Saudi Pharmaceutical Journal 31 (2023) 101802

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Saudi Pharmaceutical Journal

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Original article

Network pharmacology based virtual screening of Flavonoids from

Dodonea angustifolia and the molecular mechanism against
inflammation
Mubarak A. Alamri a,⇑, Muhammad Tahir ul Qamar b
a
Department of Pharmaceutical Chemistry, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia
b
Integrative Omics and Molecular Modeling Laboratory, Department of Bioinformatics and Biotechnology, Government College University, Faisalabad 38000, Pakistan

a r t i c l e i n f o a b s t r a c t

Article history: Inflammation is a nonspecific immune response against injury caused by a harmful agent that strives to
Received 17 May 2023 restore tissue function and homeostasis. Dodonaea angustifolia L.f. (Sapindaceae) is a medium-sized shrub
Accepted 25 September 2023 used to treat a variety of diseases in traditional medicine. In the current study, integrated network-
Available online 28 September 2023
pharmacology and molecular docking approaches were used to identify the active constituents, their pos-
sible targets, signaling pathways, and anti-inflammatory effects of flavonoids from D.angustifolia. D.
Keywords: angustifolia active ingredients were acquired from the Indian Medicinal Plants, Phytochemistry and
Dodonea angustifolia
Therapeutics (IMPPAT), and Traditional Chinese Medicine System Pharmacology (TCMSP) databases.
Anti-inflammatory
Network pharmacology
The screening included the ten most prevalent D. angustifolia components, and the
Flavonoids SwissTargetPrediction database was utilized to anticipate the targets of these compounds. Anti-
KEGG inflammatory genes were found using the GeneCards database. The 175 overlapping genes were discov-
Molecular docking ered as prospective D. angustifolia anti-inflammatory targets. Gene Ontology and Kyoto Encyclopedia of
Genes and Genomes (KEGG) enrichment analysis revealed that the overlapped targets were closely
related to the major pathogenic processes linked to inflammation, such as response to organonitrogen
compound, protein kinase activity, phosphotransferase activity, pI3k-Akt signaling pathway, metabolic
pathways, and chemical carcinogenesis. Compound–target–pathway, and protein–protein interaction
networks revealed 6-Methoxykaempferol and 5-Hydroxy-7,8 dimethoxyflavone as key compounds,
and AKT1, VEGFA, and EGFR as key targets. Furthermore, molecular docking followed by molecular
dynamic (MD) simulation of D. angustifolia active ingredients with core proteins fully complemented
the binding affinity of these compounds and indicated stable complexes at the docked site. These findings
reveal D. angustifolia ’s multi-target, multi-compound, and multi-pathway strategies against inflamma-
tion. Our study paved the way for further research into the mechanism for developing D. angustifolia -
based natural products as alternative therapies for inflammation.
Ó 2023 The Author(s). Published by Elsevier B.V. on behalf of King Saud University. This is an open access
article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

1. Introduction

Inflammation is a complicated pathological and physiological

process (Pant et al., 2014). It controls a variety of pathological
and physiological processes in the body by influencing a number
⇑ Corresponding author at: Department of Pharmaceutical Chemistry, College of of cells and microenvironmental elements (Korniluk et al., 2017).
Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj 16278, Saudi Arabia. Inflammation activates immune cells and tissue stromal cells,
E-mail addresses: m.alamri@psau.edu.sa (M.A. Alamri), tahirulqamar@gcuf.edu. allowing proteins and cells from the vascular system to enter
pk (M. Tahir ul Qamar).
infected or injured tissues and promote repairing (Mraz and
Peer review under responsibility of King Saud University.
Haluzik 2014, Owens 2015). Inflammation often develops in stages,
beginning with a quick induction phase that triggers a pro-
inflammatory response, then gradually progressing to a resolution
phase. Although self-limiting inflammation is physiological and
Production and hosting by Elsevier

https://doi.org/10.1016/j.jsps.2023.101802
1319-0164/Ó 2023 The Author(s). Published by Elsevier B.V. on behalf of King Saud University.
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
M.A. Alamri and M. Tahir ul Qamar Saudi Pharmaceutical Journal 31 (2023) 101802

