Elucidation of Therapeutic Mechanism of Lipopeptide Iturin A from Bacillus aryabhattai on Lung Cancer Through Integration of Network Pharmacology, Molecular Docking, Molecular Dynamics Simulation and In Vitro Analysis

doi:10.21203/rs.3.rs-4900157/v1

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Elucidation of Therapeutic Mechanism of Lipopeptide Iturin A from Bacillus aryabhattai on Lung Cancer Through Integration of Network Pharmacology, Molecular Docking, Molecular Dynamics Simulation and In Vitro Analysis

https://doi.org/10.21203/rs.3.rs-4900157/v1

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This study used network pharmacology to evaluate iturin A's mechanism of action on lung cancer. Iturin action targets were gathered using the Swiss Target Prediction and PubChem databases. The Gene Cards database was utilised to gather pertinent target sets for lung cancer, and the drug-disease target intersection was identified as a possible site of iturin activity in lungcancer. Using a target protein-protein interaction (PPI) network constructed with the STRING database, topological network analysis was used to identify the primary target genes of iturin A in lung cancer. Subsequently, Cytoscape 3.7.1 was used to import the data. The Shiny database was used to analyse the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology (GO) functional enrichment. Three common targets between lung cancer and iturin A were identified through target intersection. Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) may be the primary target of iturin activity on lung cancer, according to the PPI map and topological study. According to molecular docking experiments, iturin A had the highest binding affinity to the target. Later, the phosphatidylinositol 4,5-bisphosphate 3-kinase complexed with Iturin A underwent a 200 ns molecular dynamics simulation within a physiological environment. The results illustrated that the ligand maintained a relatively constant shape throughout the simulation. Iturin A was used to treat human lung cancer A549 cells, and the results of the MTT test demonstrated inhibitory action with an IC50 value of 7.73 µM. This allowed for an assessment of the cell's viability. These findings validated iturin-A as an anticancer agent. The combined insights from our network analysis, in-silico tests, and in vitro analyses collectively underscore the potential efficacy of Iturin A in fighting lung cancer.

Health sciences/Oncology

Biological sciences/Computational biology and bioinformatics/Network topology

Biological sciences/Computational biology and bioinformatics/Cellular signalling networks

Iturin A

Network pharmacology

lung cancer

KEGG

A malignant tumour that begins in the lung is lung cancer, sometimes referred to as lung carcinoma. Lung cancer typically affects smokers and starts in the lungs. Narrow and non-small cell cancers are the two primary forms of lung cancer. The DNA of cells in the airways becomes damaged genetically, which is the cause of lung cancer. This damage is frequently brought on by smoking cigarettes or breathing harmful substances (air pollution). Unchecked multiplication of damaged airway cells leads to tumor formation. Tumours damage lung function if left untreated, spreading throughout the organ. Thyroid cancers eventually spread to other regions of the body when they metastasise. Globally, lung cancer is the most prevalent type of cancer. It is responsible for 12.3% of all malignancies with an estimated 1.2 million new cases annually ¹. The primary cause of lung cancer is tobacco use, with 80% to 90% of cases occurring in cigarette smokers. The incidence of lung cancer varies significantly by region, race, and gender, and some research indicates that women may be more susceptible to the carcinogens in tobacco smoke. Compared to lifelong nonsmokers, lifetime smokers have a 20–30-fold higher risk of acquiring lung cancer. While the number of smokers in the USA is declining, there is an epidemic of smoking in China and Eastern Europe that will add tens of millions of new instances to the smoking population this century ². Interestingly, lung cancer can be prevented and generally, after a seven-year lag, quitting cigarettes lowers the risk. However, this decreased risk never goes back to normal, and lung cancer is increasingly striking those who have quit smoking in the US. Despite advancements in treatment, ninety per cent of lung cancer patients will die from their disease. It is estimated that 1.1 million deaths worldwide from lung cancer occurred in 2000, making upto 17.8% of all deaths from cancer. Nonetheless, just 11% of chronic smokers get lung cancer, suggesting that the illness may have inherited tendencies ^3,4.

PIK3CA, or phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha, is the gene that codes for the p110 alpha (p110α) protein, a subunit of PI3K. The p110α protein is the catalytic subunit since it performs PI3K's job; the other subunit, produced by a different gene, regulates the enzyme’s activity. Like other kinases, PI3K adds a phosphate group, or a cluster of phosphorus and oxygen atoms, to other proteins to phosphorylate them. Specific signalling molecules are phosphorylated by PI3K, which sets off a chain of other events that carry chemical messages throughout cells. Numerous cellular processes, such as cell growth and division (proliferation), migration, synthesis of new proteins, intracellular material transport, and cell survival, depend on PI3K signalling. According to studies, PI3K signalling may be necessary for the maturation of adipocytes or fat cells and may regulate several hormones ^5,6. Mutations in the PIK3CA gene linked to cancer produce a modified p110α subunit, which permits unregulated PI3K signalling. An unchecked cell proliferation that results in cancer can be attributed to increased signalling. The distinct functions of PIK3CA is head and neck squamous cell carcinoma enrichment and maintenance of cancer stem cells. MicroRNA3633p inhibits cell proliferation and induces apoptosis in retinoblastoma cells via the Akt/mTOR signalling pathway that targets PIK3CA ⁷. The illness known as lung cancer is characterised by the unchecked development and multiplication of lung tissue cells, brought on by variations in specific genes inside the body. While the majority of lung cancer patients acquire a genetic mutation as a result of environmental exposure to carcinogens, in certain instances, these mutations may be inherited from a family member who has the illness. EGFR and KRAS are the two most prevalent genetic alterations associated with lung cancer. Up to half of all instances of lung cancer have the epidermal growth factor receptor (EGFR), a crucial gene in the pathophysiology of the disease. The receptor protein produced in response to EGFR is incorporated into the cell membrane and controls signalling pathways that lead to cell division and growth ⁸.

