#These authors contributed equally to this work
Tetrandrine has a variety of anti-tumor effects including against or reversal of tumor chemoresistance, but its mechanism of against tumor chemoresistance is still unclear. Therefore, the analytical method of network pharmacology and molecular docking was used to investigate the mechanism by which tetrandrine acts in tumor chemoresistance. We used public databases (PubChem, SwissADEM, SwissTargetPrediction) to obtain the physicochemical information and targets of tetrandrine, and used gene databases (GeneCards and OMIM) to collected disease targets, respectively. The intersection targets of disease and drug were analyzed by RStudio. We built protein-protein interaction network through the STRING database, and used Cystoscope to screen out hub genes. GO and KEGG pathway enrichment analysis were analyzed by Metascape database and RStudio. “Component-target-pathway” network was erected by Cystoscope. Ultimately, the key targets were chosen to dock with tetrandrine via molecular docking to verify network analysis results. 29 common targets were screened out through intersection. AKT1, PIK3CA, PIK3CB, PIK3CG, JAK2, IGF1R, KDR, SRC and MTOR were the core targets. KEGG pathway enrichment mainly included PI3K-AKT signaling pathway, EGFR tyrosine kinase inhibitor resistance, and Rap1 signaling pathway. Molecular docking indicated that the configuration of protein binding of ligand is stable. In conclusion, the against tumor chemoresistance effect of tetrandrine has the characteristics of multiple targets and multiple pathways, and the prediction of network pharmacology and molecular docking indicated that MTOR, SRC, PIK3CA were the key targets of tetrandrine in tumor chemoresistance, which provides a scientific basis for subsequent research on its anti-tumor chemoresistance mechanism.
Tetrandrine, a bisbenzylisoquinoline alkaloidis, is the main active ingredient of Chinese herb medicine called Fang-ji (Stephaniae Tetrandrae Radix), exhibits a variety of anti-tumor activity including against or reversal of tumor chemoresistance. It has been reported that tetrandrine possessed the role as kinase-inhibitor, reversal of drug resistance, inhibition of angiogenesis, inducer of autophagy and caspase pathways in different cancers [
Chemotherapy is the main strategy for cancer treatment, but drug resistance is the reason of treatment failure and leads to tumor recurrence. So the exact clarification of the molecular mechanism of tumor chemoresistance and its reversal has always been the key research goal of cancer [
Network pharmacology, an appropriate approach for modern Traditional Chinese Medicine research, is a brand-new method that uses bioinformatics which contains systems biology, connectivity, network analysis and pleiotropy to predict and discern multiple drug targets and interplay in disease, and network pharmacology will provide more and more meaningful information for drug discovery development [
PubChem database (https://PubChem.ncbi.nlm.nih.gov) provides components’ normal name, PubChem CID, 2D and 3D structure, Canonical SMILES and other information for rectifying the identity of components. SwissADME database (http://swissadme.ch/), a free and simple web tool to assess drug-likeness, pharmacokinetics and medicinal chemistry friendliness of small molecules. we used PubChem database to obtain the 2D structure and Canonical SMILES of tetrandrine, used SwissADME to analyze the other physicochemical information of tetrandrine.
SwissTargetPrediction (http://www.swisstargetprediction.ch/), a database provides a very intuitive interface to predict small molecule protein targets, and the prediction is established on a combination of 3D and 2D similarity with a library of 370,000 known actives on over 3000 proteins from three different species. Tetrandrine’s 2D structure was imported (limit species to humans) into SwissTargetPrediction to predict the targets.
GeneCards, the human gene database (https://www.genecards.org/), contains exhaustive information about all annotated and predicted human genes. OMIM (https://www.omim.org/) provides information on all known mendelian disorders and over 15,000 genes. Using keywords “tumor/cancer/carcinoma chemoresistance, multidrug resistance” to search for disease related genes by both two databases.
Screening candidate targets related to tetrandrine and disease through RStudio software (version 3.6.3), which offers a wide variety of graphical and statistical techniques. This software is usually the tool of choice for bioinformatics analysis and statistical methods research.
The tetrandrine-disease target network was made by Cytoscape software (version 3.8.2), which is an information data editing and analysis software for designing, constructing, and drawing grids.