essential for killing germs, it is harmful to the systemic responses Explorations into the anti-inflammatory properties and mecha-
of the affected organs and adjacent organs if it persists (Raucci nisms of action of D. angustifolia are in their nascent stages. There-
et al., 2019). Several studies revealed that inflammation controls fore, uncovering its pivotal bioactive components and potential
the onset and progression of a wide range of complex disorders. targets will considerably augment our understanding of D. angusti-
Acute inflammation and chronic inflammation are two different folia’s anti-inflammatory activity. In our present study, we have
types of inflammation. The acute inflammation subsides quickly implemented an integrative approach involving network-
and typically benefits the host. Chronic inflammation occurs when pharmacology-based screening, molecular docking, and compre-
inflammation persists for an extended period of time and can lead hensive molecular dynamic simulation to analyze the anti-
to a number of chronic diseases such as diabetes, obesity, arthritis, inflammatory effects of flavonoids extracted from D. angustifolia.
cardiovascular, pancreatitis, metabolic, neurological, and some This methodology offers a thorough and nuanced understanding
types of cancer. of the plant’s therapeutic potential against inflammatory
Investigators have focused on the mechanisms of the inflamma- conditions.
tion process in inflammatory bowel disease (IBD), psoriasis, arthri-
tis, depression, and atherosclerotic disease, with higher levels of 2. Materials and methods
inflammatory mediators observed at the sites of the lesion. The
inflammation aggravates the progression of the disease, which 2.1. Virtual screening of active phytomolecules
exacerbates the inflammation, producing a vicious cycle that
makes therapy challenging. Hence, we must emphasize that The active phytomolecules of D. angustifolia were retrieved from
inflammation plays a key role in the onset and progression of dis- the Traditional Chinese Medicine System Pharmacology Database
ease, and substances with anti-inflammatory properties are the (TCMSP) database (Ru et al., 2014) and the Indian Medicinal Plants,
direction to search for therapeutic drugs (Peng et al., 2021). Many Phytochemistry and Therapeutics (IMPPAT) (Mohanraj et al.,
related drugs including steroidal anti-inflammatory drugs (SAIDs) 2018). From the PubChem database, the structures of prevalent
and non-steroidal anti-inflammatory drugs (NSADIDs) have been phytochemicals were downloaded in the SMILE and 3D SDF for-
identified in the marker (Osborn and Hunt 2007, Islam et al., mats (Kim et al., 2019).
2018). However, the drugs have certain drawbacks because long-
term usage causes unfavorable reactions in numerous organs
2.2. Screening of Anti-Inflammatory targets
(Narsinghani and Sharma 2014).
Flavonoids, a diverse group of phytochemicals, have been
The anti-inflammatory gene targets were identified by scanning
extensively studied for their health benefits, including their anti-
the GeneCards database (The Human Gene Database) for the key-
inflammatory properties. Numerous studies have suggested that
words ‘‘Inflammatory” (Safran et al., 2010). An Excel spreadsheet
flavonoids possess potent anti-inflammatory activities, such as
was used for saving all related genes for further study.
the suppression of proinflammatory cytokines and the inhibition
of key enzymes involved in the inflammatory process, like
2.3. Screening of D. Angustifolia potential target genes
cyclooxygenase, lipoxygenase, and inducible nitric oxide synthase
(Kim et al., 2004, Amic et al., 2007). Recent research has shown that
Potential targets of active constituents from D. angustifolia were
regulatory enzymes and transcription factors which are important
obtained using the SwissTargetPrediction database (Daina,
in regulating inflammatory mediators can be inhibited by flavo-
Michielin and Zoete 2019). For further research, only prospective
noid derivatives. In fact, in vitro and animal models suggested that
targets with a probability score higher than 0 were chosen.
flavonoids have the potential to inhibit the onset as well as the
development of inflammatory diseases (Maleki, Crespo and
Cabanillas 2019). 2.4. Identification of overlapping genes
Dodonaea, also known as hop-bush or sand olive, is a genus
with approximately 70 species including D. angustifolia (Shepherd Target intersections between anti-inflammatory targets and
et al., 2007). D. angustifolia L. f. (Sapindaceae), also called as Ketketa putative active phytomolecules targets of D. angustifolia were
in Ethiopia, is a 3 m tall shrub. It also occurs naturally in various found employing the Venny 2.1.0 online database (Oliveros
forms from southern Africa to Arabia, as well as in New Zealand 2007). These overlapping targets were recognized as potential
and Australia. D. angustifolia plant decoctions are frequently used anti-inflammatory targets.
as a cure for many ailments, injuries, infections, dental pain, and
jungle fever (de Oliveira et al., 2012). The plant is said to have anti- 2.5. Protein-Protein interaction analysis
fungal (Pirzada et al., 2010), antibacterial (Teffo, Aderogba and
Eloff 2010), anti-inflammatory (Getie et al., 2003), antidiabetic The above-mentioned potential anti-inflammatory targets were
(Veerapur et al., 2010), and antidiarrheal properties assessed using the STRING database for protein–protein interac-
(Rajamanickam et al., 2010). Particularly for D. angustifolia, flavo- tion (PPI) analysis with a confidence score greater than 0.4 and a
noids have been reported as the primary active components. Their species limitation of ‘‘Human sapiens” (Szklarczyk et al., 2023).
potential benefits in inflammation and other health conditions In order to identify possible anti-inflammatory core targets, the
have been emphasized in the literature (Tadeg et al., 2005). findings of the string PPI analysis were then loaded into the Cytos-
Recognizing the potential of phytoconstituents, Hopkins (Hop- cape software (Kohl, Wiese and Warscheid 2011).
kins, 2007) formulated an integrative computational approach
‘‘network pharmacology”. Network pharmacology transitioned 2.6. Network construction
the paradigm that single gene disordered required single target
drugs while complicated diseases where gene network is involved The network construction process, which serves as the back-
required more holistic multiple-targeted therapies (Noor et al., bone of our investigation, was executed using the Cytoscape pro-
2023, Noor et al., 2022). Thus, network pharmacology has now gram (Kohl, Wiese and Warscheid 2011). Cytoscape is a powerful
been emerged as an asset in the process of drug development, con- open-source bioinformatics software platform for visualizing
tributing significantly to the reinvigoration of traditional knowl- molecular interaction networks and biological pathways and inte-
edge (Noor et al., 2022). grating these networks with annotations, gene expression profiles,
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M.A. Alamri and M. Tahir ul Qamar Saudi Pharmaceutical Journal 31 (2023) 101802