A mutation in the EGFR gene can change the expressed proteins, activating the signalling pathways continuously and causing unchecked cell growth. Numerous more genes have also been linked to the pathophysiology of lung cancer. More specifically, mutations in MET, LKB1, BRAF, PIK3CA, ALK, RET and ROS1 genes may be responsible for the illness. Of the 110 core genes for lung cancer, 34 have been chosen as target genes by the GeneCards Database. Some strains of Bacillus subtilis produce iturinA, a lipopeptide biosurfactant with antifungal properties. Iturin has a molecular mass of around 1.1 kDa. iturin A has two main sections: an 11–12 carbon hydrophobic tail and a peptide portion with seven amino acid residues (Figure 1). The compound's amphiphilic nature is evident from its structure, suggesting that the cellular membranes are likely the location of action. Iturin lipopeptide is a cyclic peptide consisting of seven amino acids (heptapeptides) connected to a chain of fatty acids that can have carbons ranging from C-14 to C-17. The food, oil, and pharmaceutical industries can benefit from these compounds' biological and physicochemical features, making them highly desirable ^9,10.

All strains of Bacillus subtilis produce this family of lipopeptides. The 38–40 kb Bacillus sp. The iturin operon comprises four open reading frames: ItuA, ItuB, ItuC, and ItuD. Iturin A's antifungal action is facilitated by its unique structure, including a cyclic peptide ring connected to a lipid tail ¹¹. Fungal cell membrane integrity may be compromised, resulting in cell lysis and eventual death ¹². Iturin A has been researched and used as a biological control agent against many plant infections in agriculture. Because of its capacity to inhibit fungal infections, it is an excellent choice for environmentally responsible and sustainable crop protection. Iturin A's antibacterial qualities have drawn interest from the pharmaceutical sector for possible therapeutic uses. Nevertheless, additional investigation is required to examine its effectiveness and safety in medical settings. The foundation of network pharmacology is the interdisciplinary theory of pharmacology and biology, which uses cutting-edge technologies like omics, high-throughput screening, and network analysis. It can provide light on the intricate network interaction between "ingredient-gene-target-disease," aid in the multidimensional understanding of the molecular causes of disease, and forecast possible medication pharmacological mechanisms ¹³. According to Yaraguppi et al (2023),; Computational modeling and simulation study have substantially improved the structural characteristics, molecular interactions, and mechanisms of action of iturin compounds. Thanks to the significant understandings of the conformational dynamics, stability, and interactions of iturin molecules, we now have a clearer understanding of their biological significance. With the use of computational techniques including molecular docking, virtual screening, and molecular dynamics simulations, several properties of iturin compounds have been studied. It was discovered that increased DNA fragmentation and protein modifications, including those of CD-31, Ki-67, p-Akt, p28 MAPK, apoptotic proteins, and anti-apoptotic proteins, were associated with iturin A's enhanced anticancer efficacy. Iturin A, a chemical derived from marine bacteria, and its possible anticancer effects on human breast cancer cells. This assessment included both animal models and in vitro investigations, with a particular emphasis on the target, the Akt pathway. MTT tests were used to evaluate iturin A's inhibitory effect on breast cancer cell growth ¹¹.

2.1 Chemicals and cell lines

All the chemicals employed to study the cytotoxicity effect were procured from Gibco, Invitrogen, and Thermofisher Scientific. Lung cancer cell line A549 used in the present study were procured from the National Centre for Cell Science, Pune, India.

2.2 Identification of active components of iturin A

Iturin A from the SwissTarget Prediction database was selected, and the complete dataset from the PubChem database was obtained for examination ¹⁴. The likely proteins iturin A could bind to were predicted using SwissTarget Prediction. A comprehensive literature search was performed using Google Scholar, and PubMed. Several public repositories were searched for active compounds using "Iturin A". A screening process involving one hundred probable targets was conducted to eliminate redundant targets from the target prediction. The compounds’ oral bioavailability (OB) discovered through literature and database searches was predicted using the Swiss ADME ¹⁵. OB is the percentage of a medication absorbed orally and enters the circulation. On the other hand, an intravenous medication swiftly enters the bloodstream and moves via the systemic circulation to the pharmacological site of need. Drug-likeness (DL), which encompasses elements like transporter effects, metabolic stability, permeability, and solubility, is significant in drug design and development. Among other aspects of pharmacological behaviour, these traits may influence a drug's metabolism, oral bioavailability, and potential toxicity ¹⁶.

2.3 Effective targets for lung cancer

One search across the above databases yielded 110 targets associated with LuCa genes. Three targets, iturin A and lung cancer shared, were found using target intersection. The PPI map and topological investigation indicate that iturin A acting on lung cancer may primarily target phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) and lung cancer genes AKT1, PIK3CA, and EGFR. This was determined using the Swiss Target Prediction databases (http://www.swisstargetprediction.ch/). Additionally, common proteins between anticipated targets of provided ligands and proteins in lung cancer were selected using Venny 2.1.0 (https://bioinfogp.cnb.csic.es/tools/venny/) ¹⁷.

