Morin Modulates Key Targets and Pathways Associated with Gastric Cancer: Network Pharmacology, Molecular Docking, Molecular Dynamics, ADMET, and In‑Vitro Analysis

Morin Modulates Key Targets and Pathways Associated with Gastric Cancer: Network Pharmacology, Molecular Docking, Molecular Dynamics, ADMET, and In‑Vitro Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Morin Modulates Key Targets and Pathways Associated with Gastric Cancer: Network Pharmacology, Molecular Docking, Molecular Dynamics, ADMET, and In‑Vitro Analysis Nilesh Naskar, Sunil Kumar, Bijo Mathew, Naseer Maliyakkal, Shweta Shrivastava, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7632832/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Apr, 2026 Read the published version in Molecular Diversity → Version 1 posted 16 You are reading this latest preprint version Abstract Gastric cancer (GC), widely known as stomach cancer, is a critical health concern across the world. It ranks among the world’s five most common cancer types and is third in terms of fatalities from tumour disease. Natural products have been renowned for millennia and are highly reputable as a fashionable supply of therapeutic agents. Morin is a natural flavonoid found in a range of plants within the Rosaceae, Fagaceae, and chiefly Moraceae families. Network pharmacology, molecular docking, molecular dynamics simulations, and an in vitro cytotoxicity study were conducted. We have identified the top 10 hub genes (PIK3R3, PIK3CA, PIK3CB, PIK3CD, PIK3R2, PLCG1, JAK2, IGF1R, ZAP70, ERBB4) from network pharmacology analysis. Further molecular docking analysis revealed that morin has high binding affinities to PIK3CD (-11.01 kcal/mol), ZAP70 (-10.72 kcal/mol), JAK2 (-10.53 kcal/mol), IGF1R (-9.99 kcal/mol), PIK3CA (-9.79 kcal/mol), and ERBB4 (-8.83 kcal/mol). Molecular dynamics simulations confirmed the binding stability of morin with proteins like JAK2, PIK3CA, and IGF1R. The MTT assay demonstrated a significant escalation in the cytotoxicity of AGS GC cells following treatment with higher concentrations of morin. From in silico study results, we identified key oncogenic targets of morin which mainly work through PI3K-Akt pathway of GC which can be used as a reference for further research. An in vitro cytotoxicity study revealed that morin effectively inhibits the proliferation of AGS GC cells. Gastric cancer Morin Network pharmacology Molecular docking Molecular dynamics AGS cells Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 Figure 17 INTRODUCTION Among all non-communicable diseases, cancer comes after cardiovascular diseases in terms of cause of death. Cancer affecting the stomach, medically termed as gastric cancer (GC), is the fifth most prevalent kind of cancer that is ranked among top four leading contributors to death due to cancer [ 1 ]. The eastern parts of Europe and Asia along with Central and South America are particularly vulnerable to stomach cancer. On the other hand, regions like New Zealand, Australia, and portions of Africa and North America are not at high danger [ 2 ]. The condition is affected by environmental and genetic factors and risk is rising with age. Factors such as biliary pancreatic reflux, chronic inflammation, atrophic gastritis, and H. pylori infection are contributing to the onset of GC [ 3 ]. Over the past years, different advances have been achieved through chemotherapy, radiation, immunotherapy and surgery in the field of cancer. Chemotherapy is effective but often leads to unpleasant side effects like exhaustion, hair loss, bleeding, infections and gastrointestinal problems including nausea and constipation. Radiation treatment can also damage healthy tissue in the immediate region of a tumour. Although a promising and fast-developing treatment, immunotherapy varies greatly across people. It may not be helpful in many patients, particularly in those with immune-evasive tumours, and can have major immunological side effects in many organs. Although surgery is the mainstay for localised cancer and could lead to a cure, tumour size or location often limits it. Furthermore, surgery carries risks, extended recovery times, and might not be suitable for people in a poor health condition or with disseminated illness. These limitations highlight the necessity of more customised, less intrusive, directly targeted cancer therapies that are easier on the normal tissues but more difficult on the malignant ones [ 4 ]. Overall treatment options for cancer and their limitations are summarized in Fig. 1 . Humans have used a wide variety of natural foods to cure a wide range of illnesses for the last thousand years. These foods include fruits, flowers, plant roots and vegetables, which are correlated with a lower risk of cancer related deaths [ 5 ]. Bioactive substances including carotenoids, flavonoids, phenolic acids, lignans and stilbenes have been identified in these foods and may have a major impact in the treatment of disease and ailments [ 6 ]. Polyphenolic flavonoids are a category of biologically active substances that are naturally present in a wide variety of plant species. These substances are distinguished by their phenylbenzopyran framework, which is distinguished by over 8000 identified derivatives and six subclasses that depend on variances in their heterocyclic ring C. These subclasses include flavonols, flavanones, flavan-3-ols, flavones, isoflavones and anthocyanins [ 5 , 7 ]. Morin was first documented in the year of 1830, which is a yellow bioactive pigment that occurs naturally as a flavonol. It is also referred to as 3,5,7,2′,4′-pentahydroxyflavone, Calico Yellow, Aurantica and morin hydrate. It is particularly common in fruits and plants belonging to the Rosaceae, Moraceae, and Fagaceae groups [ 8 – 10 ]. Morin was found in Osage orange ( Maclura pomifera ), sweet chestnut ( Castanea sativa ), old fustic ( Maclura tinctoria ), white mulberry ( Morus alba L), jack fruit ( Artocarpus heterophyllus ), bambangan ( Mangifera pajang ), figs ( Chlorophora tinctoria) , guava ( Psidium guajava ), apple skin ( Malus pumila ), almond ( Prunus dulcis ), and bambangan ( Mangifera pajang ). Apart from that, morin was found in a wide variety of natural foods and beverages including onions, red wine, seaweed, tea and coffee [ 11 ]. The specific biosynthesis pathway of morin is unknown but anticipated that it is following the conventional flavonoid biosynthesis pathway named shikimate pathway. It is initiated from L-phenylalanine, converted into 4-coumarate: CoA with the help of phenylalanine ammonia-lyase (PAL). With the help of chalcone synthase (CHS), one of the chalcone derivative 2',4,4',6'-tetrahydroxychalcone formed. The enzyme Chalcone-flavanone isomerase (CHI) is responsible for the isomerisation of the chalcone intermediate, which results in the production of naringenin, a central flavanone. Finally, particular hydroxyl groups introduced by flavonoid 3′,5′-hydroxylase (FH) introduced particular hydroxyl groups to produce morin (3,5,7,2′,4′-pentahydroxyflavone) [ 11 , 12 ]. Figure 2 illustrates the biosynthetic pathway of morin. Researchers have discovered that morin has several therapeutic properties, including antioxidant, antihypertensive, anti-inflammatory, antibacterial, antihyperlipidemic, antidiabetic, antiallergic, antihyperuricemic, antithrombotic, antiviral, and anticancer properties [ 13 ]. Morin exhibited numerous pharmacological activities by blocking phosphorylation and protein expression associated with key molecular pathways like Wnt/𝛽-catenin, Keap1/Nrf2, mTOR, JAKs/STATs, NF-қB and MAPK pathways [ 14 ]. Kyu-Shik Lee et al. (2021) reveal that morin can suppress HER2/EGFR signaling pathway across the various cell lines of breast cancer, resulting in apoptosis and hindering metastasis [ 15 ]. According to Fakhredini et al. (2024), Morin facilitates the processes of autophagic and apoptotic cell death in human prostate cancer PC3 cells through modulation of the AMPK/ULK1/mTOR signaling pathway, highlighting its ability to control energy metabolism as well as apoptosis [ 16 ]. Morin also increases the effectiveness of cisplatin in ovarian carcinoma cells and apoptosis of melanoma cells [ 17 , 18 ]. Gao et al. (2022) showed that aloin has both anti-proliferative and