and other state data. In this study, Cytoscape was utilized to finding its lowest energy conformation. Following this, the mole-
develop an integrated network of active phytomolecules from D. cules were converted into pdbqt format, which is compatible with
angustifolia and their anti-inflammatory targets. Specifically, the the Autodock Vina software. Finally, we visualized and analyized
active phytomolecules of D. angustifolia, identified through our ear- the docking results using BIOVIA Discovery Studio Visualizer
lier screening process, were imported into Cytoscape along with 2021 and Pymol programs.
the associated key and core anti-inflammatory targets. These tar-
gets were identified based on their roles in the inflammation pro-
2.9. Molecular dynamic (MD) simulation
cess, as per our Gene Ontology and KEGG enrichment analyses.
By using Cytoscape, these various components were connected
MD simulation is a computer technique that uses explicit mod-
based on their interactions and relationships. Nodes in this net-
eling of each bond and atom in a system, enabling a highly thorough
work represent either the active phytomolecules or the anti-
analysis of molecular dynamics. This method entails solving the
inflammatory targets, and the edges represent the potential inter-
equations of motion for each atom in the system based on the inter-
actions between them. This complex network, thus visualized,
atomic potentials that define their interactions. MD simulations of
offers a comprehensive view of how the multiple active com-
docked complexes were performed using GROMACS 2018 software
pounds in D. angustifolia might interact with different anti-
and the OPLS-AA/L force field. The protein’s 3D structure served as
inflammatory targets, thereby hinting at the plant’s multi-target,
the starting point for the simulations, and the DockPrep program
multi-compound, and multi-pathway strategies against inflamma-
was used for additional optimization (Van Der Spoel et al., 2005).
tion. Such a network not only aids in comprehending the molecular
Docked complexes of ligand molecules with the target protein with
mechanisms underlying the anti-inflammatory properties of D.
the highest binding affinity were used as the starting point for the
angustifolia but also serves as a robust tool for further investigation
MD simulation. The SwissParam website was used to parameterize
and potential drug discovery.
the ligand molecule (Zoete et al., 2011). Following earlier research,
20 ns of MD simulations were run later (Fatima et al., 2022). Gen-
2.7. Enrichment and pathway analysis
eral MD simulation parameters for each complex such as radius of
gyration (RoG), root mean square deviation (RMSD), and root mean
The ShinyGO database was used to perform the enrichment
square fluctuation (RMSF) were examined.
analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG)
pathway and GO functional on potentially anti-inflammatory key
targets (Ge, Jung and Yao 2020). Three groups of GO terms were 3. Results
formed: biological process (BP), molecular function(MF), and cellu-
lar component (CC). The top 20 KEGG pathways and GO analysis 3.1. D. angustifolia compounds target and Anti-Inflammatory disease
data (BP, CC, and MF) were exhibited in the form of an enrichment target screening
dot bubble by uploading the data to the Bioinformatics platform
(Zhao et al., 2022). Statistical significance was evaluated using This study involved a comprehensive analysis of various phyto-
the conventional hypergeometric test. The Benjamini-Hochberg molecules, each characterized by unique structural attributes and
method was used to control the false discovery rate (FDR) for mul- belonging to various subclasses of flavonoids. These natural com-
tiple hypothesis testing, and the corrected p-value of 0.05 was then pounds, sourced from different plant species, were scrutinized