2.4 Construction of protein-protein interaction network (PPI) and critical targets

The network structure was visually shown and examined using the Cytoscape software. Annotations, gene expression profiles, and other state data can be integrated with molecular interaction networks and biological pathways to provide an open-source software platform for visualising these networks. In this study, two networks were built: (1) iturin A and its related components were joined to create a component-component target network; (2) the core network was screened based on the degree of value of the component-component target networks.

Gene expression patterns and other state data can be integrated with molecular interaction networks using the open-source bioinformatics software platform Cytoscape ¹⁸. There are plugins available for more functionality. Various layouts, additional file format support, database connectivity, network and molecular profiling analysis, and large-scale network searching are all supported by plugins. Although Cytoscape is neutral in terms of usage, biological research applications are the ones that use it the most. Any network graph, including social networks, may be shown and analysed using Cytoscape. Part of Cytoscape's software design is the usage of plugins for specific functions. The core developers and the larger user community contribute to creating plugins ¹⁹.

2.5 GO and KEGG pathway enrichment analysis

Genes on KEGG pathway maps may be visualised using Shiny Gene Ontology (GO) tools, which also revealed enhanced biological themes, mainly GO terms like biological process (BP), cell component (CC), and molecular functions (MFs). The organism that was limited to "Homo sapiens" was added to the Shiny GO database as the target. The identified GO keywords' dividing value was FDR < 0.05, while KEGG pathways were set to P < 0.05. The Kyoto Encyclopaedia of Genes and Genomes (KEGG) database includes information about biological pathways, drugs, diseases, and genomes. KEGG is utilised in translational research in drug development, modelling and simulation in systems biology, and data processing in genomics, metagenomics, metabolomics, and other omics studies in bioinformatics research and education. It incorporates the system's wiring diagrams and building blocks, namely the molecular interaction and reaction networks wiring diagrams, genetic building blocks of genes and proteins, and chemical building blocks of tiny molecules and processes. The following KEGG databases divided into systems, genetic, chemical, and health information databases actualise this idea ²⁰.

2.6 Molecular docking of compound and target

We performed molecular docking using PPI network molecules and targets associated with Lung cancer. The AutoDock Vina, PyMOL, and Discovery Studio 4.5 Client software packages examined the possible interactions between the significant targets and the putative active chemicals. The method of action and binding affinity of a small molecule ligand with a target protein were predicted by applying molecular docking ²¹. The RCSB PDB was used to obtain the protein structures of several significant targets, including PGR (PDB ID: 4JPS). PDB is a global, central repository for three-dimensional protein and nucleic acid structures. It includes information on proteins compiled by researchers using nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography worldwide. The docking analysis produced the binding scores. A docking study indicates that the biosurfactant iturin A has several molecules with a strong affinity for different target proteins. A crucial step in computer-aided drug development is molecular docking. It makes accurate molecule binding possible by making it easier to predict the intermolecular structure created when a protein interacts with a ligand. The AutoDock Vina tool used the Lamarckian Genetic Algorithm (LGA) and an integrated empirical free energy function to accomplish docking. AutoGrid was used to compute the grid mappings. A grid map with 20 x 20 x 20 spaces is used for all dockings. The optimal conformation with the lowest docked energy was chosen from the docking search. Utilising Pymol, UCSF Chimaera, and Accelrys Discovery Studio Visualizer software, complex protein-ligand conformation interactions, such as hydrogen bond lengths, were investigated ²².

2.7 Molecular dynamics simulation

An essential technique for assessing the stability and compactness of docked complexes is molecular dynamics (MD) simulations. Gromacs-2019 performed a molecular dynamics simulation of the chosen protein-ligand combination. Before the system was finished, the Hoover was decreased for 1500 steps using the steepest descent method. Subsequently, the complicated structures were solved using a water simple point charge (SPC) water model in a cubic periodic box of 0.5 nm. Then, by adding Cl and Na + counterions in the right amounts, the complex systems' salt content was kept at 0.15 M. Preparing the plan was advised based on a previously published study. For every final structure from the NPT equilibration phase, a 200 ns simulation of the final manufacturing run in the NPT ensemble was done. The GROMACS simulation suite of Protein RMSD, RMSF, RG, SASA, and H-Bond was used for trajectory analysis(Hollingsworth et al., 2018; dos Santos Nascimento et al., 2022).

2.8 Principal component analysis and Gibbs free energy calculation

The structural alterations in our study are understood via the use of analytical methods such as Gibbs Free Energy (GFE) and Principal Component Analysis (PCA). While the GFE offers a thermodynamic viewpoint that aids in evaluating the stability of various protein conformations, the PCA sheds light on the overall mobility and variability of atomic coordinates. When taken as a whole, these assessments add to a thorough knowledge of the system's dynamic behaviour and energetic environment. PCA was utilised, as previously mentioned, to capture the sharp variations in protein residues. Studies by Rajendran et al. (2014) have shown that stability levels of protein molecules are critical for their appropriate functional performance, and this was taken into account while evaluating the variability in GFE values at the same time. Understanding the thermodynamic characteristics that underline the creation of antibody-antigen complexes and protein-protein interactions is made possible by the computation of GFE. We only took into account the Cα coordinates while computing the covariance matrix. Eigenvectors and Eigenvalues might be derived more easily with the help of subsequent diagonalization. Next, a trajectory with 2000 pictures was used for PCA, and the first two principal components (PC1 and PC2) were identified for further study. Additionally, the free energy landscape was created using techniques described in earlier research by Sun et al. and Martis and Coutinho