pro-apoptotic actions on GC cells through the PI3K/AKT signaling pathway, utilizing a network pharmacology approach alongside in vitro experiments [ 19 ]. Huang et al. (2020) demonstrated the considerable cytotoxic effects of gentiopicroside, along with its capability to induce cell cycle arrest in GC cells through PI3K/AKT and p38 MAPK pathways, which was confirmed using bioinformatics and experimental assays [ 20 ]. Further research suggests that morin has significant anticancer properties across many tumour types. But research on morin's therapeutic benefits and mechanisms in GC is lacking. Both network pharmacology and molecular docking are emerging tools that are derived from the principles of computational biology, bioinformatics and analysis of molecular correlations derived from databases. These technologies are used for the purpose of discovering novel medications and predicting the targets that are associated with them [ 21 ]. Consequently, in order to address some of the gaps in the current literature, we want to thoroughly examine the underlying molecular processes of morin in the management of GC through insilco and invitro approaches. To our knowledge, this is one of the first studies to provide integrated network pharmacology and molecular dynamics insight into the mechanistic basis of morin’s anticancer effects in gastric cancer. Findings may maximise morin's therapeutic potential and provide fresh perspectives for the designing of innovative natural medication with anti-GC properties. MATERIALS AND METHODS Exploration of morin-associated targets in GC The PubChem platform ( https://pubchem.ncbi.nlm.nih.gov ) was utilized to retrieve the 2D structure of the compound “Morin” (PubChem CID: 5281670), and that was used for the further step. We used the PharmMapper ( http://www.lilab-ecust.cn/pharmmapper/ ) tool to identify potential drug-related targets. The parameters, i.e., 300, and pharmacophore mapping were set to find out human protein targets only. The disease-related targets were retrieved using the keyword “Gastric cancer” with the help of two databases, i.e., GeneCards ( https://www.genecards.org/# ) and Open Targets Platform ( https://platform.opentargets.org/ ). In some cases, the UniProt ( https://www.uniprot.org ) database was engaged to find out the official symbols of the target proteins. A venn analysis was done to find out the common targets between morin and gastric cancer. Venny 2.1.0 ( https://bioinfogp.cnb.csic.es/tools/venny/ ) platform was utilized for creating venn diagram. Protein-protein interaction (PPI) network construction and key targets screening We used the Cytoscape app (version 3.10.1) for this purpose. In that stringApp (v2.1.1) was installed, and common genes were inserted for network construction. In the operating interface, only human ( Homo sapiens ) data were considered and a full-string network was created with selected the confidence level and maximum additional interactions at ≥ 0.9 and ≥ 30 respectively. MCODE (v2.0.3) was used for the generation of clusters of a big network. To sort out the core composite targets, three crucial topological parameters, i.e., betweenness centrality (BC), degree centrality (DC) and closeness centrality (CC), were chosen in cytoHubba (v0.1). On the basis of these three parameters, we got ten genes each for every parameter and plotted them in a bar graph to extract the top ten hub genes. Gene Ontology (GO) & KEGG pathway analysis Using GO enrichment profiling, we make sense of the biological processes, activities and intracellular localization of enriched for a given set of genes. GO was assessed by using the database ShinyGo 0.80 ( http://bioinformatics.sdstate.edu/go/ ) where the top ten hub genes were considered for assessment of cellular component (CCT), molecular function (MF) and biological process (BP) mainly associated with gastric cancer. For the purpose of the analysis, the following parameters were considered: the species was human, a cut-off value of 0.05 was set for false discovery rate (FDR), and the number of paths to show was set at 20. The Kyoto Encyclopaedia of Genes and Genomes (KEGG) Pathway Database ( https://www.genome.jp/kegg/pathway.html ) was utilized to conduct the pathway enrichment study related to gastric cancer. Molecular docking analysis Protein preparation Structures of the target protein corresponding to the hub genes were collected using the RSCB PDB and UniProt. Protein IDs were selected considering certain features such as the X-ray crystallography resolution around 2.0 Å with monomer or dimer biological assembly. The structure needs to be in either an active or inactive conformation typically attached to an inhibitor with no mutations. The key information regarding selected proteins are compiled in Table S1 . Then retrieved protein files were processed by the protein preparation wizard module of Schrodinger. Initially, the proteins' structures were prepared for further processing by bond order definition, introducing H atoms introduction, disulfide linkage construction, reconstruction of loops and missing chain, assigning bond orders and removing H 2 O molecules exceeding a distance of 5 Å. Furthermore, the pre-processed proteins were fine-tuned using PROPKA at pH:7 and the OPLS4 force field was utilised with optimum potentials to minimise it. Ligand preparation From the PubChem database, the 2D structure of morin with the PubChem CID of 5281670 was downloaded in SDF format. Further ligand was processed by utilizing the Schrödinger’s LigPrep tool with OPLS4 force field. The ionization and computation methods were set as ‘Do not change’ and ‘Determine chiralities from 3D structure’. A single low-energy conformer of the ligand was generated which was further used for in silico docking analysis. Receptor grid construction and ligand docking Within the workspace grid box was generated via Schrödinger’s receptor grid generation wizard, guided by the native ligand coordinates. The dimensions of the bounding box were configured to resemble those of the workspace ligand and no restrictions were applied to any atoms inside the protein's binding pocket. After that docking was carried out with prepared proteins and ligand in XP (extra precision) mode applying a scaling factor and partial charge cutoff of 0.8 and 0.15, respectively. A blind docking strategy was conducted on those PDB Ids lacking of an active inhibitor binding site. Molecular dynamics As a computer simulation tool, molecular dynamics (MD) examines the time-dependent physical motions of atoms which captures the dynamic behaviour of the atoms, including their vibrational, rotational, and translational movements. The docked complexes with a docking score of more than – 8 kcal/mol are only considered for the dynamics study. The system was configured with the system builder panel in desmond of schrodinger’s academic version. Solvation was performed with the water model of SPC by applying the orthorhombic simulation box with a 10 Å distance on all sides. To ensure charge neutrality, sodium cation and chloride anions were incorporated at a final ionic strength of 0.15 M and subsequently recalculation was done. Molecular dynamics simulation was set up in the NPT ensemble mode where temperature and pressure were maintained at 310 K and 1.01325 bar, respectively. 