As a representative drug for the treatment of severe community-acquired pneumonia and sepsis, Xuebijing (XBJ) injection is also one of the recommended drugs for the prevention and treatment of coronavirus disease 2019 (COVID-19), but its treatment mechanism for COVID-19 is still unclear. Therefore, this study aims to explore the potential mechanism of XBJ injection in the treatment of COVID-19 employing network pharmacology and molecular docking methods. The corresponding target genes of 45 main active ingredients in XBJ injection and COVID-19 were obtained by using multiple database retrieval and literature mining. 102 overlapping targets of them were screened as the core targets for analysis. Then built the PPI network, TCM-compound-target-disease, and disease-target-pathway networks with the help of Cytoscape 3.6.1 software. After that, utilized DAVID to perform gene ontology (GO) function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to predict the action mechanism of overlapping targets. Finally, by applying molecular docking technology, all compounds were docked with COVID-19 3 CL protease(3CLpro), spike protein (S protein), and angiotensin-converting enzyme II (ACE2). The results indicated that quercetin, luteolin, apigenin and other compounds in XBJ injection could affect TNF, MAPK1, IL6 and other overlapping targets. Meanwhile, anhydrosafflor yellow B (AHSYB), salvianolic acid B (SAB), and rutin could combine with COVID-19 crucial proteins, and then played the role of anti-inflammatory, antiviral and immune response to treat COVID-19. This study revealed the multiple active components, multiple targets, and multiple pathways of XBJ injection in the treatment of COVID-19, which provided a new perspective for the study of the mechanism of traditional Chinese medicine (TCM) in the treatment of COVID-19.
Angiotensin-Converting Enzyme 2/metabolism* ; Biological Availability ; COVID-19/virology* ; Coronavirus 3C Proteases/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Humans ; Medicine, Chinese Traditional/methods* ; Molecular Docking Simulation/methods* ; Protein Interaction Mapping/methods* ; SARS-CoV-2/physiology* ; Signal Transduction/drug effects* ; Spike Glycoprotein, Coronavirus/metabolism*

Escherichia coli ; chemistry ; cytology ; Fluorine Radioisotopes ; MAP Kinase Kinase 5 ; chemistry ; metabolism ; MAP Kinase Kinase Kinase 3 ; chemistry ; metabolism ; Nuclear Magnetic Resonance, Biomolecular ; Protein Binding ; Protein Interaction Mapping ; methods ; Protein Interaction Maps

Bacterial two-hybrid system is a newly developed method for studying protein-protein interactions. However, in our studies of the interaction of regulatory proteins in Streptomyces, it was found that the bacterial two-hybrid system is not sensitive enough by the blue-and-white selection on X-gal plate. To overcome this drawback, the reason of false positive clone was firstly determined, which was the disturbance of other direct or indirect regulation on lacZ promoter. Then the disturbance was diluted by introducing multicopy lacZ promoter, which drive another reporter gene gfp. By such design, the sensitivity of the modified bacterial two-hybrid system was significantly inproved and the two different reporters also help to decrease the rate of the false positive clones. Further the evaluation of the modifiedd bacterial two-hybrid system indicated that the sensitivity was significantly improved.
Bacteria ; Genes, Reporter ; Promoter Regions, Genetic ; Protein Interaction Mapping ; methods ; Two-Hybrid System Techniques

Atherosclerosis is a complex disease characterized by lipid accumulation in the vascular wall and influenced by multiple genetic and environmental factors. To understand the mechanisms of molecular regulation related to atherosclerosis better, a protein interaction network was constructed in the present study. Genes were collected in nucleotide database and interactions were downloaded from Biomolecular Object Network Database (BOND). The interactional data were imported into the software Cytoscape to construct the interaction network, and then the degree characteristics of the network were analyzed for Hub proteins. Statistical significance pathways and diseases were figured out by inputting Hub proteins to KOBAS2. 0. The complete pathway network related to atherosclerosis was constructed. The results identified a series of key genes related to atherosclerosis, which would be the potential promising drug targets for effective prevention.
Atherosclerosis ; genetics ; Databases, Factual ; Humans ; Protein Interaction Mapping ; methods ; Protein Interaction Maps ; Software

Animals ; Databases, Protein ; Humans ; Models, Molecular ; Protein Interaction Domains and Motifs ; Protein Interaction Mapping ; methods ; Protein Interaction Maps ; Proteins ; chemistry ; metabolism ; Proteome ; chemistry ; metabolism

Drug targets discovery is one of the most important elements in new drug development, and a variety of methods have been developed recently from this point of view. This paper proposed a network-based local and global consistency for cardiovascular genes identification. Results were evaluated through the widely used database HPRD and DrugBank. Results showed that our algorithm can give reasonable candidate targets set. The method in this paper could be an impressive solution for targets searching.
Algorithms ; Cardiovascular Diseases ; genetics ; metabolism ; prevention & control ; Databases, Protein ; Drug Delivery Systems ; methods ; Drug Discovery ; methods ; Gene Regulatory Networks ; Humans ; Models, Theoretical ; Pharmaceutical Preparations ; administration & dosage ; metabolism ; Protein Binding ; Protein Interaction Mapping ; methods ; Proteins ; genetics ; metabolism