2.9 Evaluation of cytotoxicity

An in-vitro 3-(4, 5-dimethylthiazol2-yl) − 2,5-diphenyltetrazolium bromide (MTT) method described previously (Shettar et al., 2023) was adopted to evaluate the cytotoxicity of purified recombinant iturin A on selected lung cancer cell line A549. Recombinant iturin A concentration range of 0.125-128 µM was evaluated on the cell lines with triplicate treatment. Doxorubicin was used as a standard drug ²⁶. A 96-well microplate was used to seed around 5000 cells/well for 24 h of incubation. The seeded cells were treated with varied defined concentration range of iturin A and followed with incubation for 48 h. Cell washing was done with phosphate buffered saline several times. MTT of 0.5 mg/ml was added to the cells and incubated for 7h. The obtained formazan crystals were solubilized using dimethyl sulfoxide and the absorbance of the solution was recorded at 570 nm. The cells without the treatment were referred to as untreated cells. The cell viability (%) of cells treated with iturin A was calculated. A plot of cell viability % vs iturin A concentration was plotted and IC₅₀ value was calculated.

3.1 Identification of targets for lung cancer

A scan of the databases mentioned above produced 110 targets connected to the LuCa genes. Three common targets between lung cancer and iturin A were identified through target intersection. Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) and lung cancer genes AKT1, PIK3CA and EGFR may be the primary targets of iturin A acting on lung cancer, according to the PPI map and topological study. This was found using the Swiss Target Prediction databases. Additionally, we selected shared proteins between the projected targets of specific ligands and proteins in lung cancer using Venny 2.1.0 and the same has been depicted in Fig. 2 ²⁷.

3.2 Gene ontology and KEGG pathway enrichment analysis

The GO and KEGG pathway analysis for LuCa genes to demonstrate how iturin A inhibits lung cancer. Annotations of LuCa were found in the Shiny GO database. To investigate the pathways for the LuCa gene further, we ran a KEGG pathway enrichment analysis. The non-small cell lung cancer pathway, the FoxO signalling pathway, the lung cancer pathway, and the EGFR tyrosine kinase inhibitor resistance pathway were the top 4 pathways identified. The Y-axis displays the target genes' significantly enriched GO categories (FDR < 0.05), while the X-axis shows the total number of target genes. The rich factor is displayed on the X-axis, while the Y-axis indicates the target genes' essential pathways. The ratio of all the annotated genes found in a pathway to the number of target genes that belong to the pathway is known as the rich factor. A higher rich factor indicates an increased level of enrichment. The dot’s colour represents different P values, and the number of target genes expressed in the route is shown by the dot's size in Figs. 3 and 4 ²⁸.

Pathway Enrichment Analysis using GO and KEGG.

The GO and KEGG pathway enrichment analysis for lung cancer and potential treatment targets was performed to understand the mechanism of iturinA. Significantly enriched GO keywords were found in the items associated with enrichment results (Figs. 5, 6 & 7) ²⁹.

To investigate the pathways for one potential therapeutic target of lung cancer, we conducted a KEGG pathway enrichment analysis; that is, the top pathways were identified based on docking analysis (Fig. 8).

3.3 Selection and preparation of iturin A

The compound iturin-A was downloaded in sdf format from the PubChem database, and it was docked to the PIK3CA (phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform) using the high AutoDock Vina tool. The ligand used for the target covered in this analysis was chosen from a range of literature reviews and our previous study. The inhibitors' three-dimensional structures and the associated PubChem CID were redeemed and saved in sdf format (Yaraguppi et al., 2022). The ligands' 3-D structure was taken to continue with the ligand preparations. After that, this three-dimensional structure was loaded into the Pymol software, which allowed it to be converted from sdf to pdb format. Using Pymol software, metals were also removed from the structural composition of the ligand to perform a suitable docking analysis. The ligand prepared for the docking studies was stored in pdb format for further docking study ³¹.

3.4 Protein preparation

The target protein, phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) (Fig. 9), was further explored for the docking technique after its crystal structure was retrieved from the Protein Data Bank (PDB) using PDB ID 4JPS. Hydrophilic interaction, hydrogen bonding, and binding energy are the three main ways the ligand and target proteins interact ³². Iturin A was more readily absorbed by the progesterone receptor when it formed two hydrogen bond interactions with amino acid residues. The amino acids with − 5.1 Kcal/mol binding energy are ASN:853(H1), SER:854(H2), GLU:768(H3), SER:773(H4), ARG:852(H5), TRP:780, ILE:932, and GLU:798 (Table 1) ³³. According to Daher et al. (2023), lung cancer may be targeted by phosphoinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PDB ID: 4JPS) ³⁴.

3.5 Molecular docking

Finally, docking analysis was performed to examine interactions between the important target and the selected ligand. The PDB ID: 4JPS was used to retrieve the alpha isoform (PIK3CA) catalytic subunit 3D structures of phosphatidylinositol 4,5-bisphosphate 3-kinase. Next, AutoDock Vina was used to complete target docking. With an exhaustiveness of 100, the PGR docking grids in AutoDock Vina were X: -1.318700, Y: -9.512667, and Z: 16.948100 from the centre. The maximum binding affinity between iturin A and PIK3CA is approximately − 5.1 kcal/mol. These results imply that because core targets attach to active compounds over time, they can be used as a potential candidate for lung cancer treatment. Three-dimensional visualisations of the target protein and the ligand are shown in Fig. 9. The Discovery Studio Visualizer might be used to investigate contributing residuals, atomic positions, and different forms of interactions.

