issues are also addressed. Our work presents an original point of view, addressing the biopharmaceutical aspects of these nanovehicles by means of descriptive statistics of the state-of-the-art of solid lipid nanoparticles research. All the presented results, trends, graphs and discussions are based in a systematic (and reproducible) bibliographic search that considered only original papers in the subject, covering a 7 years range (2013-today), a period that accounts for more than 60% of the total number of publications in the topic in the main bibliographic databases and search engines. Focus was placed on the therapeutic fields of application, absorption and distribution processes and current efforts for the translation into the clinical practice of lipid-based nanoparticles. For this, the currently active clinical trials on lipid nanoparticles were reviewed, with a brief discussion on what achievements or milestones are still to be reached, as a way of understanding the reasons for the scarce number of solid lipid nanoparticles undergoing clinical trials.

Abstract: Diabetic nephropathy (DN) is one of the most common complications of diabetes mellitus. Owing to its complicated pathogenesis, no satisfactory treatment strategies for DN are available. Milkvetch Root is a common traditional Chinese medicine (TCM) and has been extensively used to treat DN in clinical practice in China for many years. However, due to the complexity of botanical ingredients, the exact pharmacological mechanism of Milkvetch Root in treating DN has not been completely elucidated. The aim of this study was to explore the active components and potential mechanism of Milkvetch Root by using a systems pharmacology approach. First, the components and targets of Milkvetch Root were analyzed by using the Traditional Chinese Medicine Systems Pharmacology database. We found the common targets of Milkvetch Root and DN constructed a protein-protein interaction (PPI) network using STRING and screened the key targets via topological analysis. Enrichment of Gene Ontology (GO) pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed. Subsequently, major hubs were identified and imported to the Database for Annotation, Visualization and Integrated Discovery for pathway enrichment analysis. The binding activity and targets of the active components of Milkvetch Root were verified by using the molecular docking software SYBYL. Finally, we found 20 active components in Milkvetch Root. Moreover, the enrichment analysis of GO and KEGG pathways suggested that AGE-RAGE signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway, and TNF signaling pathway might be the key pathways for the treatment of DN; more importantly, 10 putative targets of Milkvetch Root (AKT1, VEGFA, IL-6, PPARG, CCL2, NOS3, SERPINE1, CRP, ICAM1, and SLC2A) were identified to be of great significance in regulating these biological processes and pathways. This study provides an important scientific basis for further elucidating the mechanism of Milkvetch Root in treating DN.

Abstract: The coronavirus disease 19 (COVID-19) is a rapidly growing pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Its papain-like protease (SARS-CoV-2 PLpro) is a crucial target to halt virus replication. SARS-CoV PLpro and SARS-CoV-2 PLpro share an 82.9% sequence identity and a 100% sequence identity for the binding site reported to accommodate small molecules in SARS-CoV. The flexible key binding site residues Tyr269 and Gln270 for small-molecule recognition in SARS-CoV PLpro exist also in SARS-CoV-2 PLpro. This inspired us to use the reported small-molecule binders to SARS-CoV PLpro to generate a high-quality DEKOIS 2.0 benchmark set. Accordingly, we used them in a cross-benchmarking study against SARS-CoV-2 PLpro. As there is no SARS-CoV-2 PLpro structure complexed with a small-molecule ligand publicly available at the time of manuscript submission, we built a homology model based on the ligand-bound SARS-CoV structure for benchmarking and docking purposes. Three publicly available docking tools FRED, AutoDock Vina, and PLANTS were benchmarked. All showed better-than-random performances, with FRED performing best against the built model. Detailed performance analysis via pROC-Chemotype plots showed a strong enrichment of the most potent bioactives in the early docking ranks. Cross-benchmarking against the X-ray structure complexed with a peptide-like inhibitor confirmed that FRED is the best-performing tool. Furthermore, we performed cross-benchmarking against the newly introduced X-ray structure complexed with a small-molecule ligand. Interestingly, its benchmarking profile and chemotype enrichment were comparable to the built model. Accordingly, we used FRED in a prospective virtual screen of the DrugBank database. In conclusion, this study provides an example of how to harness a custom-made DEKOIS 2.0 benchmark set as an approach to enhance the virtual screening success rate against a vital target of the rapidly emerging pandemic.

Abstract: OBJECTIVES: Coronavirus disease 2019 (COVID-19) is rapidly spreading worldwide. Lianhua Qingwen capsule (LQC) has shown therapeutic effects in patients with COVID-19. This study is aimed to discover its molecular mechanism and provide potential drug targets. MATERIALS AND METHODS: An LQC target and COVID-19-related gene set was established using the Traditional Chinese Medicine Systems Pharmacology database and seven disease-gene databases. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and protein-protein interaction (PPI) network were performed to discover the potential mechanism. Molecular docking was performed to visualize the patterns of interactions between the effective molecule and targeted protein. RESULTS: A gene set of 65 genes was generated. We then constructed a compound-target network that contained 234 nodes of active compounds and 916 edges of compound-target pairs. The GO and KEGG indicated that LQC can act by regulating immune response, apoptosis and virus infection. PPI network and subnetworks identified nine hub genes. The molecular docking was conducted on the most significant gene Akt1, which is involved in lung injury, lung fibrogenesis and virus infection. Six active compounds of LQC can enter the active pocket of Akt1, namely beta-carotene, kaempferol, luteolin, naringenin, quercetin and wogonin, thereby exerting potential therapeutic effects in COVID-19. CONCLUSIONS: The network pharmacological strategy integrates molecular docking to unravel the molecular mechanism of LQC. Akt1 is a promising drug target to reduce tissue damage and help eliminate virus infection.