100 ns molecular dynamics run was executed with storing output every 100 ps and an approximate frame count of 1,000 for subsequent analysis. Lastly, the simulation interaction diagrams were obtained which consist of protein-ligand root-mean square deviation (RMSD), root-mean square fluctuation (RMSF), and time-dependent protein-ligand contacts data of each complex. These data were further used to analyse the MD-simulation trajectory [ 22 ]. Physicochemical properties and toxicity assessment of morin The chemical structure of morin obtained through PubChem ( https://pubchem.ncbi.nlm.nih.gov ). The drug-likeness, physicochemical, and toxicological properties of the molecule were evaluated utilized SwissADME ( http://www.swissadme.ch/ ) and ProTox 3.0 ( https://tox.charite.de/ ). Cell Lines The human gastric adenocarcinoma cell line AGS was procured from NCCS, Pune, India. It was cultured using complete media consisting of v-Nutrient Mixture F-12 Ham with 10% NuSera Serum replacement solution and 200 µg/ml antibiotic solution, which are purchased from HiMedia, Mumbai, India. AGS cells were propagated in T-25 flasks and incubated in a humidified incubator under the controlled conditions (37°C, 5% CO₂). The cell line was sub-cultured by enzyme digestion with 0.25% trypsin/1 mM EDTA when the cultures became about 70–80% confluent. Morin was solubilised in DMSO to obtain a 20 mM mother stock and subsequently adjusted to desired concentrations using basal media. Cell viability assay MTT assay was performed to evaluate cell viability. It relies on the colorimetric detection of purple coloured formazan transformed through viable cell metabolism from yellow tetrazolium salt. In a 96 well plate AGS cells were seeded at a density of 1×10 4 cells per well in 100 µl of medium. The next day, after incubation, morin treatment was given at concentrations of 6.25, 12.5, 25, 50 and 100 µM for 24 hours. Subsequently, media was aspirated from each well and 10 µl of MTT (5 mg/ml) was included. The medium was then incubated for 4 hrs at 37°C. Once the MTT- supplemented media was discarded, the produced purple crystals of formazan were solubilized in 200 microlitres of dimethyl sulfoxide. Reading was taken with the help of microplate reader by setting wavelength at 570 nm (23, 24). RESULTS Exploration of morin-associated targets in GC After removing the duplicates, overall, 294 morin-associated targets were isolated from PharmMapper. In a similar way, 242 and 13,898 targets of GC were retrieved by using the database of Open Targets Platform and GeneCards. Subsequently, the shared genes of morin and GC were screened out by constructing a venn diagram (Fig. 3 A). Specifically, 4 common targets in “PharmMapper” and “Open Targets Platform”, 62 common targets in “PharmMapper” and “GeneCards”, and 117 common targets in “PharmMapper”, “GeneCards” and “Open Targets Platform” were obtained. Overall, 183 unique overlapping targets are listed in Table S2. PPI network construction and key targets screening We imported the 183 common targets to the STRING database by using Cytoscape 3.10.1. A STRING network (Fig. S1 ) formed with 213 nodes and 675 edges. With the help of MCODE, a total of eight clusters (Fig. S2) were generated which are listed in Table S3. Among all the clusters, cluster 1 had the highest score and was further considered for topological parameters analysis. By using cytoHubba, degree centrality (DC), closeness centrality (CC), and betweenness centrality (BC) were analyzed (Fig. 3 B, 3 C, AND 3 D). The rank of the corresponding gene of all the topological parameters are listed in Table S4, S5 and S6. Finally, with a bar graph (Fig. S3) the top 10 hub genes are shorted out which are PIK3R3, PIK3CA, PIK3CB, PIK3CD, PIK3R2, PLCG1, JAK2, IGF1R, ZAP70 and ERBB4. Gene Ontology & KEGG Pathway Analysis Involving the top ten hub genes, enrichment analyses for GO and KEGG pathways were carried out via ShinyGO 0.80. The result showed that morin versus GC exhibited considerable enrichment in 1000 biological processes, 80 cellular components, and 104 molecular functions. Among the top 20 pathways of biological processes (Fig. 4 ), many are very enriched. For cell survival and proliferation, Phosphatidylinositol-3-phosphate biosynthetic process, phosphatidylinositol phosphate biosynthetic process and phosphatidylinositol 3-kinase are playing a crucial role. On another note, endothelial cell migration, ameboidal-type cell migration and cell motility and localization have a significant correlation with tumour spread and invasion. The analysis also highlights the role of transmembrane receptor protein tyrosine kinase signaling, enzyme-linked receptor protein signaling and regulation of kinase activity which are essential for cancer cell communication and signal transduction. Upon examining the foremost 20 pathways of cellular components (Fig. 5 ), the most significantly augmented components include various classes of the phosphatidylinositol 3-kinase (PI3K) complex which are crucial in regulating cancer cell proliferation, metabolism, and viability through the PI3K-Akt signalling pathway. Moreover, insulin receptor complex, caveolae, and plasma membrane receptor complexes are involved in signal transduction, endocytosis, and metabolic control. After assessment of 20 pathways of molecular functions (Fig. 6 ), it was found that various phosphatidylinositol kinase activities are most significantly enriched which are mainly associated with cell survival and proliferation. Additionally, functions like insulin receptor substrate binding suggest a link to metabolic dysregulation particularly via insulin signalling. Based on the KEGG pathway analysis, the hub genes were highly enriched for 128 pathways. The top twenty pathways which have a high level of enrichment are displayed in Fig. 7 . While examining the GC pathway (Fig. S4) very closely, it was found that the subclass of the PI3K gene (PIK3CA, PIK3CB, PIK3CD, PIK3R2 and PIK3R3) were mainly targeted by morin in two main pathways like PI3K-Akt signaling pathway (Fig. S5) and MAPK signaling pathway. In the above two mentioned pathways, morin also targets other genes, i.e., ERBB4, IGF1R and JAK2 in the PI3K-Akt signaling pathway and ERBB4 and IGF1R in MAPK signaling pathway. Molecular docking Docking assessment was performed involving the ligand morin on the top 10 hub genes. The molecular docking investigations indicated that morin had good binding affinities to a number of target proteins involved in gastric cancer. Lower (more negative) docking scores meant a higher binding affinity. The docking study outcomes revealed that the maximum and minimum docking scores are − 11.013 kcal/mol and 2.60 kcal/mol respectively. Docking scores higher than − 8 kcal/mol, showed strong binding strengths. Many protein-ligand combinations including PIK3CD (-11.013 kcal/mol), ZAP70 (-10.726 kcal/mol), JAK2 (-10.535 kcal/mol), IGF1R (-9.994 kcal/mol), PIK3CA (-9.790 kcal/mol), and ERBB4 (-8.836 kcal/mol) are some well-known finding cases. These values indicate that the proteins have strong binding affinity at their active sites and further validate via molecular dynamics stimulation. There were many different types of molecular interactions found in all protein ligand complexes which include hydrogen bonding, pi–pi stacking, and pi–cation interactions. Hydrogen bonding interaction is the majority among all interactions and it plays an important role in stabilizing the ligand inside the active binding sites. Specifically, Pi–Pi stacking interactions were seen in the PIK3CD and PIK3CA complexes with aromatic residues TRP 760 and TRP 780 respectively. Only Pi–cation interactions were found in the PIK3R3 complex with LYS 242. Table 1 lists a comprehensive summary of the docking results and protein–ligand 2D interaction profiles are depicted in Fig. 8 , Fig. 9 A, Fig. 10 A, Fig. 11 A, Fig. 12 A. Figure 13 A, and 14 A. Table 1 Docking scores of morin with GC related proteins. S. no Target protein PDB ID Key residues located within the active site Type of interaction Docking score (kcal/mol) 1 PIK3R3 5ZUT GLU 7 Hydrogen bond -5.125 ALA 56 Hydrogen bond ARG 14 Hydrogen bond LEU 221 Hydrogen bond LYS 242 Pi-Cation 2 PIK3CA 8EXL GLU 849 Hydrogen bond -9.790 VAL 851 Hydrogen bond TRP 780 Pi–Pi stacking 3 PIK3CB No PDB ID found 4 PIK3CD 6PYR VAL 828 Hydrogen bond -11.013 GLU 826 Hydrogen bond LYS 779 Hydrogen bond TRP 760 Pi–Pi stacking 5 PIK3R2 7RNU ASP 337 Hydrogen bond -2.603 ARG 340 Hydrogen bond 6 PLCG1 7NXE HIE 607 Hydrogen bond -6.597 THR 596 Hydrogen bond SER 588 Hydrogen bond GLU 589 Hydrogen bond 7 JAK2 4D1S GLU 930 Hydrogen bond -10.535 LEU 932 Hydrogen bond PRO 933 Hydrogen bond 8 IGF1R 5FXS MET 1082 Hydrogen bond -9.994 GLU 1080 Hydrogen bond ASP 1153 Hydrogen bond GLN 1007 Hydrogen bond 9 ZAP70 1U59 ASP 479 Hydrogen bond -10.726 ALA 417 Hydrogen bond 10 ERBB4 3BBT MET 774 Hydrogen bond -8.836 ASP 836 Hydrogen bond Molecular dynamics JAK2 (PDB- 4D1S) and Morin The protein RMSD (Fig. 9 B) showed that there was a stable conformation from initial to 100 ns with minimal fluctuation between 0.942 and 2.84 Å. Ligand RMSD was more or less stable, and there is a continuous interaction of protein and ligand. At some points (0.3–0.5, 1.1–1.7, 22.1–24.8, 72.2–72.6, 73.8, 74.6–75.1 ns), ligand RMSD is more than protein RMSD, but that is negligible. The vertical bars with a green colour indicate that the protein residues interact with the ligand (Fig. 9 C). The residues which are in contact with the ligand, i.e., LEU 932, MET 929, GLY 856, TYR 931, LYS 857, ARG 980, ASP 994, PRO 933, GLY 858, GLU 930, VAL 863, SER 936, ARG 938, LYS 943, LEU 855, TYR 934, ASP 939, GLN 853, LEU 983, and ALA 880. Also, there is low fluctuation during contact. Overall, a protein RMSF value is less than 2.5 Å, indicating good stability. During molecular docking (Fig. 9 A), morin formed hydrogen bonds with the GLU 930, LEU 932 and PRO 933 residues of JAK2. Further, molecular dynamic simulations (Fig. 9 D & 9 E) promoted new significant binding contacts of morin with JAK2 residues LEU855 and ALA880. PIK3CA (PDB- 8EXL) and Morin The protein RMSD (Fig. 10 B) initiates from 1.345 Å and gradually increases until 25 ns, then maintains a steady state up to 43.8 ns. Furthermore, scaling up was observed at 46.1 ns with the RMSD value of 4.362 Å and ended up with 3.249 Å. Ligand RMSD is more or less stable with a minimum of 0.476 Å and a maximum of 2.651 Å. The RMSD value of the ligand was less than the protein RMSD, which indicates the ligand was localized in its binding site throughout the stimulation period. Up to residue index 400, protein RMSF (Fig. 10 C) was fluctuating, then stabilized for all residues except residues 730 and 804 with RMSF of 4.195 Å and 4.936 Å. There is minimal fluctuation during contact of ligand with protein. The residues which are in contact with the ligand, i.e., MET 922, ASP 810, MET 772, ILE 848, GLN 859, SER 773, PHE 934, THR 856, LYS 802, SER 774, ASP 805, TRP 780, VAL 851, ARG 770, ILE 800, GLU 849, ALA 775, TYR 836, SER 919, ILE 932, SER 854, and ASP 933. During molecular docking (Fig. 10 A), morin interacted with PIK3CA by the formation of pi–pi stacking with TRP 780 along with hydrogen bonding linked to VAL 851 and GLU 849. Further, molecular dynamic simulations (Fig. 10 D & 10 E) promoted new significant binding contacts between ILE 800, ILE 932, LYS 802, MET 922, ILE 848 and ASP 810 residues in PIK3CA and morin. PIK3CD (PDB- 6PYR) and Morin In the initial time, protein RMSD (Fig. 11 B) was fluctuating, and after 25 ns, it was stabilized till 70 ns with the RMSD around 4 Å. Then it was again fluctuating and it ended up with 4.226 Å. Ligand RMSD was initiated from 0.671 Å and gradually increased. After 25 ns, it maintained a steady state until 70 ns, followed by a gradual decrease. This complex has the best docking score, but molecular dynamics simulations confirmed unstable ligand-protein interactions that deny morin’s binding stability. Throughout the stimulation period, protein RMSF (Fig. 11 C) was fluctuating, but there was minimal fluctuation while it contacted the ligand with few exceptions. The residues which are in contact with the ligand, i.e., PHE 912, ASP 787, SER 842, MET 752, ASP 897, LYS 841, ILE 910, GLU 826, ILE 777, ASP 782, MET 900, TRP 760, VAL 828, THR 833, ASN 836, ARG 830, LYS 779, ASP 832, TYR 813, SER 754, ILE 825, VAL 827, SER 831, and ASP 911. Molecular docking (Fig. 11 A) results showing that morin interacted with PIK3CD by the formation of pi–pi stacking with TRP 760 and hydrogen bonds with VAL 828, GLU 826 and LYS 779 residues. Molecular dynamic simulations (Fig. 11 D & 11 E) promoted new binding contacts between ILE 777, SER 831, ASP 832M, MET 900 and ASP 911 residues of PIK3CD and morin. IGF1R (PDB- 5FXS) and Morin The starting protein RMSD (Fig. 12 B) was 1.516 Å and fluctuated until 20 ns. Thereafter, it maintained a steady state around 3 Å with minimal deviation and ended up with 3.506 Å. From initial to 26.2 ns, ligand RMSD fluctuates between 0.452 Å and 2.453 Å. Then it reached around 3 Å and maintained stable conformation till the end, except for a deviation around 50 ns. The protein RMSF (Fig. 12 C) was below 3 Å from the residue index 9 to 305, except for the range of 120 to 126. The residues which are in contact with the ligand, i.e., VAL 1013, GLU 1015, ALA 1031, LYS 1033, VAL 1063, MET 1079, GLU 1080, LEU 1081, MET 1082, THR 1083, ARG 1084, GLY 1085, ASP 1086, SER 1089, ARG 1139, MET 1142, ASP 1153, PHE 1154, GLY 1155, MET 1156, THR 1157, ILE 1160, and TYR 1161. Here the number of contacts between ligand and protein is more. Molecular docking (Fig. 12 A) results revealed that morin formed hydrogen bonds with MET 1082, GLU 1080, ASP 1153 and GLN 1007 residues of 5FXS. Further, molecular dynamic simulations (Fig. 12 D & 12 E) promoted new binding contacts between MET 1156 residues of 5FXS and morin. ZAP70 (PDB- 1U59) and Morin The protein RMSD (Fig. 13 B) initiated from 1.11 Å and showed a stable confirmation until 60 ns. Then a gradual increase up showed around 3.5 Å and ended up with 3.095 Å. Ligand RMSD is fluctuating throughout the stimulation period. Around 80 ns, it was deviated more and reached around 3 Å. Up to 60 ns, the RMSD of the ligand is more than the RMSD of the protein in most of the cases that indicate the ligand drifted away from the binding pocket. There is minimal fluctuation while the ligand and protein come into contact, and it is below RMSF 2 Å (Fig. 13 C). The residues which are in contact with the ligand, i.e., PHE 349, ASN 466, GLY 420, LEU 344, LYS 369, GLU 343, CYS 346, VAL 352, GLU 415, GLY 419, PRO 421, SER 478, MET 414, ARG 465, ASP 479, GLU 386, ASN 348, VAL 467, PHE 480, LYS 424, ALA 367, GLY 418, LEU 468, GLN 354, and ALA 417. A 2D diagram of molecular docking (Fig. 13 A) revealed that morin formed hydrogen bonds with the ASP 479 and ALA residues of ZAP70. Molecular dynamic simulations (Fig. 13 D & 13 E) promoted new binding contacts between LEU 344, GLU 415, ARG 465 and SER 478 residues in ZAP70 and morin. ERBB4 (PDB- 3BBT) and Morin The protein RMSD (Fig. 14 B) starts from 1.226 Å and rapidly fluctuates till 68 ns, indicating changes in the structural conformation. After that, it stabilised at around 5 Å. Ligand RMSD has a minimum of 0.41 Å and a high of 2.327 Å, making it relatively stable. A lower ligand RMSD than that of the protein suggests that the ligand remained at its binding site during the stimulation period. There is not much variation when the ligand and protein come into contact, and it is below 1.6 Å (Fig. 14 C). The residues which are in contact with the ligand, i.e., GLN 772, LYS 709, THR 835, LEU 825, ALA 724, GLU 781, HIS 776, GLY 700, VAL 707, LEU 699, CYS 778, MET 774, THR 771, SER 701, ARG 822, GLY 777, PRO 775, ASP 836, LEU 769, and ASN 823. During molecular docking (Fig. 14 A), morin formed H-bonds with the MET 774 and ASP 836 residues of ERBB4. Molecular dynamic simulations (Fig. 14 D & 14 E) promoted new binding contacts between GLN 722, GLU 781, ARG 822 and ASN 823 residues of ERBB4 and morin. Physicochemical properties and toxicity assessment of morin The ADME information of morin was retrieved from SwissADME and shown in Table 2 and Fig. 15 A. Morin is a drug-like compound which is freely soluble in water with moderate lipophilicity (iLOGP 1.47) property. It is rapidly absorbed through the gastrointestinal tract and poorly permeable to the blood-brain barrier. Apart from this, it also follows Lipinski's rule of five. Morin’s toxicity profile was evaluated using the ProTox-II (version 3.0) platform, and the report predicted that morin comes under toxicity class V, which implies it may be harmful if swallowed (2000 < LD₅₀ ≤ 5000 mg/kg), with a lethal dose (LD₅₀) of 3919 mg/kg (Fig. 15 B). It has a moderate safety profile with selective organ-specific hazards, according to projections of organ toxicity. Morin is active for nephrotoxicity and respiratory toxicity but inactive for hepatotoxicity, carcinogenicity, cardiotoxicity and neurotoxicity (Fig. 15 C). Table 2 Physicochemical Properties of Morin Physicochemical Properties Formula C 15 H 10 O 7 Molecular weight 302.24 g/mol Num. heavy atoms 22 Num. arom. heavy atoms 16 Num. rotatable bonds 1 Num. H-bond acceptors 7 Num. H-bond donors 5 Molar Refractivity 78.03 Lipophilicity Log Po/w (iLOGP) 1.47 Water Solubility Log S (ESOL) -3.16 Solubility 2.11e-01 mg/ml; 6.98e-04 mol/l Class Soluble Pharmacokinetics GI absorption High BBB permeant