used as the significant threshold (Khan and Lee 2022). for their potential pharmacological and health-related properties.
The investigation encompassed ten specific phytomolecules:
2.8. Molecular docking Pinocembrin, a flavanone with a molecular weight of 256.25; 5-
Hydroxy-7,8-dimethoxyflavone, a dimethoxyflavone with a molec-
The two active chemicals; 6-Methoxykaempferol and 5- ular weight of 298.29; Luteolin, a tetrahydroxyflavone with a
Hydroxy-7,8 dimethoxyflavone from D. angustifolia were sourced molecular weight of 286.24; Isokaempferide, a flavonol with a
from the NCBI Pubchem database. This database provides three- molecular weight of 300.26; Santin, an O-methylated flavonol with
dimensional (3D) structures of these molecules in a Spatial Data File a molecular weight of 344.3; Kumatakenin, an O-methylated flavo-
(SDF) format, offering detailed molecular structure information cru- nol with a molecular weight of 314.29; Rhamnazin, an O-
cial for the subsequent docking process. The crystal structures of the methylated flavonol with a molecular weight of 330.29; Rhamnoc-
top three potential anti-inflammatory core targets, which are pro- itrin, a monomethoxyflavone with a molecular weight of 300.26;
teins believed to have significant roles in anti-inflammatory activity Retusin, an O-methylated flavonol with a molecular weight of
(AKT1 PDB ID: 3o96, EGFR PDB ID: 7jxq, VEGFA PDB ID: 2vpf), were 358.3; and 6-Methoxykaempferol, a flavonoid with a specific struc-
downloaded from the Protein Data Bank (PDB) in PDB format ture, 3,40 ,5,7-Tetrahydroxy-6-methoxyflavone, and a molecular
(Berman et al., 2000). These protein structures act as docking sites weight of 316.26 (Table 1). These phytomolecules have been
for the active phytomolecules. Upon acquiring these protein struc- extensively studied due to their potential health benefits and
tures, we removed any water molecules and ligands - compounds diverse applications. These findings provide valuable insights into
that may bind to the protein - embedded within the protein crystal their chemical diversity and properties, offering a solid foundation
structure complexes. This step is necessary to prevent any interfer- for future research aimed at harnessing their therapeutic potential.
ence with the docking process and was achieved using the BIOVIA Each of the ten distinct compounds investigated generated a set
Discovery Studio Visualizer 2021 (Studio 2008) tool. The docking of 100 target predictions, resulting in a total of 1000 potential tar-
process was then initiated, wherein each phytomolecule was virtu- gets. To prioritize biologically significant targets for further scru-
ally ’fitted’ into its respective protein target. This was conducted tiny, we employed a stringent probability threshold of greater
individually for each compound to ensure accurate and than 0.4 (Basavarajappa et al., 2023). This threshold ensured that
interference-free results. We used Autodock Vina, a well-regarded only targets with a greater probability of interaction with the com-
software integrated within the PyRx virtual screening tool for this pounds of interest were selected for subsequent analysis, enhanc-
purpose (Dallakyan and Olson 2015). ing the biological relevance of our findings. Hence, 193
However, before we started the docking, the phytomolecules pharmacological targets were identified. Additionally, a total of
were energy minimized. This process, performed using the OpenB- 11,448 anti-inflammatory targets were retrieved from the Gene-
able tool in PyRx, optimizes the molecular structure for docking by Cards database. Venn diagram was constructed to identify com-
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Table 1
List of D. angustifolia’s active phytomolecules.