Table 1

Binding energy of receptor-ligand complex.
Protein PDB Id	Compound name	Binding affinity (kcal/mol)	No. Hydrogen bonds	Interacting residues
4JPS	IturinA	-4.1	05 H1: 2.43Å H2: 2.43Å H3: 2.78Å H4: 2.66Å H5: 2.46Å	ASN:853(H1),SER:854(H2),GLU:768(H3),SER:773(H4),ARG:852(H5),TRP:780,ILE:932,GLU:798

The interaction was recorded and is shown in Fig. 10 and Table 1. According to additional research, most interactions occurred with the anticipated active site residues.

3.6 Molecular dynamics analysis (RMSD, RMSF, RG, SASA, H-bond and MMPBSA)

A molecular dynamics simulation was used to study a molecule with the ligand iturin A from the docking. An MD simulation was conducted for 200 nanoseconds (ns) to better understand the stability of the protein-ligand complexes previously mentioned. The following acronyms were used in the computations: H-Bonds (hydrogen bonds), SASA (solvent accessible surface area), MMPSA, RG (radius of gyration), RMSF (root mean square fluctuations), and RMSD (root mean square deviation)³⁵.

3.6.1 Root Mean Square Deviation (RMSD)

The outcome provided a quantitative analysis of the procedure, indicating the various parameters' degree of fluctuation and departure. It is crucial to consider how the two confirmations vary from one another. The divergence increases along with the RMSD value. The simulation timescale of 100 ns is used to calculate the RMSD values. It comes with an RMS tool that can compute RMSD. The graphic below shows the RMSD calculation for the protein-ligand structure. Domain of binding for the 4JPS of phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA). For complexes containing iturin A, the average RMSDs from 0 to 200 ns were 0.13 nm and 0.31 nm, respectively (Fig. 11). The relative stability of chemical compounds during the simulation is shown by these RMSD values, which suggest that the protein and ligand complex are stable and have good interaction ³⁶.

3.6.2 Root Mean Square Fluctuation (RMSF)

The protein becomes unstable in the presence or lack of ligand, and RMSF analysis reveals which amino acids in the protein are more likely to generate vibrations. It is necessary to compute the RMSF values using a simulation length that falls between 0 and 200 ns. The results of the RMSF for iturin A Complexed with the Alpha Isoform of the Phosphatidylinositol 4,5-bisphosphate 3-kinase Catalytic Subunit (PIK3CA) (4JPS) Binding Domain are displayed in Fig. 12 (Deshpande et al., 2023).

3.6.3 Radius of Gyration (RG)

The radius of gyration (Rg) plot demonstrated the rigidity of the protein structure. If the variance rises while the simulation is running, the structure becomes unstable. The apparent compactness of a protein can be determined using the radius of gyration. The protein folding and unfolding for the Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) (4JPS) Binding Domain Complexed with iturin A was evaluated using the RG values vs the simulated timeline of 0 to 20,000 ps. Figure 13 displays the RG result of the APO and ITU combination. The radius of the gyration plot showed that the values stayed at or below 1.9 nm, demonstrating the compactness and stability of the ligand ³⁸.

3.6.4 Solvent Accessible Surface Area (SASA):

Compactness and flexibility are related in several ways. SASA was shown to be useful in understanding how inhibitors affect protein compactness, even though the changes in SASA values were extremely small in each complex. The SASA values, which span from 0 to 200, are shown in Fig. 14. It is a section of a protein's surface that is solvent-accessible and serves as a marker for the protein's stability. Throughout the simulation, SASA showed itself to be stable, with no appreciable changes in the solvent accessibility, which remained between 135 and 140 nm2 ³⁹.

3.6.5 Hydrogen bond (H-bond):

Hydrogen bonds are created, which stabilise protein-ligand complexes. The simulation analysis in our work validates the hydrogen bond formation found by the molecular docking investigation. Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) (4JPS) Binding Domain complexed with iturin A H-Bond is shown in Fig. 15 ⁴⁰.

3.6.6 Molecular Mechanics Poisson–Boltzmann Surface Area (MMPBSA)

MMPBSA computes the energy needed for the ligands to bind to the protein. The MD simulation using the MMPBSA analysis yielded an overall binding energy of -58.136+/-42.564 kJ/mol, showing that the protein retained the ligand during the simulation. It was discovered that the system's total Vander Waal energy was − 240.585+/-30.913. Figure 16 shows higher system stability as the net binding energy for the complex anticipated by MMGBSA is -81.247+/-47.990 kcal/mol, compared to the result attained by MMPBSA (22.9620 kcal/mol). The polar solvation energy appears to have a less significant effect on the receptor-inhibitor interaction, which explains the considerable difference in net energy between the two techniques. The entropy impact over the inhibitor has not been considered due to the higher computational expense ⁴¹.