No CYP1A2 inhibitor Yes CYP2C19 inhibitor No CYP2C9 inhibitor No CYP2D6 inhibitor Yes CYP3A4 inhibitor Yes Log K p (skin permeation) -7.05 cm/s Druglikeness Lipinski Yes Cell viability The cytotoxic effect of morin on the AGS cell line was evaluated using the MTT assay. Cells were cultured and exposed to the morin with the concentration of 3.125–100 µM. After 24 hrs of treatment with morin, viable cell count decreased in a concentration-dependent manner. The IC 50 value (Fig. 16 ) was found to be 78.8 ± 5.8 µM (mean ± SEM). DISCUSSION Natural products have been renowned for millennia and have established themselves as a rich and reliable source of therapeutic agents due to their availability and lower adverse effects compared to chemotherapeutic drugs [ 25 ]. As stated in Pratas et al. (2024), apigenin is a naturally occurring flavonoid that exerts anti-GC activity by blocking cellular growth and causing apoptosis through the Akt/Bad/Bcl2/Bax-associated mitochondrial pathway [ 26 ]. In a separate study, Wang et al. (2023) showed that astragalin flavonoid decreased cell survival, migration, and invasion, increased apoptosis, and suppressed the PI3K/AKT signaling pathway which leads to effective anti-tumor activity in GC [ 27 ]. Several studies have shown that morin has antiproliferative and apoptosis induction properties in several types of tumours including breast cancer, melanoma, colorectal cancer, lymphoblastic leukaemia, tongue squamous cell carcinoma, lung cancer, head and neck squamous carcinoma, ovarian cancer, prostate cancer, hepatocellular carcinoma, bladder cancer, multiple myeloma and mammary carcinogenesis [ 14 ]. The cellular and molecular mechanism of action of morin against GC is still unknown. Only one or two key targets cannot reveal the actual underlying mechanism of action. So, utilising network pharmacology analysis, we can identify complex interactions between various pathways and key targets of morin on GC. This study aims to anticipate the key targets of morin associated with various pathological pathways of GC by in silico study and further validate them by in vitro experiments. Initially, we identified 183 common target genes between morin and GC from various databases. Then, the PPI network was constructed in the cytposcape platform and the top 10 hub genes were sorted depending upon the topological parameters rank. Among the ten hub genes, five are coming under PI3K class (PIK3R3, PIK3CA, PIK3CB, PIK3CD, PIK3R2) and the others are PLCG1, JAK2, IGF1R, ZAP70 and ERBB4. It was found that morin predominately targets the PI3K-Akt signaling pathway and MAPK signaling pathway after analysis of the KEGG pathway related to gastric cancer. Morin mainly targets the upstream and downstream molecules of the PI3K-AKT cascade. Latest findings have shown that the PI3K-AKT axis has a significant impact on the processes of cell survival, proliferation, migration and apoptosis in GC [ 28 – 30 ]. Docking analysis has shown that morin strongly binds to the critical target proteins, including PIK3CD (-11.01 kcal/mol), ZAP70 (-10.72 kcal/mol), JAK2 (-10.53 kcal/mol), IGF1R (-9.99 kcal/mol), PIK3CA (-9.79 kcal/mol), and ERBB4 (-8.83 kcal/mol). Further, molecular dynamics simulations validated that morin has good binding stability with proteins like PIK3CA, JAK2, and IGF1R by forming new interactions and minimal fluctuations over a 100 ns period. PIK3CA mutations were infrequent, but amplification was highly prevalent in GC and it may be a predominant mechanism of PI3K/Akt activation in GC [ 29 , 31 ]. JAK2 and the transmembrane tyrosine kinase receptor produced by the IGF1R gene are implicated mainly in physiological events like cellular proliferation and survival. It is necessary for subsequent triggering of PI3K/AKT/mTOR signaling cascade in GC [ 32 – 35 ]. Shutting off the PI3K/AKT signaling pathway efficiently reduces mTOR function. As noted by Wang et al. (2023), the pathway’s inhibition leads to the activation of proapoptotic factors like Bax and caspase-9 [ 27 ]. Furthermore, Morgos et al. (2024) mentioned that blocking PI3K/AKT signaling results in the downstream inhibition of mTOR activity, thus eliminating survival signals and inducing apoptosis in GC cells by triggering mitochondrial pro-apoptotic pathways [ 36 ]. Drug-likeness evaluation showed that morin has good pharmacokinetic properties and low toxicity so that it could be a potential drug candidate. Concurrently, in vitro assays were conducted to support the findings of the in-silico study and elucidate the mechanisms of action of morin against GC. In vitro cell viability assay also confirmed the antiproliferative property of morin against the GC cell line. Although the IC 50 value is moderate (84.17 ± 8.2 µM), it aligns with the general range of natural flavonoids and provides a rationale for the future to design more active semi-synthetic derivatives or to use them in combination with existing chemotherapeutic drugs. Our study is limited due to the absence of mechanistic exploration beyond cytotoxicity and in vivo validation. Further studies are needed to explore apoptotic markers, cell cycle regulation, and the compound’s efficacy in xenograft gastric tumor models. In addition, evaluation of combination strategies with standard chemotherapeutics such as 5-FU or cisplatin could uncover synergistic potential and improve clinical relevance. CONCLUSION In summary, the present study provided the mechanistic insight into the anti-cancer potential of the natural flavonoid morin in GC. In this present study, we identify some key targets of morin against GC by employing network pharmacology analysis. From KEGG pathway analysis it was revealed that morin mainly targets the PI3K-AKT axis in GC pathophysiology. Furthermore, supreme targets (PIK3CA, JAK2, and IGF1R) were summarized depending upon the binding affinity and stability from molecular docking and dynamics analysis (Fig. 17 ). In vitro cell viability assay also revealed that morin produces concentration-dependent cytotoxicity on the AGS cell line. Network pharmacology, molecular docking, molecular dynamics and MTT assay along with ADME and toxicity analysis also showed its favourable pharmacokinetic profile and low predicted toxicity, making it a drug-like candidate. Our findings suggest that morin interferes with key oncogenic proteins in GC and can be considered a potential lead compound for further studies. This study primarily relies on databases to predict the targets. The main limitations are some of the targets may be overlooked and these databases are updated from time to time. Lastly, our findings need to be validated through more molecular-level in vitro and distinct in vivo experiments. Future experiments involving in vitro mechanistic studies (western blotting/RT PCR) and in vivo models will be essential to understand its complete anti-cancer mechanism and therapeutic relevance. Declarations Declarations Conflict of interest The authors declare no conflicts of interest. Funding The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through the Small Research Project under grant number RGP1/149/46. This research work was supported by a University Seed Grant from Amrita Vishwa Vidyapeetham, Kochi. Author Contribution N.N. wrote the main manuscript, prepared the figures, and performed the investigation. S.S. carried out data curation, formal analysis, validation and software. B.M. contributed to supervision and software. N.M. contributed to funding acquisition and investigation. S.S. and U.K.R. contributed to concept discussion and writing. M.K.J. contributed to conceptualisation, methodology, funding acquisition, and supervision. All authors reviewed the manuscript. Acknowledgement The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through the Small Research Project under grant number RGP1/149/46. Data Availability The authors declare that the data supporting the findings of this study are available within the paper and its Supplementary Information files. 