PubChem CIDs Phytomolecule name Phytomolecule class Phytomolecules structure Molecular weight
68,071 Pinocembrin Flavonoids (flavanone) 256.25

188,316 5-Hydroxy-7,8-dimethoxyflavone Flavonoids (dimethoxyflavone) 298.29

5,280,445 Luteolin Flavonoids (tetrahydroxyflavone) 286.24

5,280,862 Isokaempferide Flavonoids (flavonol) 300.26

5,281,695 Santin Flavonoidas(trimethoxyflavone) 344.3

5,318,869 Kumatakenin Flavonoids (O-methylated flavonol) 314.29

5,320,945 Rhamnazin Flavonoids (O-methylated flavonol) 330.29

5,320,946 Rhamnocitrin Flavonoids (monomethoxyflavone) 300.26

5,352,005 Retusin Flavonoids (O-methylated flavonol) 358.3

5,377,945 6-Methoxykaempferol Flavonoids (3,40 ,5,7-Tetrahydroxy-6-methoxyflavone) 316.26

mon genes between pharmacological targets and compounds asso- 20 GO analysis data (BP, CC, and MF) are displayed. According to
ciated with diseases. The Venn diagram showed that a total of 175 the findings of the GO enrichment analysis, D. angustifolia anti-
compounds were found to be common, which later be considered inflammatory targets are engaged in a number of biological pro-
as potential anti-inflammatory targets for D. angustifolia. The 175 cesses, including response to oxygen containing compound,
overlapping genes were recognized as prospective D. angustifolia response to organonitrogen compound, and regulation of pro-
anti-inflammatory targets when both D. angustifolia and anti- grammed cell death, etc (Fig. 2A). Similarly, anti-inflammatory tar-
inflammatory targets were imported into a Venn diagram (Fig. 1). gets of D. angustifolia are mostly receptor complex, plasma
membrane region, membrane raft, perinuclear region of cytoplasm,
3.2. Enrichment analysis and axon in the cellular component category (Fig. 2B). The same is
applicable for enhanced molecular function ontologies, which pre-
Pathway enrichment and GO analysis of overlapping proteins dominate protein kinase activity, phosphotransferase activity, ATP
were carried out to ascertain their biological properties using Shi- binding, etc (Fig. 2C). The anti-inflammatory targets of D. angusti-
nyGO resources. In Fig. 2, the top 20 KEGG pathways and the top folia appear to be predominantly implicated in pathways in cancer,

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To acquire the PPI network, the PPI analysis findings were

exported as a simple textual data format (.tsv) file and uploaded
into Cytoscape software 3.9.0. The network is depicted in Fig. 4A
for the top 20 effect targets, based on the calculation of degree of
centrality, as a series of colored circles with each node’s color rep-
resenting its degree, ranging from yellow (lowest) to red (highest).
The five nodes that satisfied the degree of centrality (DC) crite-
rion with an average value of around  70.00 were retrieved and
are considered of as anti-inflammatory core targets Fig. 4B.
Fig. 4C shows a bar graph of the top ten anti-inflammatory core
targets as determined by DC. The five anti-inflammatory core tar-
gets include AKT1, VEGFA, EGFR, ESR1, and SRC. Details of these
targets were mentioned in Fig. 4D.

3.4. Molecular docking

The top three anti-inflammatory core targets (AKT1, VEGFA, and

Fig. 1. Intersecting targets between anti-inflammatory -related targets and
EGFR) were molecularly docked with the two active compounds
potential targets of D. angustifolia active phytomolecules.
(5-Hydroxy-7,8 dimethoxyflavone and 6-Methoxykaempferol) of
D. angustifolia. Molecular docking was performed to determine
pI3k-Akt signaling pathway, metabolic pathways, chemical car- the binding ability of D. angustifolia bioactive components and
cinogenesis, endocrine resistance, etc., according to the KEGG path- the anti-inflammatory genes. These active chemicals exhibit strong
way enrichment data. (Fig. 2D). binding ability towards these genes. The binding energy scores for
5-Hydroxy-7,8 dimethoxyflavone and 6-Methoxykaempferol
against AKT1 were 9.2 and 8.9 kcal/mol, respectively (Fig. 5A).
3.3. Protein-Protein interaction analysis and network construction In term of interaction, 5-Hydroxy-7,8 dimethoxyflavone formed
stable hydrogen bonds with Asn54 and Thr82 within the active site
The 175 anti-inflammatory targets of D. angustifolia were of AKT1 (Fig. 5B). Similarly, 6-Methoxykaempferol interact with
imported into STRING Database 11.5 to create the PPI network. Gln79, Thr82 and Asp292 via hydrogen bonds at the active site
In terms of the PPI enrichment, the local clustering coefficient, chamber (Fig. 5C).
average node degree, and p-value were 0.528, 4.48, and 1.0e-16, On the other hand, The binding energy scores for 5-Hydroxy-7,8
respectively (Fig. 3A). A network exhibiting the 10 active chemicals dimethoxyflavone and 6-Methoxykaempferol against VEGFA were
operating on the 175 anti-inflammatory targets of D. angustifolia 6.0 and 6.6 kcal/mol, respectively. The interaction mechanism
was created using Cytoscape Software 3.9.0 Each edge indicates of compounds with VEGFA is represented in Fig. 5D. Both ligands
the link between an active substance and D. angustifolia anti- adapted similar binding modes in the binding site cavity. 5-
inflammatory target (Fig. 3B). Hydroxy-7,8 dimethoxyflavone formed hydrogen bonds with
Only two active chemicals 6-Methoxykaempferol and 5- Cys61 and Asn62 while 6-Methoxykaempferol interact with
Hydroxy-7,8 dimethoxyflavone were found to interact with D. Asp64 and Arg224 at the active site chamber (Fig. 5E & F).Further-
angustifolia anti-inflammatory targets. So these two active chemi- more, the results of docking the ligands with EGFR showed that the
cals were considered for further research. The binding interaction binding energy scores for 5-Hydroxy-7,8 dimethoxyflavone and 6-
network of these two active chemicals with potential anti- Methoxykaempferol against EGFR were 8.0 and 8.9 kcal/mol,
inflammatory -related targets is represented in Fig. 3C. respectively. interact with identical catalytic residues at