3.7 Principal component analysis and Gibbs free energy calculation

The structural dynamics were investigated using GFE and PCA analysis. The Gibbs free energy values for the Apo and ligand-bound proteins are correspondingly shown in Figs. 17A and 17B, which shed light on the stability of the corresponding confirmations. The Principal Component Analysis (PCA) of the 2000-frame data set from Molecular Dynamics (MD) simulations is shown in Fig. 17. The outcomes show a significant dot clustering, indicating little variation in the structural dynamics. Remarkably, Fig. 17B shows a larger sample than Fig. 17A, which may be related to the ligand and protein confirmation. Figures 17A and 17B show the comparable Gibbs Free Energy (GFE) landscapes. A steady confirmation is shown by a strong cluster of Apo proteins (dark purple) in the energy well in Fig. 17A. Comparably, Fig. 17B shows a clear well for the protein attached to the ligand, suggesting a stable confirmation. The GFE values, which show the stability and affinity of the protein-ligand complex and range from almost 0 to 1 kJ/mol (Fig. 16B), offer essential insights into the energetic environment. This small range supports the strength of the interaction in our investigation by pointing to a well-defined and favourable binding. In conclusion, the idea of a stable binding confirmation between the ligand and protein is supported by both PCA and GFE analysis

3.9 Cytotoxic assessment of recombinant iturin A

Lung cancer is suggested to be one of the main existing cancers globally with utmost death rate in humans. MTT assay is commonly performed to evaluate the cell viability and analyze the lethal influence of metabolites and proteins on cancer cells. Recombinant iturin A was produced as per our earlier work (Yaraguppi et al., 2022). The cytotoxic effect of recombinant iturin A was assessed by MTT assay procedure in lung cancer cell line A549 in a concentration range of 0.125-128 µM. The % cell viability of recombinant iturin A treated cells was calculated. The % cell viability declined at increased concentration of recombinant iturin A as shown in Fig. 18. The results indicate the dose dependent effect of iturin A on % cell viability of lung cancer cell line A549. At a concentration of 64 µM, a cell viability % of 10.8% was evidenced. A 24% cell viability (data not shown) was evidenced with Doxorubicin (standard drug) at 100 µg/mL. IC₅₀ represents the value of cell inhibition by 50% which was found to be 7.73 µM for iturin A. Interestingly, 100% cell viability was observed in case of untreated cells validating the significant cytotoxic effect of recombinant iturin A on lung cancer cell propagation. The outcome suggests the potentiality of recombinant iturin A molecule as a promising lead for suppression of lung cancer.

Globally, lung cancer is the leading cause of cancer in women and poses a serious risk to public health. Thus, it is crucial to discover safe and effective drugs to prevent the beginning and spread of lung cancer. Synthetic musk has the same medicinal efficacy as real musk while having a different makeup ⁴³. Musk has been said to have potent anti-tumour properties, but real musk is expensive and hard to come by. In this work, we investigated the mechanism and effect of iturin A on lung cancer using network pharmacology. By performing an extensive search of databases, we were able to identify 34 prospective targets for lung cancer. Further, the PPI network for the targets and performed a topological analysis. Three intersecting targets were identified as possible iturin A targets for lung cancer. These targets included EGFR, AKT1, PIK3CA, and PIK3CA as the primary target. The PIK3CA gene codes for the catalytic subunit alpha isoform of phosphatidylinositol 3-kinase (PI3K), which is responsible for producing the p110 alpha (p110α) protein. Each p110α subunit is a portion of the PI3K enzyme. Because it carries out PI3K's function, the p110α protein is referred to as the catalytic subunit; the other subunit, which is generated by a separate gene, controls the enzyme's activity. Iturin A inhibits lung cancer cells by regulating signalling pathways (cancer pathways, prostate cancer, Faconi anaemia, and homologous recombination pathway) through molecular responses (guanine/thymine mispair, single base insertion, damaged DNA binding), as revealed by GO and KEGG analysis of potential targets of iturin action in lung cancer. However, the study only offers a few fresh suggestions for choosing medications and prescriptions. Physicians with extensive clinical experience should prescribe treatments for lung cancer; fundamental investigations and clinical trials are required to confirm. Wang et al (2020) report the clinical significance of PIK3CA gene by employing systematic review study, in which mutation in PIK3CA can have a significant effect on the lymph node metastasis and which can further serve as a prognostic factor for lung cancer, and further smoking practice may lead to the high expression of PIK3CA in NSCLC patients.

The overlap of compound targets and NSCLC were used to build the PPI network, according to Thorpe et al. (2015) and other references the PPI, PTPN11, FYN, AKT1, PIK3CA, PIK3R1, MAPK3, STAT3, MAPK1, HSP90AA1, and SRC were excellent candidates for YFSJF targeting NSCLC. Their primary functions involve MAPK and PI3K-AKT signalling. AKT1, PIK3R1, and PIK3CA are essential components of the PI3K/AKT pathway. Comprising of PIK3R1 and PIK3CA, type I PI3K is a heterodimer that is strongly linked to cancer. PIP2 can be phosphorylated into PIP3 by PI3K activation. Subsequently, PIP3 attract PDK1 and AKT1 to the plasma membrane, then PIP3 activates AKT1. The AKT1 activation also increase downstream signalling pathways that support the invasion, proliferation, and angiogenesis of metastases in cancer cells. ^45,46.

By anticipating the relationship between the lipopeptide iturin A and genes and targets associated with disease, network pharmacology reveals the mechanism of action of medicine on diseases and illustrates the regulatory effect of components on significant enrichment pathways through core chemicals and genes. Our research is primarily focused on the mechanism of action of iturin A to provide a strong scientific basis for the use of this lipopeptide in the treatment of lung cancer. Future systematic research is necessary to fully understand the specific mechanism of iturin A. The assessment of the contact force is strengthened by flexible and semi-flexible molecular docking, and the locking of important medications and disease targets is made possible by the prediction of the composition of active components and their targets at network analysis.

