3.1. Pharmacokinetics parameters of resveratrol
Detailed information on the oral bioavailability (OB), drug-likeness (DL) properties, blood-brain barrier (BBB) permeability, and other attributes of resveratrol was obtained by querying the TCMSP database. The results are shown in Table 1. Although resveratrol has low OB and DL values, it has been reported in the literature that resveratrol may have therapeutic effects in neurodegenerative diseases [20]; additionally, the US FDA has approved resveratrol as an anticancer and antioxidant agent for use in clinical treatment, showing that resveratrol has medicinal properties.
Table 1 Pharmacological and molecular properties of resveratrol
Molecule ID
|
MW
|
OB (%)
|
Caco-2
|
BBB
|
DL
|
MOL012744
|
228.26
|
19.07
|
0.80
|
-0.01
|
0.11
|
3.2. Screening of resveratrol- and TBI-related targets
A total of 577 resveratrol targets were obtained by searching the TCMSP, BATMAN-TCM, DrugBank, SuperPred, PharmMapper, and SwissTargetPrediction databases and conducting a literature search. A total of 9231 TBI-related targets were retrieved from the GeneCards database, and a total of 845 targets with a relevance score greater than 20 were selected. The targets were supplemented with 255 additional targets by searching the TTD, DrugBank, CTD, OMIM, and MalaCards databases. After the targets were reviewed, 1100 TBI-related targets were ultimately selected. The resveratrol and TBI-related targets were intersected, and a total of 165 targets of resveratrol in the treatment of TBI were obtained (Figure 1).
Fig 1 The overlapping targets of resveratrol and TBI
3.3. Drug-target-disease network construction
The resveratrol targets, the TBI-related targets, and the 165 resveratrol targets in TBI were introduced into Cytoscape 3.8.0, and a drug-target-disease network diagram was constructed (Figure 2) that involved 1,514 nodes and 1,677 edges. Among the nodes, the orange node represents the resveratrol target category, the yellow node represents the TBI-related target category, the green nodes represents the individual resveratrol targets, the blue nodes represent the individual TBI-related targets, the brown nodes represents the targets of resveratrol in the treatment of TBI, and the edges represent the interrelationships among the drug, targets, and disease. The figure shows that resveratrol may affect TBI by acting on multiple targets.
Fig 2 Drug-target-disease network of resveratrol in TBI treatment
3.4. PPI network construction and module analysis of resveratrol targets in TBI.
The STRING database and Cytoscape 3.8.0 software were used to construct the PPI network for the 165 overlapping targets, and a network with 165 nodes and 3672 edges was obtained (Figure 3). The "Network Analyzer" function was used to analyse the network and evaluate the importance of nodes with their degrees and combined scores. The nodes in the figure represent the targets, and the edges represent the associations between targets. The size of each node is proportional to its degree value. The larger the degree value, the larger the node, and the darker the colour. The thickness of the edge is directly proportional to the combined score. The larger the combined score, which indicates a closer connection between related targets, the thicker the edge and the darker the colour. It can be seen that there are interactions among these 165 targets, which indicates that these targets are related to each other and affect TBI through mutual coordination.
Fig 3 The PPI network of overlapping targets of resveratrol and TBI
The MCODE plug-in was used to analyse the functional modules of the PPI network, and 5 functional modules with nodes ≥4 and k-core ≥3 (MCODE 1–5) were identified (Figure 4). The MCODE 1 module contains 54 nodes and 1265 edges. MCODE 2 contains 26 nodes and 82 edges. MCODE 3 contains 8 nodes and 20 edges. MCODE 4 contains 6 nodes and 9 edges. MCODE 5 contains 5 nodes and 6 edges.
Fig 4 Module analysis of overlapping targets
To further analyse the functions of the above five modules, the targets of the modules were imported into the Metascape database for GO enrichment and KEGG pathway analysis and sorted according to -log10(p), and the first 20 entries were selected for inclusion in the diagram (Figure 5).