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Supplementary Files 2SupplementaryMorin20.07.25.docx GRAPHICALABSTRACT.png Cite Share Download PDF Status: Published Journal Publication published 10 Apr, 2026 Read the published version in Molecular Diversity → Version 1 posted Editorial decision: Revision requested 05 Oct, 2025 Reviews received at journal 05 Oct, 2025 Reviews received at journal 04 Oct, 2025 Reviews received at journal 03 Oct, 2025 Reviews received at journal 27 Sep, 2025 Reviewers agreed at journal 19 Sep, 2025 Reviewers agreed at journal 18 Sep, 2025 Reviewers agreed at journal 17 Sep, 2025 Reviewers agreed at journal 17 Sep, 2025 Reviews received at journal 17 Sep, 2025 Reviewers agreed at journal 17 Sep, 2025 Reviewers agreed at journal 17 Sep, 2025 Reviewers invited by journal 17 Sep, 2025 Editor assigned by journal 17 Sep, 2025 Submission checks completed at journal 17 Sep, 2025 First submitted to journal 16 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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analysis pathway.\u003c/p\u003e","description":"","filename":"Picture7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7632832/v1/e12e9e52e30a44cbe859cf1c.jpg"},{"id":92203381,"identity":"65db011d-e5f7-4e5e-8d62-5c09e0644054","added_by":"auto","created_at":"2025-09-25 17:46:12","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":508372,"visible":true,"origin":"","legend":"\u003cp\u003e2D interaction diagram between protein and ligand \u003cstrong\u003eA.\u003c/strong\u003e PIK3R3 (PDB- 5ZUT) and morin. \u003cstrong\u003eB.\u003c/strong\u003e PIK3R2 (PDB- 7RNU) and morin. \u003cstrong\u003eC.\u003c/strong\u003ePLCG1 (PDB- 7NXE) and morin.\u003c/p\u003e","description":"","filename":"Picture8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7632832/v1/ea234f3b5b80dbc3b4f6e5d8.jpg"},{"id":92203388,"identity":"af329263-af50-4cbe-846f-497b8374e147","added_by":"auto","created_at":"2025-09-25 17:46:12","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":996603,"visible":true,"origin":"","legend":"\u003cp\u003eBinding affinity and complex stability of the JAK2-morin. \u003cstrong\u003eA. \u003c/strong\u003eLigand–protein interaction map (2D) between JAK2 (PDB-4D1S) and morin. \u003cstrong\u003eB.\u003c/strong\u003e RMSD analysis of the JAK2-morin complex over time (100 ns) \u003cstrong\u003eC.\u003c/strong\u003e Fluctuation analysis (RMSF) of Cα residues in JAK2. \u003cstrong\u003eD.\u003c/strong\u003e Residue-level contact profile between JAK2 and morin. \u003cstrong\u003eE.\u003c/strong\u003e A time-resolved contact map of morin binding to JAK2.\u003c/p\u003e","description":"","filename":"Picture9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7632832/v1/4d5f0ae8a960ac7c8dab3cb4.jpg"},{"id":92203379,"identity":"6db854ad-48e8-47b7-a9d9-e84a4712b224","added_by":"auto","created_at":"2025-09-25 17:46:12","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":1052084,"visible":true,"origin":"","legend":"\u003cp\u003eBinding affinity and complex stability of the PIK3CA-morin. \u003cstrong\u003eA. \u003c/strong\u003eLigand–protein interaction map (2D) between PIK3CA (PDB- 8EXL) and morin. \u003cstrong\u003eB.\u003c/strong\u003e RMSD analysis of the PIK3CA-Morin complex over time (100 ns) \u003cstrong\u003eC.\u003c/strong\u003e Fluctuation analysis (RMSF) of Cα residues in PIK3CA. \u003cstrong\u003eD.\u003c/strong\u003e Residue-level contact profile between PIK3CA and morin. \u003cstrong\u003eE.\u003c/strong\u003e A time-resolved contact map of morin binding to PIK3CA\u003c/p\u003e","description":"","filename":"Picture10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7632832/v1/0c64a1ec3f41be722dc0f6e4.jpg"},{"id":92204731,"identity":"a1217db0-8af3-4cba-bb03-1dc390309f51","added_by":"auto","created_at":"2025-09-25 18:10:12","extension":"jpg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":1014433,"visible":true,"origin":"","legend":"\u003cp\u003eBinding affinity and complex stability of the PIK3CD-morin. \u003cstrong\u003eA. \u003c/strong\u003eLigand–protein interaction map (2D) between PIK3CD (PDB- 6PYR) and Morin. \u003cstrong\u003eB.\u003c/strong\u003e RMSD analysis of the PIK3CD-morin complex over time (100 ns) \u003cstrong\u003eC. \u003c/strong\u003eFluctuation analysis (RMSF) of Cα residues in PIK3CD. \u003cstrong\u003eD.\u003c/strong\u003e Residue-level contact profile between PIK3CD and morin. \u003cstrong\u003eE.\u003c/strong\u003e A time-resolved contact map of morin binding to PIK3CD.\u003c/p\u003e","description":"","filename":"Picture11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7632832/v1/aee7850f486a8483bae022c1.jpg"},{"id":92204319,"identity":"7da792d6-47d9-474c-a23e-1b3047c5dc0d","added_by":"auto","created_at":"2025-09-25 18:02:12","extension":"jpg","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":898754,"visible":true,"origin":"","legend":"\u003cp\u003eBinding affinity and complex stability of the IGF1R-morin. \u003cstrong\u003eA.\u003c/strong\u003e Ligand–protein interaction map (2D) between IGF1R (PDB- 5FXS) and morin. \u003cstrong\u003eB.\u003c/strong\u003e RMSD analysis of the IGF1R-morin complex over time (100 ns) \u003cstrong\u003eC.\u003c/strong\u003e Fluctuation analysis (RMSF) of Cα residues in IGF1R. \u003cstrong\u003eD.\u003c/strong\u003e Residue-level contact profile between IGF1R and morin. \u003cstrong\u003eE.\u003c/strong\u003e A time-resolved contact map of morin binding to IGF1R.\u003c/p\u003e","description":"","filename":"Picture12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7632832/v1/cc3eb059e17276ec54803641.jpg"},{"id":92204732,"identity":"d17d2bb7-c00b-4ec9-b0c7-28cb3c1c4303","added_by":"auto","created_at":"2025-09-25 18:10:12","extension":"jpg","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":1004007,"visible":true,"origin":"","legend":"\u003cp\u003eBinding affinity and complex stability of the ZAP70-morin. \u003cstrong\u003eA.\u003c/strong\u003e Ligand–protein interaction map (2D) between ZAP70 (PDB- 1U59) and morin. \u003cstrong\u003eB.\u003c/strong\u003e RMSD analysis of the ZAP70-Morin complex over time (100 ns) \u003cstrong\u003eC.\u003c/strong\u003e Fluctuation analysis (RMSF) of Cα residues in ZAP70. \u003cstrong\u003eD.\u003c/strong\u003e Residue-level contact profile between ZAP70 and morin. \u003cstrong\u003eE.\u003c/strong\u003e A time-resolved contact map of morin binding to ZAP70.\u003c/p\u003e","description":"","filename":"Picture13.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7632832/v1/05e16950e4ea86599dad2247.jpg"},{"id":92203392,"identity":"363f0697-659e-4a51-97b1-d3ff853e948c","added_by":"auto","created_at":"2025-09-25 17:46:12","extension":"jpg","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":990540,"visible":true,"origin":"","legend":"\u003cp\u003eBinding affinity and complex stability of the ERBB4-morin. \u003cstrong\u003eA.\u003c/strong\u003e Ligand–protein interaction map (2D) between ERBB4 (PDB- 3BBT) and morin. \u003cstrong\u003eB.\u003c/strong\u003e RMSD analysis of the ERBB4-morin complex over time (100 ns) \u003cstrong\u003eC.\u003c/strong\u003e Fluctuation analysis (RMSF) of Cα residues in ERBB4. \u003cstrong\u003eD.\u003c/strong\u003e Residue-level contact profile between ERBB4 and morin. \u003cstrong\u003eE.\u003c/strong\u003e A time-resolved contact map of morin binding to ERBB4.\u003c/p\u003e","description":"","filename":"Picture14.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7632832/v1/f0432859ea7ded7592d5a6f4.jpg"},{"id":92204323,"identity":"bff31a5e-8401-49f5-9375-9482b52b0d3f","added_by":"auto","created_at":"2025-09-25 18:02:12","extension":"jpg","order_by":15,"title":"Figure 15","display":"","copyAsset":false,"role":"figure","size":1011094,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA. \u003c/strong\u003ePhysicochemical Properties assessment by Swiss ADME. \u003cstrong\u003eB.\u003c/strong\u003e LD\u003csub\u003e50\u003c/sub\u003e and toxic class prediction. \u003cstrong\u003eC.\u003c/strong\u003e Radar chart showing compound toxicity prediction.\u003c/p\u003e","description":"","filename":"Picture15.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7632832/v1/91aa3063976a56742fb36660.jpg"},{"id":92204734,"identity":"a9d9a934-8852-4e67-817b-8627836f4fe1","added_by":"auto","created_at":"2025-09-25 18:10:12","extension":"png","order_by":16,"title":"Figure 16","display":"","copyAsset":false,"role":"figure","size":21007,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of morin on the viability of AGS gastric cancer cells after 24 hours of treatment.