Reagents and materials
1-Ethyl-3-(3-dimetylaminopropyl)-carbodiimide hydrochloride (EDC) was obtained from Shanghai Beinuo Biotechnology Co., Ltd. (Shanghai, China), and N-hydroxysuccinimide (NHS) was purchased from Shanghai Dibai Biotechnology Co., Ltd. Sodium acetate and dimethyl sulfoxide (DMSO) were purchased from Beijing Chemical Plant (Beijing, China). Ethanolamine hydrochloride was purchased from Shanghai Sanying Chemical Reagent Co., Ltd. (Shanghai, China). The protein TNF-a was provided by RD Biosciences (USA). Artemisinin, scopoletin, arteannuin B and artemisinic acid were provided by Chengdu Ruifensi Biological Technology Co., Ltd. (Chengdu, China), and Dulbecco’s phosphate-buffered saline PBS buffer (pH 4.7) was freshly prepared.
Plasma sample preparation
Approximately 40 mg of EDC and 10 mg of NHS were weighed, and 1 mL of solution was prepared with distilled water. This solution was injected within 5 min into two channels that were thoroughly rinsed with PBS buffer.
Fifty micrograms of TNF-a protein was dissolved in 100 μL of PBS, and 10 μL of this solution was taken in three portions and diluted with sodium acetate solutions with pH values of 5.5, 6.0, and 6.5, respectively, and the final concentration was 50 μg/mL. The flow rate was reduced to 20 µL/min, and the left channel was rinsed for 10 min to determine the optimal pH of sodium acetate.
After determination of the optimal pH value, 1 M ethanolamine hydrochloride was injected into the two channels for 10 min to complete the sample fixation.
The four chemical compounds, scopoletin (A), artemisinin (B), artemisinic acid (C) and arteannuin B (D), were divided into 12 groups according to the combination rule of A, B, C, D, AB, AC, AD, ABC, ABD, ACD, BCD, and ABCD, and each group had 6 concentration levels. The control group was PBS buffer at pH 7.4.
Next, 19.2 mg of Scutellaria lactone, 28.2 mg of artemisinin, 24.8 mg of artemisinin 2 and 23.4 mg of artemisinin were accurately weighed and dissolved in 1 mL DMSO (dimethyl sulfoxide). The DMSO solution in each group was gradient-diluted with PBS to final concentrations of 200 μM, 66.7 μM, 22.2 μM, 7.41 μM, and 2.47 μM.
Target fishing
Known therapeutic targets for the treatment of malaria were obtained from the DrugBank database (http://www.drugbank.ca/, version 4.3) [15]. The prediction of drug targets based on ligand structural features primarily includes chemical similarity searches and reverse pharmacophore searches. The theoretical basis of the chemical similarity search is that small molecular compounds with similar structural or physicochemical properties act on targets with the same or similar properties: “antimalaria” was selected as the key word, and the drug-target interactions of drugs approved by the USA Food and Drug Administration (FDA) for the treatment of menstrual disorders. All target gene/protein identifiers (IDs) were converted into the corresponding gene symbol/UniProtKB-Swiss-Prot IDs to facilitate further data analyses. After removing redundant entries, 25 target genes corresponding to 15 known antimalarial drugs were retrieved.
Protein‑protein interaction (PPI) data
PPI data were imported from the Human Annotated and Predicted Protein Interaction Database (HAPPI, http://bio.informatics. iupui.edu/HAPPI/, Version 31.2) [16]. Based on this PPI network database, an interaction network of Artemisia annua candidate target groups and known antimalarial drug target groups was constructed, and the distribution of target nodes in metabolic pathways and the corresponding diseases was determined. A direct interaction network of key nodes was established and divided into different modules according to the functions of the nodes. According to the malaria pathway (ko05144: Malaria) in the Kyoto Encyclopedia of Genes and Genomes (KEGG), molecules closely related to the malaria pathway were selected as candidates to be verified from the key nodes. The MCODE algorithm is used to intersect the PPI network for module analysis. The score was 2.2-4.7, while the node was 3-21, and the edge was 2-58.
3. The unit of docking score is kJ/mol. And the unit was mentioned in the manuscript.
Network construction and topological analysis
Compound–target (C-T), target–pathway (T-P), and target–disease (T-D) networks of malaria were constructed using Cytoscape 3.2 software (https://cytoscape. org/download.html), which is a general bioinformatics software package for data integration and visualization of biological networks (Bindea et al., 2009; Smoot et al., 2011). An interaction network of Artemisia annua candidate target genes with known antimalarial drug target genes was established and consisted of 85 nodes and 298 pairs of interactions. The topological characteristic value of each node was calculated in the network, and the median of the topological characteristic value was used as the card value. A total of 32 key nodes were screened. A direct interaction network of key nodes was established and processed according to the node functions. The module was divided, the malaria pathway in KEGG (ko05144: Malaria) was compared, and molecules closely related to the malaria pathway were selected as candidates for verification from the key nodes.
Molecular docking
The molecular structures of CDK4, NFKB1, PIK3CG, MAPK1, TNF and ITGB2 human protein targets were searched in the database UniProt (http://www.uniprot.org/). The structures of scopolamine and artemisinic acid were downloaded from the PubChem database (https://pubchem.ncbi.nlm.nih.gov). Chemical compositions and protein structures were dehydrated and hydrotreated, respectively. Molecular docking and figures were generated using Discovery Studio Visualizer 2.5 software.
Probe Kd determination
Approximately 40 mg of EDC and 10 mg of NHS were weighed, and 1 mL of solution was prepared with distilled water. This solution was injected within 5 min into two channels that were thoroughly rinsed with PBS buffer. Next, 19.2 mg of scopolamine, 28.2 mg of artemisinin, 24.8 mg of artemisinin, and 23.4 mg of artemisinic acid were precisely weighed in 1 mL DMSO and mixed well. TNF-α protein was immobilized on grafted sensor chips. The compound monomers and combinations were divided into 12 groups (Table 1). Each group of samples was injected from low to high concentrations, and a control group (PBS) was set at each concentration. Regression analysis was performed when concentration curves were separated and approaching equilibrium. The dissociation constant (Kd) and its maximum value (Bmax) were calculated by fitting the titration curve to the single-site saturation binding equation [Y = Bmax*X/(Kd+X)] using GraphPad Prism software (GraphPad Software Incorporated, La Jolla, CA, USA).
Table 1 Compound monomers and combinations
Group
|
Compounds
|
A
|
Scopoletin (C10H8O4)
|
B
|
Artemisinin (C15H22O5)
|
C
|
Artemisinic acid (C15H22O2)
|
D
|
Arteannuin B (C15H20O3)
|
AB
|
Scopoletin; Artemisinin
|
AC
|
Scopoletin; Artemisinic acid
|
AD
|
Scopoletin; Arteannuin B
|
ABC
|
Scopoletin; Artemisinin; Artemisinic acid
|
ABD
|
Scopoletin; Artemisinin; Arteannuin B
|
ACD
|
Scopoletin; Artemisinic acid; Arteannuin B
|
BCD
|
Artemisinin; Artemisinic acid; Arteannuin B
|
ABCD
|
Scopoletin; Artemisinin; Artemisinic acid; Arteannuin B
|