Preclinical and clinical settings can be used to evaluate novel targeted medications developed with the help of data generated from these procedures. Additionally, networks of interactions between proteins and ligands have been constructed to assess the physical connectivity between various proteins, providing insights into the molecular mechanisms underlying cellular function. This paper investigates the pharmacological mechanism of iturin A in combination with Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) (4JPS) in the treatment of lung cancer. Dysregulation of the PI3K pathway is a common occurrence in various cancers, including lung cancer, where PIK3CA mutations are frequently observed. These mutations contribute to oncogenic transformation and tumor progression, making PIK3CA an attractive therapeutic target. In the context of lung cancer, targeting PIK3CA holds potential for precision medicine approaches, as it allows for tailored treatments based on the specific molecular alterations present in individual tumours ⁴⁷.

Several preclinical and clinical studies are investigating the efficacy of PI3K inhibitors in lung cancer, providing a foundation for the development of targeted therapies. The exploration of PIK3CA as a cancer target underscores the importance of molecular profiling in guiding treatment decisions and advancing personalized medicine in the field of oncology ⁴⁸. It does this by using network pharmacology, docking analysis, and simulation study. Furthermore, network pharmacology is a valuable tool for understanding the effects of iturin A on the alpha isoform of the Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit (PIK3CA) (4JPS). The mechanism of the progesterone receptor's distinct ability to inhibit cancer cells has not received much attention in research, even though traditional medicine has made extensive use of the therapeutic properties of the phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA). The relationship between the advantageous chemical iturin A and the selective inhibitor Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) is examined in the in-silico study.

The results on the binding affinity and molecular dynamics of bioactive compounds were especially encouraging when contrasted with the validated inhibitor. The optimal conformation with the lowest docked energy was chosen from the docking search. When docked with the Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) (4JPS), the protein and ligand have a good binding energy at iturin A (-5.1 kcal/mol). Any ligand that shows more torsions than six is corrected to have six torsions. The quantity of torsions is fixed between 0 and 6. Hydrogen bond interactions are also estimated and discussed; the presence of H-bonds suggests a stable bond between the ligand and the protein. Protein-ligand interactions, two-dimensional images, and hydrogen bonds are all represented using the Discovery Studio 2020 Client and Chimaera software. The protein and ligand have strong binding energies, as shown by the docking of the Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) (4JPS) with iturin A (-5.1 kcal/mol). Using molecular docking, the binding affinities of ten hub molecules and three primary targets were examined. Binding affinities of less than − 5 kcal/mol are typically taken into account, signifying a strong confirmation intersection ⁴⁹.

Molecular dynamics calculations were carried out using the following techniques to investigate the stability of the previously described protein-ligand complexes: RMSD (Root Mean Square Deviation), RMSF (Root Mean Square Fluctuations), RG (Radius of Gyration), H-bonds (Hydrogen bonds), SASA, and MMPSA. The Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) protein and the iturin A complex protein had average relative standard deviations (RMSDs) of 0.28 nm and 0.18 nm, respectively, between 0 and 200 ns. A low and stable RMSD value of a protein-compound system implies that the compound fits well into the protein binding site and forms strong interactions with the protein residues. A stable RMSD value of a system is directly proportional to the binding affinity of the protein and the compound, as higher binding affinity means lower energy and higher stability ⁵⁰. The c-alpha atoms' root mean square fluctuation in the APO and ITU complex was shown against a time span of 0-200 ns. Plotting the iturin A complex RG values and the Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) protein against the simulated timeline of 0 to 20,000ps was done.

The H-Bond result of the complex containing iturin A was shown with the SASA values in the range of 0 to 200 ns. According to MMPBSA measurements, the electrostatic energy, polar solvation energy, and binding energy are − 135.500+/-87.220 kJ/mol, 349.422+/-98.522 kJ/mol, and − 16-58.136+/-42.564 kJ/mol, respectively. This will lead to the development of a specific chemical and its increased use in animal trials. Ultimately, the theory that YFSJF inhibits PIK3R1, PIK3CA, and AKT1 to reduce the PI3K/AKT pathway and combat NSCLC was confirmed by molecular docking and dynamics simulations. Subsequent studies revealed the anticancer activity of hub chemicals, particularly about lung cancer ^51–53. Study by Zhao et al, 2018 clearly shows the apoptosis and paraptosis activity of lipopeptides produced by Bacillus subtilis, in which mixture of iturin homologues having concentration of 42.75% showed the inhibition of K562 myelogenous leukemia cells ⁵⁴. There by showing the inhibitory potential of iturin A in the cancer cells by targeting the important targets involved in the critical pathways that play major role in cancer progenesis and proliferation.