\u003cbr\u003e\nAGS cells were treated with various concentrations of morin for 24 hours, and cell viability was assessed using the MTT assay. Data are expressed as mean ± SEM from three independent experiments (n = 3).\u003c/p\u003e","description":"","filename":"Picture16.png","url":"https://assets-eu.researchsquare.com/files/rs-7632832/v1/05d722a6f043637993058fb2.png"},{"id":92203395,"identity":"f6164bdd-306c-4d66-b558-81133eaaed42","added_by":"auto","created_at":"2025-09-25 17:46:12","extension":"jpg","order_by":17,"title":"Figure 17","display":"","copyAsset":false,"role":"figure","size":593679,"visible":true,"origin":"","legend":"\u003cp\u003eOverall\u003cstrong\u003e \u003c/strong\u003emechanistic insights into the anti-cancer potential of morin in GC [37, 38].\u003c/p\u003e","description":"","filename":"Picture17.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7632832/v1/39ef5c078d82fdb6ddff170d.jpg"},{"id":106809181,"identity":"eb9986d8-00cc-4093-a7dc-50064355efc6","added_by":"auto","created_at":"2026-04-13 16:07:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":13009461,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7632832/v1/fc8775db-5a5e-4aaf-9bdc-e939313290e9.pdf"},{"id":92204729,"identity":"e9ec674e-70d4-46e1-a061-641046d67420","added_by":"auto","created_at":"2025-09-25 18:10:12","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":3240471,"visible":true,"origin":"","legend":"","description":"","filename":"2SupplementaryMorin20.07.25.docx","url":"https://assets-eu.researchsquare.com/files/rs-7632832/v1/c58eedf37feb85da4d034cb2.docx"},{"id":92203370,"identity":"70cb47c7-aac1-417f-b92a-92fa9330f982","added_by":"auto","created_at":"2025-09-25 17:46:12","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":142485,"visible":true,"origin":"","legend":"","description":"","filename":"GRAPHICALABSTRACT.png","url":"https://assets-eu.researchsquare.com/files/rs-7632832/v1/01c55c36f5ad4d44ff41f451.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Morin Modulates Key Targets and Pathways Associated with Gastric Cancer: Network Pharmacology, Molecular Docking, Molecular Dynamics, ADMET, and In‑Vitro Analysis","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAmong all non-communicable diseases, cancer comes after cardiovascular diseases in terms of cause of death. Cancer affecting the stomach, medically termed as gastric cancer (GC), is the fifth most prevalent kind of cancer that is ranked among top four leading contributors to death due to cancer [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The eastern parts of Europe and Asia along with Central and South America are particularly vulnerable to stomach cancer. On the other hand, regions like New Zealand, Australia, and portions of Africa and North America are not at high danger [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The condition is affected by environmental and genetic factors and risk is rising with age. Factors such as biliary pancreatic reflux, chronic inflammation, atrophic gastritis, and \u003cem\u003eH. pylori\u003c/em\u003e infection are contributing to the onset of GC [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOver the past years, different advances have been achieved through chemotherapy, radiation, immunotherapy and surgery in the field of cancer. Chemotherapy is effective but often leads to unpleasant side effects like exhaustion, hair loss, bleeding, infections and gastrointestinal problems including nausea and constipation. Radiation treatment can also damage healthy tissue in the immediate region of a tumour. Although a promising and fast-developing treatment, immunotherapy varies greatly across people. It may not be helpful in many patients, particularly in those with immune-evasive tumours, and can have major immunological side effects in many organs. Although surgery is the mainstay for localised cancer and could lead to a cure, tumour size or location often limits it. Furthermore, surgery carries risks, extended recovery times, and might not be suitable for people in a poor health condition or with disseminated illness. These limitations highlight the necessity of more customised, less intrusive, directly targeted cancer therapies that are easier on the normal tissues but more difficult on the malignant ones [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Overall treatment options for cancer and their limitations are summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Humans have used a wide variety of natural foods to cure a wide range of illnesses for the last thousand years. These foods include fruits, flowers, plant roots and vegetables, which are correlated with a lower risk of cancer related deaths [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Bioactive substances including carotenoids, flavonoids, phenolic acids, lignans and stilbenes have been identified in these foods and may have a major impact in the treatment of disease and ailments [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Polyphenolic flavonoids are a category of biologically active substances that are naturally present in a wide variety of plant species. These substances are distinguished by their phenylbenzopyran framework, which is distinguished by over 8000 identified derivatives and six subclasses that depend on variances in their heterocyclic ring C. These subclasses include flavonols, flavanones, flavan-3-ols, flavones, isoflavones and anthocyanins [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eMorin was first documented in the year of 1830, which is a yellow bioactive pigment that occurs naturally as a flavonol. It is also referred to as 3,5,7,2\u0026prime;,4\u0026prime;-pentahydroxyflavone, Calico Yellow, Aurantica and morin hydrate. It is particularly common in fruits and plants belonging to the Rosaceae, Moraceae, and Fagaceae groups [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Morin was found in Osage orange (\u003cem\u003eMaclura pomifera\u003c/em\u003e), sweet chestnut (\u003cem\u003eCastanea sativa\u003c/em\u003e), old fustic (\u003cem\u003eMaclura tinctoria\u003c/em\u003e), white mulberry (\u003cem\u003eMorus alba\u003c/em\u003e L), jack fruit (\u003cem\u003eArtocarpus heterophyllus\u003c/em\u003e), bambangan (\u003cem\u003eMangifera pajang\u003c/em\u003e), figs (\u003cem\u003eChlorophora tinctoria)\u003c/em\u003e, guava (\u003cem\u003ePsidium guajava\u003c/em\u003e), apple skin (\u003cem\u003eMalus pumila\u003c/em\u003e), almond (\u003cem\u003ePrunus dulcis\u003c/em\u003e), and bambangan (\u003cem\u003eMangifera pajang\u003c/em\u003e). Apart from that, morin was found in a wide variety of natural foods and beverages including onions, red wine, seaweed, tea and coffee [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe specific biosynthesis pathway of morin is unknown but anticipated that it is following the conventional flavonoid biosynthesis pathway named shikimate pathway. It is initiated from L-phenylalanine, converted into 4-coumarate: CoA with the help of phenylalanine ammonia-lyase (PAL). With the help of chalcone synthase (CHS), one of the chalcone derivative 2',4,4',6'-tetrahydroxychalcone formed. The enzyme Chalcone-flavanone isomerase (CHI) is responsible for the isomerisation of the chalcone intermediate, which results in the production of naringenin, a central flavanone. Finally, particular hydroxyl groups introduced by flavonoid 3\u0026prime;,5\u0026prime;-hydroxylase (FH) introduced particular hydroxyl groups to produce morin (3,5,7,2\u0026prime;,4\u0026prime;-pentahydroxyflavone) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the biosynthetic pathway of morin.