Network pharmacology, as a new developmental direction of drug discovery, was generating attention of more and more researchers. The key problem in drug discovery was how to identify the new interactions between drugs and target proteins. Prediction of new interaction was made to find potential targets based on the predicting model constructed by the known drug-protein interactions. According to the deficiencies of existing predicting algorithm based bipartite graph, a supervised learning integration method of bipartite graph was proposed in this paper. Firstly, the bipartite graph network was constructed based on the known interactions between drugs and target proteins. Secondly, the evaluation model for association between drugs and target proteins was created. Thirdly, the model was used to predict the new interactions between drugs and target proteins and confirm the new predicted targets. On the testing dataset, our method performed much better than three other predicting methods. The proposed method integrated chemical space, therapeutic space and genomic space, constructed the interaction network of drugs and target proteins, created the evaluation model and predicted the new interactions with good performance.
Algorithms ; Drug Delivery Systems ; methods ; Drug Discovery ; methods ; Genomics ; methods ; Models, Theoretical ; Pharmaceutical Preparations ; administration & dosage ; metabolism ; Protein Binding ; Protein Interaction Mapping ; methods ; Proteins ; genetics ; metabolism

Detection of protein-protein interaction can provide valuable information for investigating the biological function of proteins. The current methods that applied in protein-protein interaction, such as co-immunoprecipitation and pull down etc., often cause plenty of working time due to the burdensome cloning and purification procedures. Here we established a system that characterization of protein-protein interaction was accomplished by co-expression and simply purification of target proteins from one expression cassette within E. coli system. We modified pET vector into co-expression vector pInvivo which encoded PPV NIa protease, two cleavage site F and two multiple cloning sites that flanking cleavage sites. The target proteins (for example: protein A and protein B) were inserted at multiple cloning sites and translated into polyprotein in the order of MBP tag-protein A-site F-PPV NIa protease-site F-protein B-His(6) tag. PPV NIa protease carried out intracellular cleavage along expression, then led to the separation of polyprotein components, therefore, the interaction between protein A-protein B can be detected through one-step purification and analysis. Negative control for protein B was brought into this system for monitoring interaction specificity. We successfully employed this system to prove two cases of reported protien-protein interaction: RHA2a/ANAC and FTA/FTB. In conclusion, a convenient and efficient system has been successfully developed for detecting protein-protein interaction.
Endopeptidases ; genetics ; metabolism ; Escherichia coli ; genetics ; Plum Pox Virus ; enzymology ; genetics ; Protein Interaction Mapping ; methods ; Proteolysis

Membrane protein and its interaction network have become a novel research direction in bioinformatics. In this paper, a novel membrane protein interaction network simulator is proposed for system biology studies by integrated intelligence method including spectrum analysis, fuzzy K-Nearest Neighbor(KNN) algorithm and so on. We consider biological system as a set of active computational components interacting with each other and with the external environment. Then we can use the network simulator to construct membrane protein interaction networks. Based on the proposed approach, we found that the membrane protein interaction network almost has some dynamic and collective characteristics, such as small-world network, scale free distributing, and hierarchical module structure. These properties are similar to those of other extensively studied protein interaction networks. The present studies on the characteristics of the membrane protein interaction network will be valuable for its relatively biological and medical studies.
Algorithms ; Animals ; Artificial Intelligence ; Computational Biology ; methods ; Computer Simulation ; Humans ; Membrane Proteins ; chemistry ; Protein Binding ; Protein Interaction Mapping ; methods ; Protein Interaction Maps

An increasing body of evidence shows that the lipid droplet, a neutral lipid storage organelle, plays a role in lipid metabolism and energy homeostasis through its interaction with mitochondria. However, the cellular functions and molecular mechanisms of the interaction remain ambiguous. Here we present data from transmission electron microscopy, fluorescence imaging, and reconstitution assays, demonstrating that lipid droplets physically contact mitochondria in vivo and in vitro. Using a bimolecular fluorescence complementation assay in Saccharomyces cerevisiae, we generated an interactomic map of protein-protein contacts of lipid droplets with mitochondria and peroxisomes. The lipid droplet proteins Erg6 and Pet10 were found to be involved in 75% of the interactions detected. Interestingly, interactions between 3 pairs of lipid metabolic enzymes were detected. Collectively, these data demonstrate that lipid droplets make physical contacts with mitochondria and peroxisomes, and reveal specific molecular interactions that suggest active participation of lipid droplets in lipid metabolism in yeast.
Animals ; Cell Line ; Genetic Complementation Test ; Lipid Metabolism ; Lipids ; Microscopy, Electron, Transmission ; Microscopy, Fluorescence ; Mitochondria ; metabolism ; Muscle Cells ; metabolism ; Muscle, Skeletal ; cytology ; metabolism ; Oncogene Proteins ; genetics ; metabolism ; Peroxisomes ; metabolism ; Plasmids ; Protein Binding ; Protein Interaction Mapping ; methods ; Rats ; Recombinant Fusion Proteins ; genetics ; metabolism ; Saccharomyces cerevisiae ; Transcription Factors ; genetics ; metabolism ; Transformation, Genetic