Fig. 2. GO enrichment analysis of 175 Anti-Inflammatory core targets (A) Biological process, (B) Cellular components, (C) Molecular function, and (D) KEGG pathway Analysis.

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Fig. 3. (A) The PPI network of 175 potential anti-inflammatory key targets constructed by employing STRING database. (B) The binding interaction network of D. angustifolia
active phytochemicals with potential anti-inflammatory -related targets. (C) The binding interaction network of 6-Methoxykaempferol and 5-Hydroxy-7,8 dimethoxyflavone
and with potential anti-inflammatory -related targets.

substrate-binding pockets (Fig. 5G). In details, the 6-Hydroxy-7,8 ence frame. RMSD is calculated by taking the square root of the
dimethoxyflavone was involved in a single hydrogen bond with average of the squared differences between the corresponding
Lys745 and many stabilized via several homophobic forces with atoms in the two structures. In the case of a protein–ligand com-
hydrophobic residues such as Leu777 and Leu858 (Fig. 5H). Simi- plex, the RMSD is calculated only for the ligand atoms, while the
larly, 6-Methoxykaempferol interacted mainly with hydrophobic protein atoms are held fixed. A low RMSD value indicates that
residues at the active site chamber (Fig. 5I). the two structures are similar, while a high RMSD value indicates
The details of amino acids involved in stabilizing the two com- that they are different. Typically, a cutoff value of 2 Å is used to
pounds at protein active sites are given in Table 2. Overall, the define a ‘‘good” ligand pose, although the acceptable RMSD value
molecular docking outcomes agreed with the network can vary depending on the application and the accuracy of the
pharmacology-based screening results, indicating that network computational method used. In Fig. 6A protein in complex with
pharmacology tools were effective in this study. both ligands was stable and no deviation was observed during
20 ns and 1000 frames. In Fig. 6B the RMSD of the ligands was
3.5. MD simulation observed and it was concluded that both ligands during 20 ns sim-
ulations were stable at their best binding poses, no deviation was
GROMACS was used to execute all-atom MD simulations for observed.
20 ns to evaluate the interaction of AKT1, VEGFA, and EGFR protein, Similarly, RMSD in Fig. 7A was observed and it was revealed
and the stability of the ligand molecules. MD simulation of each that protein was stable during 20 ns simulation after binding with
complex was performed to get the RMSD, RMSF, and RoG values, both ligands throughout 1000 frames. An average deviation 0.01 ±
which ultimately helped determine the docked complex’s stability. 0.001 nm was observed and a minor deviation of 0.01 was seen at
Protein-ligand RMSD (Root Mean Square Deviation) is a metric 18 ns. In Fig. 7B both ligands with the respective protein were
commonly used to assess the similarity between two structures of strongly stable till 8 ns but after 8 ns 0.01 nm deviation was
a protein–ligand complex. It measures the deviation between the observed which was in the range of protein–ligand strong binding
positions of the atoms in the protein–ligand complex structures affinity. In Fig. 8A, the protein with respective both ligands was
after the structures have been aligned based on a common refer- stable and the mean deviation was calculated which was

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Fig. 4. (A) Top 20 potential anti-inflammatory key targets, and (B) The top five potential anti-inflammatory core-targets constructed using the Cytoscape software based on
degree centrality (DC). The color of each node changes from gradually from red (highest) to yellow (lowest) as its degree decreases. (D) The five anti-inflammatory core-
targets ranked by DC > average value of (62.8). (E) Table shown the details of five anti-inflammatory core-targets ranked by DC.