Fig 5 GO functional and KEGG pathway enrichment analysis of MCODE 1-5
The results of the functional module enrichment analysis show that the biological processes associated with MCODE 1 are mainly related to the positive regulation of cell migration, epithelial cell proliferation, response to oxidative stress, cytokine-mediated signalling, blood vessel development, and so on. The molecular functions associated with MCODE 1 are mainly involved in kinase, cytokine receptor, transcription factor, and phosphatase binding; protein kinase activity; and so on. The main cell components associated with MCODE 1 include membrane rafts, vesicle lumens, focal adhesions, RNA polymerase II transcription factor complexes, the basal part of the cell, and so on. The signalling pathways associated with MCODE 1 include pathways in cancer, the AGE-RAGE signalling pathway in diabetic complications, hepatitis B, endocrine resistance, EGFR tyrosine kinase inhibitor resistance, fluid shear stress and atherosclerosis, the FoxO signalling pathway, the HIF-1 signalling pathway, the JAK-STAT signalling pathway, insulin resistance, and so on. The biological processes associated with MCODE 2 are mainly related to the cellular response to hormone stimuli, phosphatidylinositol 3-kinase signalling, reactive oxygen species metabolism, the regulation of hormone secretion, the positive regulation of kinase activity, and so on. The molecular functions associated with MCODE 2 are mainly involved in insulin receptor substrate binding, glycosaminoglycan binding, SH2 domain binding, protein domain-specific binding, antioxidant activity, and so on. The main cell components associated with MCODE 2 include cell-cell junctions, transferase complexes, transferrin phosphorus-containing groups, membrane rafts, lytic vacuoles, receptor complexes, and so on. The signalling pathways associated with MCODE 2 include pathways in cancer, insulin resistance, adipocytokine signalling, peroxisomes, and neuroactive ligand-receptor interactions. The biological processes associated with MCODE 3 involve dopamine metabolism, organic hydroxy compound metabolism, monoamine transport, drug catabolism, and cofactor biosynthesis; the molecular functions associated with MCODE 3 include G protein-coupled amine receptor activity and oxidoreductase activity; the MCODE 3-associated cell components include glutamatergic synapses and dendrites; and the signalling pathways associated with MCODE 3 include serotonergic and dopaminergic synapses and neuroactive ligand-receptor interactions. The biological processes associated with MCODE 4 are related to behaviour, second-messenger-mediated signalling, the alcohol response, and the activation of protein kinase activity; the molecular functions associated with MCODE 4 are related to peptide binding; the MCODE-4-associated cell components include axons, membrane rafts, neuron cell bodies, and presynapses; and the signalling pathways associated with MCODE 4 are related to neuroactive ligand-receptor interaction. The biological processes associated with MCODE 5 are related to cell-matrix adhesion, axon guidance, the positive regulation of protein kinase activity, cell division, lymphocyte activation, and so on; the molecular functions associated with MCODE 5 are related to protein kinase activity and kinase binding; the MCODE 5-associated cell components include serine/threonine protein kinase complexes, the leading edge of the cell, and dendrites; and the signalling pathways associated with MCODE 5 are involved in viral carcinogenesis and cancer.
3.5. GO function and KEGG pathway enrichment analyses of targets for resveratrol against TBI
The 165 overlapping targets were imported into the Metascape database for GO functional and KEGG pathway enrichment analysis and sorted according to -log10(p), and the top 20 hits for each item were kept; the Bioinformatics platform was used to draw the GO bar graphs (Figure 6) and KEGG pathway bubble graphs (Figure 7). The results show that the targets are enriched in 303 biological processes, including the positive regulation of transferase activity, responses to toxic and inorganic substances, the positive regulation of cell migration, reactive oxygen species metabolism, the wound response, epithelial cell proliferation and so on. The targets are enriched in 117 molecular functions, including kinase binding, protein kinase activity, protein phosphatase binding, cytokine receptor binding, protein homodimerization, protease binding, transcription factor binding, and so on. The targets are enriched in 97 cell components, including membrane rafts, vesicle lumens, postsynapses, dendrites, receptor complexes, focal adhesions, endoplasmic reticulum lumens, cell-cell junctions, and so on. The targets are enriched in 148 signalling pathways, including pathways in cancer; the AGE-RAGE signalling pathway in diabetic complications; microRNAs in cancer, the FoxO signalling pathway, transcriptional misregulation in cancer, measles, and so on. The results show that resveratrol can play a role in the treatment of TBI by participating in the regulation of a variety of biological processes and multiple pathways.