Iturins are a class of lipopeptides majority synthesized by Bacillus sps. and recommended in several reports to possess antitumor properties. Iturin has been evaluated for anticancer effect on various cell lines like MCF-7, K562 leukamia, A549, HepG2 and Caco-2 and has shown inhibitory effect on HepG2 and Caco-2 at 100 µM ⁵⁴. In a study by Dan et al. (2021), the authors analysed the iturin induced inhibitory pathways that comprises of instigation of apoptosis and mitochondrial inflammation, reticence of autophagy succession and stimulated intrinsic pathway. The lipopeptides derived from of B. subtilis revealed anticancer effect on cancer cell lines through regulation of cellular behaviours. The compounds from B. subtilis NC16 triggered apoptosis of cell lines such as, H1299 and A549 via restraining propagation rate and relocation motility, influenced the regulatory aspects of cell cycle and stimulated cell apoptosis through Caspase-3/7 signaling mitochondrial apoptosis pathway⁵⁶. Several molecules and proteins have been previously reported for cytotoxic effect on cancer cells. Various authors evaluated the cytotoxic effect of different molecules such as recombinant proteins and peptides, plant metabolites and nanoparticles. Recombinant subtilisin from B. subtilis showed an IC₅₀ value of 5 µM for A549 cell lines indicating its probable interface with protein’s cationic sites and anionic locations on cancerous cell’s cytoplasmic membrane ¹¹.

Plant metabolites such as, different kinds of Withanolides derived from Withania somnifera roots presented anticancer attributes largely by targeting KAT6A involved in significant cellular pathways ⁵⁷. The cytotoxic influence of nanoparticles synthesized from keratin hydrolysates are reported in breast cancer cell lines ⁵⁸. Rofeal and El-Malek (2021) reviewed several biosurfactant (lipopeptides) acting as anticancer agents emphasizing hepatocellular cancer. The lipopeptides (surfactin) obtained from B. subtilis HSO121 showed inhibition of human Bel-7402 hepatoma cells with reported IC₅₀ of 35 µM. Iturin A (lipopeptide) from marine bacteria showed inhibition of MDA-MB-231 and MCF-7 by suppressing tumor escalation and reducing the expressions of Ki-67, CD-31, P-Akt, P-GSK3β, P-FoxO3a and P-MAPK ⁶⁰. Lipopeptide (surfactin) has shown inhibitory effect on several cancer cells by suppressing the cancer succession, arresting cell cycle and metastasis ⁶¹. The present investigation provides emphasis on the eventual relevance of iturin A as anticancer protein triggering the possibility for its biomedical efficacy in cancer treatment.

This study looked at the active lipopeptide iturin A for lung cancer using network pharmacology. The lung cancer network analysis explained the process by a range of components, targets, and pathways by utilising protein analysis of the string database to identify three key targets and four relevant pathways. Our findings suggest that iturin A's main active components may reduce the risk of lung cancer by inhibiting the central nervous system and mental disorders’ risk factors and suppressing and using the binding energies derived from docking studies. Based on the molecular docking data, the selected proteins and lipopeptide showed better binding capabilities. However, to validate these findings, other studies must be performed in the future. Recent research made effective use of network analysis, structure-based drug design, and simulation analysis. The current work's outcomes are predicated on precise and trustworthy software that validates its usage. The first advantage of network analysis is that in-silico research saves a great deal of money and effort compared to in vitro and in vivo investigations. Since the design of novel chemicals has yielded impressive results, it can be applied to more Molecular Dynamics simulations to produce a real-time behaviour system. An in-silico approach to Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) as a potential pathway for lung cancer has been proposed. The current work leads to the discovery of possible targets and medications to meet the demands of patients with lung cancer and offers a theoretical foundation for understanding the underlying molecular simulation mechanisms. The computational simulation that served as the basis for the current study's conclusions can be further verified by in vitro and in vivo investigations.

Author Contributions

DAY has been involved in the concept design. DAY has executed all the research work and carried out all the network constructions and analysis. DAY, ZKB, DP, RKM, and NM have carried out all the data analysis and interpretations. DAY and ZKB have written the manuscript. DAY, DP, and NM have critically reviewed the manuscript. DAY has supervised the entire work. The authors have read and approved the contents of the manuscript.

Conflict of interests

All the authors affirm that they do not have any conflict of interests.

Data availability

The datasets used/or analysed during the current study available from the corresponding author on reasonable request.

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No competing interests reported.

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Elucidation of Therapeutic Mechanism of Lipopeptide Iturin A from Bacillus aryabhattai on Lung Cancer Through Integration of Network Pharmacology, Molecular Docking, Molecular Dynamics Simulation and In Vitro Analysis

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Abstract

Figures

1. Introduction

2. Materials and Methods

2.1 Chemicals and cell lines

2.2 Identification of active components of iturin A

2.3 Effective targets for lung cancer

2.4 Construction of protein-protein interaction network (PPI) and critical targets

2.5 GO and KEGG pathway enrichment analysis

2.6 Molecular docking of compound and target

2.7 Molecular dynamics simulation

2.8 Principal component analysis and Gibbs free energy calculation

2.9 Evaluation of cytotoxicity

3. Results and discussion

3.1 Identification of targets for lung cancer

3.2 Gene ontology and KEGG pathway enrichment analysis

3.3 Selection and preparation of iturin A

3.4 Protein preparation

3.5 Molecular docking

3.6 Molecular dynamics analysis (RMSD, RMSF, RG, SASA, H-bond and MMPBSA)

3.6.1 Root Mean Square Deviation (RMSD)

3.6.2 Root Mean Square Fluctuation (RMSF)

3.6.3 Radius of Gyration (RG)

3.6.4 Solvent Accessible Surface Area (SASA):

3.6.5 Hydrogen bond (H-bond):

3.6.6 Molecular Mechanics Poisson–Boltzmann Surface Area (MMPBSA)

3.7 Principal component analysis and Gibbs free energy calculation

3.9 Cytotoxic assessment of recombinant iturin A

4. Discussion

5. Conclusions

Declarations

References

Additional Declarations

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