0.001 nm and this was an acceptable range. In Fig. 8B, RMSD Rg values are in the range of acceptance. All the ligands showed
showed that 5-Hydroxy-7-8-dimethoxyflavone was stable during an acceptable range of radius of gyration.
the whole simulation time but 6-Methoxykaempferol was not
stable till 9 ns of simulation but after 9 ns simulation this ligand
was also stable. Herein, results showed that protein–ligand com- 4. Discussion
plexes were strongly stable during 20 ns in a range of 2 Å.
Protein root mean square fluctuation (RMSF) is a measure of the For centuries, medicinal plants have been used to cure a variety
flexibility or mobility of a protein’s structure. It calculates the aver- of diseases, including inflammation. Many plants contain anti-
age deviation of each atom in a protein from its mean position over inflammatory bioactive chemicals, making them ideal candidates
a given period of time of simulation. The RMSF can provide insights for the creation of new anti-inflammatory drugs (Aslam et al.,
into protein dynamics and functional changes, such as protein–li- 2021, Noor et al., 2022, Rehman et al., 2022). D.angustifolia is a
gand binding or conformational changes. Typically, the RMSF val- plant species native to Australia and other areas of the world.
ues are plotted as a function of the protein’s residue number to The plant is well-known for its traditional medical applications
visualize regions of high flexibility or mobility in the protein struc- in treating a number of diseases, including inflammation (Getie
ture. High RMSF values usually correspond to more flexible et al., 2003). D.angustifolia extracts and compounds may have
regions, such as loop regions or exposed surface areas, while low anti-inflammatory potential but more research is required to fully
RMSF values correspond to more rigid or stable regions, such as understand their modes of action and possible therapeutic
alpha-helices or beta-sheets. In Fig. 6D, Fig. 7D and Fig. 8D the applications.
RMSF of protein respective to all ligands revealed that there were This study can be utilized as a basis for early screening of flavo-
no higher conformational changes in protein structure during noids obtained from D. angustifolia, and it provides a novel thera-
20 ns and the RMSF values were in the acceptable range of 2 Å. peutic idea for further research into the plant’s ability to treat
In the case of a protein–ligand complex, the radius of gyration is inflammation. Many flavonoids have anti-inflammatory effects,
used to characterize the overall size and shape of the complex. according to research. Flavonoids are thought to act as anti-
However, it is important to note that the ligand is typically much inflammatory agents by suppressing the generation of pro-
smaller than the protein, and therefore its contribution to the over- inflammatory enzymes and cytokines, scavenging free radicals,
all radius of gyration is relatively small. In general, the radius of and altering inflammatory signaling pathways. This analysis dis-
gyration of a protein–ligand complex depends on the size and covered 10 active components and 1000 targets in total. A total
shape of both the protein and the ligand, as well as the specific of 11,448 genes associated with inflammation were also collected
interactions between them. Therefore, it can be a useful parameter from the Gencards database. Among these were 175 intersecting
for characterizing the stability and binding affinity of the complex, targets, which were related to the inflammation.
as well as for guiding drug design efforts. In Fig. 6C, Fig. 7C, and GO functional analysis showed that the anti-inflammatory tar-
Fig. 8C, all the complexes showed strong stability because their gets of D. angustifolia are chiefly engaged in response to oxygen-
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M.A. Alamri and M. Tahir ul Qamar Saudi Pharmaceutical Journal 31 (2023) 101802

Fig. 5. (A) Docking and interaction mechanism of Ligands with AKT1. Amino acid interactions with (B) 5-Hydroxy-7–8-dimethoxyflavone and (C) 6-Methoxykaempferol
within the active site of AKT1. (D) Docking and interaction mechanism of Ligands with VEGFA. Amino acid interactions with (E) 5-Hydroxy-7–8-dimethoxyflavone and (F) 6-
Methoxykaempferol within the active site of VEGFA. (G) Docking and interaction mechanism of Ligands with EGFR. (H) 5-Hydroxy-7–8-dimethoxyflavone and (I) 6-
Methoxykaempferol against EGFR.

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Table 2
Docking and amino acid interactions of 5-Hydroxy-7–8-dimethoxyflavone and 6-Methoxykaempferol against AKT1, VEGFA and EGFR.

Protein Phytochemical
5-Hydroxy-7–8-dimethoxyflavone 6-Methoxykaempferol
H- bonds Hydrophobic H- bonds Hydrophobic
AKT1 Asn54, Thr82 Trp80 Asn54, Gln79, Thr82, Val271, Tyr272, Asp292 Trp80, Val270
VEGFA Ser50, Cys61, Asn62, Asp63 Asp34, Glu64 Asp63, Arg224 Ile46, Glu64
EGFR Lys745 Leu777, Leu788, Leu858, Phe856 – Leu759, Met766, Leu788, Leu858,

Fig. 6. MD Simulation analysis of 5-Hydroxy-7–8-dimethoxyflavone and 6-Methoxykaempferol in complex with AKT1.

Fig. 7. MD Simulation analysis of 5-Hydroxy-7–8-dimethoxyflavone and 6-Methoxykaempferol in complex with EGFR.