The STRING database (https://www.string-db.org/) currently covers 2.4 billion proteins from more than 5 thousand organisms, which is a database of known and predicted protein-protein interactions. We imported common targets into the STRING database and screened human targets with a confidence score >0.4. The TSV format of the Protein-protein interaction network was downloaded. Then screened core targets and subnets by cytoNCA, a plug-in of Cytoscape software, and the degree value, betweenness centrality, closeness centrality was applied for filtering major hub genes. we assessed the tetrandrine PPI network in antitumor chemoresistance.
Metascape database (https://metascape.org/) is a powerful gene function annotation analysis tool. We copied and pasted the common genes into the Metascape’s gene list, selected the species as “
The molecular docking approach was utilized to validate the association of tetrandrine and hub target gene. Importing the 2D structure of tetrandrine to Chemoffice, a chemical drawing tool, and converting it into 3D structure as mol2 format. The three core targets protein crystal structure of MTOR (ID: P42345), SRC (ID: P12931) and PIK3CA (ID: P42336) were downloaded as pdb file from the RCSB PDB database (https://www.rcsb.org/), a protein database, which offers archive-information about the 3D shapes of proteins, nucleic acids, and complex assemblies. We used visual bioinformatics tools AutoDockTools (version 1.5.6) to transform pdb files to pdbqt formats for molecular docking. The conformations of tetrandrine and the key target protein were visualized by PyMol software (version 2.4.1). Running all docking simulations with default settings and presenting with publication. The docking conformation that has docking affinity score –5.0 kcal/mol represents great binding interactions between the compound and its corresponding targets, and the lower the binding energy is, the better the ligand can bind to the protein.
Tetrandrine’s PubChem CID, Canonical SMILES (
Properties | Parameters | Tetrandrine |
---|---|---|
Identity information | PubChem CID | 73038 |
CanonicalMILES | CN1CCC2=CC(=C3C=C2C1CC4=CC | |
=C(C=C4)OC5=C(C=CC(=C5 )CC6C7 | ||
=C(O3)C(=C(C=C7CCN6C)OC)OC)OC)OC | ||
Physicochemical | Formula | C38H42N2O6 |
properties | Molecular weight | 622.75 g/mol |
Num. heavy atoms | 46 | |
Num. arom. heavy atoms | 24 | |
Fraction Csp3 | 0.37 | |
Num. rotatable bonds | 4 | |
Num. H-bond acceptors | 8 | |
Num. H-bond donors | 0 | |
Molar Refractivity | 186.07 | |
Fraction Csp3 | 51.00 | |
TPSA | 61.86 Å2 | |
Lipophilicity Log | iLOGP | 5.11 |
PO/W | XLOGP3 | 6.66 |
WLOGP | 5.75 | |
MLOGP | 3.73 | |
SILICOS-IT | 6.06 | |
Consensus | 5.46 | |
Water solubility | Log S (ESOL) | –8.02 |
Solubility | 5.96e-06 mg/ml; 9.57e-09 mol/l | |
Class | Poorly soluble | |
Log S (Ali) | –7.76 | |
Solubility | 1.08e-05 mg/ml; 1.73e-08 mol/l | |
Class | Poorly soluble | |
Log S (SILICOS-IT) | –10.80 | |
Solubility | 9.78e-09 mg/ml; 1.57e-11 mol/l | |
Class | Insoluble | |
Pharmacokinetics | GI absorption | High |
BBB permeant | No | |
P-gp substrate | No | |
CYP1A2 inhibitor | No | |
CYP2C19 inhibitor | No | |
CYP2C9 inhibitor | No | |
CYP2D6 inhibitor | No | |
CYP3A4 inhibitor | No | |
Log Kp (skin permeation) | –5.37 cm/s | |
Druglikeness | ||
Lipinski | Yes; 1 violation: MW > 500 | |
Ghose | No; 4 violations: MW > 480, WLOGP > 5.6, MR > 130, #atoms > 70 | |
Veber | Yes | |
Egan | Yes | |
Muegge | No; violations: MW > 600, XLOGP3 > 5 | |
Bioavailability Score | 0.55 | |
Medicinal | PAINS | 0 alert |
chemistry | Brenk | 0 alert |
Leadlikeness | No; 2 violations: MW > 350, XLOGP3 > 3.5 | |
Synthetic accessibility | 7.01 |
A total 98 drug genes were screened by the SwissTargetPrediction database. We finally obtained 753 disease related tumor chemoresistance targets after deleting duplicates from GeneCards and OMIM databases. We used the RStudio to read and obtain 29 common targets of tetrandrine and disease, drawing the Venn diagram (