Fig 6 GO functional enrichment analysis of overlapping targets
Fig 7 KEGG pathway enrichment analysis of overlapping targets
3.6. Construction of the drug-target-KEGG pathway network
The drug-target-KEGG pathway network was constructed using the Cytoscape 3.8.0 software, and the network contained 186 nodes and 734 edges. In Figure 8, the orange node represents the drug, the yellow nodes represent the targets, the green nodes represent the pathway, and the lines represent the relationships between the nodes. The results show that the targets of resveratrol are distributed among different pathways and participate in the pathological process of TBI through multiple targets acting on multiple pathways.
Fig 8 Drug-target-KEGG pathway network
3.7. Screening of the hub genes involved in the effect of resveratrol on TBI
The hub genes, as important nodes, play an important role in the PPI network. The "CytoHubba" plug-in was used to analyse the topology of the nodes in the PPI network, and the top 10 nodes in the network were selected based on the MCC calculation method. The results showed that insulin (INS), human insulin-like growth factor 1 (IGF1), tumor necrosis factor (TNF), tumor suppressor P53 (TP53), plasma albumin (ALB), interleukin 6 (IL6), SRC, signal transducer and activator of transcription 3 (STAT3), vascular endothelial growth factor A (VEGFA) and matrix metalloproteinase 9 (MMP9) may be the hub genes of resveratrol in TBI (Figure 9).
Fig 9 PPI network of the top 10 hub genes
3.8. Molecular docking between resveratrol and the hub genes
The AutoDockTools 1.5.6 software was used to verify the molecular docking between resveratrol and the 10 selected hub target proteins. If the binding free energy required for the interaction between the ligand and the receptor is less than 0 kcal•mol-1, it indicates that the two can bind spontaneously. If the binding free energy is less than -5 kcal•mol-1, it indicates that the two have good binding affinity. The smaller the binding free energy, the more stable the conformation formed by the ligand and the receptor. The results of the molecular docking analysis showed that resveratrol and the 10 hub target proteins can all be successfully docked (Table 2). Among them, the binding free energy of resveratrol with the IL6, MMP9, INS, and SRC proteins is less than -5 kcal•mol-1, showing a good binding affinity between them. The optimal binding configurations of resveratrol with the IL6, MMP9, INS, and SRC proteins were selected for further interaction analysis. The results showed that resveratrol can form hydrogen bonds with the amino acid residues LEU65 and GLU173 and form hydrophobic interactions with the residues PRO66, LEU166, and MET68 in IL6 (Figure 10 a-b); resveratrol can form hydrogen bonds with the key residue LEU418 and hydrophobic interactions with ARG424 and GLU416 in MMP9 (Figure 10 c-d); resveratrol forms 4 hydrogen bonds with INS, including CYS7, CYS6, CYS11 and SER9, and hydrophobic interactions with the LEU11, ALA14, LEU16, and LEU13 residues (Figure 10 e-f); resveratrol and SRC form hydrogen bonds between the GLU342 and MET344 residues and hydrophobic interactions between LEU396, VAL284, ALA296 and LEU276 (Figure 10 g-h).
Table 2 Information on molecular docking of resveratrol and 10 hub target proteins
Ligand
|
Receptor
|
Affinity (kcal•mol-1)
|
Resveratrol
|
IL6
|
-5.43
|
INS
|
-5.28
|
MMP9
|
-5.08
|
SRC
|
-5.01
|
TNF
|
-4.63
|
ALB
|
-4.25
|
IGF1
|
-3.94
|
STAT3
|
-3.76
|
TP53
|
-3.55
|
VEGFA
|
-3.42
|
Fig 10 The 2D and 3D molecular docking patterns of resveratrol with IL6 (a, b), MMP9 (c, d), INS (e, f), and SRC (g, h)