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M.A. Alamri and M. Tahir ul Qamar Saudi Pharmaceutical Journal 31 (2023) 101802

Fig. 8. MD Simulation analysis of 5-Hydroxy-7–8-dimethoxyflavone and 6-Methoxykaempferol in complex with VEGFA.

containing compounds, response to organonitrogen compounds, damage and triggering inflammation, thereby contributing to can-
and the regulation of programmed cell death. Each of these activ- cer development (Kundu and Surh 2008). Taken together, our
ities has notable roles within inflammatory processes. Oxygen- results suggest that the anti-inflammatory actions of D. angustifolia
containing compounds include reactive oxygen species (ROS), may involve multiple biological processes and pathways that are
which are known mediators of inflammation. An overproduction critical in the regulation of inflammation.
of ROS can lead to oxidative stress, triggering inflammatory Further, compound-target-pathway and PPI network identified
responses and contributing to the pathogenesis of several inflam- 6 Methoxykaempferol and 5-Hydroxy-7,8 dimethoxyflavone as
matory diseases, such as atherosclerosis and rheumatoid arthritis potential key chemicals, as well as AKT1, VEGFA, and EGFR as
(Mittal et al., 2014). On the other hand, Organonitrogen com- potential key targets. AKT1 is important for the promotion of
pounds such as nitric oxide (NO) are recognized as key signaling microvascular leakage in response to inflammatory stimuli such
molecules in various physiological processes, including inflamma- as histamine, and consequently controls the amplitude of this reac-
tion. Elevated levels of NO are often observed in inflammatory con- tion(Di Lorenzo et al., 2009). VEGFA (vascular endothelial growth
ditions, playing a crucial role in vasodilation, increased vascular factor A) is a protein family that has been linked to the develop-
permeability, and leukocyte adhesion, which are hallmarks of ment of vascular endothelial cells, with VEGFA being the most
inflammation (Bogdan 2001). ubiquitous and abundantly expressed member(Vafadari,
Regulation of programmed cell death or apoptosis is a vital pro- Salamian and Kaczmarek 2016). Recent research has found that
cess in controlling inflammation. During an inflammatory VEGFA is intimately associated to the occurrence and progression
response, apoptotic cell death helps in the resolution of inflamma- of inflammatory disorders(Fatima et al., 2017). The epidermal
tion by promoting the removal of activated immune cells, thereby growth factor receptor (EGFR) has been identified as a major initia-
preventing excessive tissue damage (Serhan et al., 2015). In addi- tor exploited by several pathogens for host survival and triggering
tion to the GO functional analysis, our KEGG pathway analysis inflammatory responses. Current research suggests that EGFR acti-
revealed that these targets are involved in various pathways vation may have a role in inflammatory disorders(Pastore et al.,
including cancer pathways, pI3k-Akt signaling pathway, metabolic 2008).
pathways, chemical carcinogenesis, and endocrine resistance. Each Further, molecular docking and molecular dynamic (MD) simu-
of these pathways has established connections to inflammation. lation of D. angustifolia active ingredients (6-Methoxykaempferol
For instance, the pI3k-Akt pathway is a key regulator of cell sur- and 5-hydroxy-7,8 dimethoxyflavone) with core proteins (AKT1,
vival and proliferation and is often dysregulated in inflammation. VEGFA, and EGFR) was performed. Docking and simulation results
The activation of this pathway leads to the production of pro- supported our findings and demonstrated that these compounds
inflammatory cytokines, promoting inflammatory responses bind steadily to the target genes’ active pockets, highlighting the
(Fruman et al., 2017). Similarly, inflammation is an integral part possibility that these substances could be used to treat inflamma-
of cancer development and progression, with many signaling path- tion by inhibiting the AKT1, VEGFA, and EGFR genes.
ways shared between inflammation and cancer, such as NF-kB and To sum up, in the context of acute inflammation, the active
STAT3 pathways (DiDonato, Mercurio and Karin 2012). compounds of D. angustifolia, especially the identified flavonoids
Metabolic pathways are also closely intertwined with inflam- 6-Methoxykaempferol and 5-Hydroxy-7,8-dimethoxyflavone,
mation. During inflammation, there is a metabolic shift in immune may have a significant role. By modulating key molecular targets
cells, with changes in glucose, lipid, and amino acid metabolism like AKT1, VEGFA, and EGFR, which play integral roles in cell sur-
that support the immune response (O’Neill, Kishton and Rathmell vival, proliferation, and angiogenesis, these compounds could
2016). Chemical carcinogenesis involves the formation of cancer potentially control the excessive inflammatory response and pre-
due to chemical exposure, with many carcinogens causing DNA vent consequent tissue damage.

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M.A. Alamri and M. Tahir ul Qamar Saudi Pharmaceutical Journal 31 (2023) 101802

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