In order to explain the therapeutic mechanism of the drug more comprehensively, we input the common targets to STRING to conduct a PPI network (
Applying the Metascape database, we did GO functional and KEGG pathway enrichment analysis of intersection targets. For GO functional analyses, we got 776 related items, including 702 biologic processes, 37 cellular component and 37 molecular function. As showed in
Molecular docking simulation was used to test and verify the mechanism of tetrandrine against tumor chemoresistance. we mainly concentrated our docking analysis on the three corn proteins Serine/threonine-protein kinase (MTOR), Proto-oncogene tyrosine-protein kinase (SRC) and Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA). As showed in
Tumor chemoresistance is an important factor for tumor treatment failure. Recently, the multi-target and multi-channel treatment of tumor by Traditional Chinese herb has received a lot of attention. Tetrandrine is a natural medicine with a variety of biological activities, and its anti-tumor activity is particularly prominent. A series of studies have shown that tetrandrine has obvious anti-different tumors function
As the results of physicochemical information about tetrandrine and network pharmacology showed, tetrandrine has a favorable pharmacokinetic profile, and the core genes of tetrandrine in anti-tumor chemoresistance included AKT1, PIK3CA, PIK3CB, PIK3CG, JAK2, IGF1R, KDR, SRC and MTOR, among which the top three were MTOR, SRC and PIK3CA.
Mammalian target of rapamycin (mTOR), a serine/threonine protein kinase in the downstream of the phosphatidylinositol 3-kinases (PI3K) family, indirectly or directly regulates the phosphorylation of more than 800 proteins, which adjusts the maintenance of cellular homeostasis by coordinating transcription, metabolism, translation, and autophagy with availability of amino acids, ATP, growth factors and oxygenis, uncontrolled activation of the mTOR is discovered in cells of the majority tumors [
Currently, several PI3K/Akt/mTOR pathway inhibitors and Src inhibitors have been developed and approved for the treatment of carcinomas. Studies have found that tetrandrine can play an anti-drug resistance effect by regulating the PI3K/Akt/mTOR signaling pathway as an autophagy agonist [
The result of KEGG functional enrichment analysis showed that the against tumor chemoresistance mechanism of tetrandrine mainly involve PI3K-AKT signaling pathway, EGFR tyrosine kinase inhibitor resistance, and Rap1 signaling pathway. This result in turn verifies our previous research findings that tetrandrine can reverse cisplatin resistance in non-small cell lung cancer by regulating the PI3K/AKT/ mTOR signaling pathway
In this study, the molecular docking technique validated the interactions between tetrandrine and the hub target genes. The interaction between MTOR, SRC, PIK3CA and tetrandrine displayed a strong binding affinity score of –8.6, –9.3, –10.2 kcal/mol, and the molecular docking results revealed that the ligand can bind to the protein well [
Tetrandrine was proven to have definite anti-tumour activities. However, the bioavailability, safety and pharmacokinetic parameter studies on tetrandrine are very limited in animal models, especially in clinical settings. And more efforts on different pharmacokinetic parameters, potentially involving human subjects, are required before judgment can be passed on the substance as a promising anticancer drug [
Integrated the result of network pharmacology and molecular docking, it is indicated that MTOR, SRC, PIK3CA were the key targets of tetrandrine against tumor chemoresistance. And PI3K-AKT signaling pathway, EGFR tyrosine kinase inhibitor resistance and Rap1 signaling pathway were the main mediation pathway for tetrandrine against tumor chemoresistance. In conclusion, our results provide the relevance between tetrandrine and tumor chemoresistance for the first-time using network pharmacology and molecular docking, which serves a new basis for future research on its anti-tumor chemoresistance mechanism.