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eResearchers have discovered that morin has several therapeutic properties, including antioxidant, antihypertensive, anti-inflammatory, antibacterial, antihyperlipidemic, antidiabetic, antiallergic, antihyperuricemic, antithrombotic, antiviral, and anticancer properties [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Morin exhibited numerous pharmacological activities by blocking phosphorylation and protein expression associated with key molecular pathways like Wnt/\u0026#120573;-catenin, Keap1/Nrf2, mTOR, JAKs/STATs, NF-қB and MAPK pathways [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Kyu-Shik Lee et al. (2021) reveal that morin can suppress HER2/EGFR signaling pathway across the various cell lines of breast cancer, resulting in apoptosis and hindering metastasis [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. According to Fakhredini et al. (2024), Morin facilitates the processes of autophagic and apoptotic cell death in human prostate cancer PC3 cells through modulation of the AMPK/ULK1/mTOR signaling pathway, highlighting its ability to control energy metabolism as well as apoptosis [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Morin also increases the effectiveness of cisplatin in ovarian carcinoma cells and apoptosis of melanoma cells [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Gao et al. (2022) showed that aloin has both anti-proliferative and pro-apoptotic actions on GC cells through the PI3K/AKT signaling pathway, utilizing a network pharmacology approach alongside in vitro experiments [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Huang et al. (2020) demonstrated the considerable cytotoxic effects of gentiopicroside, along with its capability to induce cell cycle arrest in GC cells through PI3K/AKT and p38 MAPK pathways, which was confirmed using bioinformatics and experimental assays [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Further research suggests that morin has significant anticancer properties across many tumour types. But research on morin's therapeutic benefits and mechanisms in GC is lacking.\u003c/p\u003e\u003cp\u003eBoth network pharmacology and molecular docking are emerging tools that are derived from the principles of computational biology, bioinformatics and analysis of molecular correlations derived from databases. These technologies are used for the purpose of discovering novel medications and predicting the targets that are associated with them [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConsequently, in order to address some of the gaps in the current literature, we want to thoroughly examine the underlying molecular processes of morin in the management of GC through insilco and invitro approaches. To our knowledge, this is one of the first studies to provide integrated network pharmacology and molecular dynamics insight into the mechanistic basis of morin\u0026rsquo;s anticancer effects in gastric cancer. Findings may maximise morin's therapeutic potential and provide fresh perspectives for the designing of innovative natural medication with anti-GC properties.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eExploration of morin-associated targets in GC\u003c/h2\u003e\u003cp\u003eThe PubChem platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was utilized to retrieve the 2D structure of the compound \u0026ldquo;Morin\u0026rdquo; (PubChem CID: 5281670), and that was used for the further step. We used the PharmMapper (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.lilab-ecust.cn/pharmmapper/\u003c/span\u003e\u003cspan address=\"http://www.lilab-ecust.cn/pharmmapper/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) tool to identify potential drug-related targets. The parameters, i.e., 300, and pharmacophore mapping were set to find out human protein targets only. The disease-related targets were retrieved using the keyword \u0026ldquo;Gastric cancer\u0026rdquo; with the help of two databases, i.e., GeneCards (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genecards.org/#\u003c/span\u003e\u003cspan address=\"https://www.genecards.org/#\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and Open Targets Platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://platform.opentargets.org/\u003c/span\u003e\u003cspan address=\"https://platform.opentargets.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). In some cases, the UniProt (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.uniprot.org\u003c/span\u003e\u003cspan address=\"https://www.uniprot.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) database was engaged to find out the official symbols of the target proteins. A venn analysis was done to find out the common targets between morin and gastric cancer. Venny 2.1.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bioinfogp.cnb.csic.es/tools/venny/\u003c/span\u003e\u003cspan address=\"https://bioinfogp.cnb.csic.es/tools/venny/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) platform was utilized for creating venn diagram.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eProtein-protein interaction (PPI) network construction and key targets screening\u003c/h3\u003e\n\u003cp\u003eWe used the Cytoscape app (version 3.10.1) for this purpose. In that stringApp (v2.1.1) was installed, and common genes were inserted for network construction. In the operating interface, only human (\u003cem\u003eHomo sapiens\u003c/em\u003e) data were considered and a full-string network was created with selected the confidence level and maximum additional interactions at \u0026ge;\u0026thinsp;0.9 and \u0026ge;\u0026thinsp;30 respectively. MCODE (v2.0.3) was used for the generation of clusters of a big network. To sort out the core composite targets, three crucial topological parameters, i.e., betweenness centrality (BC), degree centrality (DC) and closeness centrality (CC), were chosen in cytoHubba (v0.1). On the basis of these three parameters, we got ten genes each for every parameter and plotted them in a bar graph to extract the top ten hub genes.\u003c/p\u003e\n\u003ch3\u003eGene Ontology (GO) \u0026 KEGG pathway analysis\u003c/h3\u003e\n\u003cp\u003eUsing GO enrichment profiling, we make sense of the biological processes, activities and intracellular localization of enriched for a given set of genes. GO was assessed by using the database ShinyGo 0.80 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bioinformatics.sdstate.edu/go/\u003c/span\u003e\u003cspan address=\"http://bioinformatics.sdstate.edu/go/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) where the top ten hub genes were considered for assessment of cellular component (CCT), molecular function (MF) and biological process (BP) mainly associated with gastric cancer. For the purpose of the analysis, the following parameters were considered: the species was human, a cut-off value of 0.05 was set for false discovery rate (FDR), and the number of paths to show was set at 20. The Kyoto Encyclopaedia of Genes and Genomes (KEGG) Pathway Database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genome.jp/kegg/pathway.html\u003c/span\u003e\u003cspan address=\"https://www.genome.jp/kegg/pathway.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was utilized to conduct the pathway enrichment study related to gastric cancer.\u003c/p\u003e\n\u003ch3\u003eMolecular docking analysis\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eProtein preparation\u003c/h2\u003e\u003cp\u003eStructures of the target protein corresponding to the hub genes were collected using the RSCB PDB and UniProt. Protein IDs were selected considering certain features such as the X-ray crystallography resolution around 2.0 \u0026Aring; with monomer or dimer biological assembly. The structure needs to be in either an active or inactive conformation typically attached to an inhibitor with no mutations. The key information regarding selected proteins are compiled in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Then retrieved protein files were processed by the protein preparation wizard module of Schrodinger. Initially, the proteins' structures were prepared for further processing by bond order definition, introducing H atoms introduction, disulfide linkage construction, reconstruction of loops and missing chain, assigning bond orders and removing H\u003csub\u003e2\u003c/sub\u003eO molecules exceeding a distance of 5 \u0026Aring;. Furthermore, the pre-processed proteins were fine-tuned using PROPKA at pH:7 and the OPLS4 force field was utilised with optimum potentials to minimise it.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eLigand preparation\u003c/h2\u003e\u003cp\u003eFrom the PubChem database, the 2D structure of morin with the PubChem CID of 5281670 was downloaded in SDF format. Further ligand was processed by utilizing the Schr\u0026ouml;dinger\u0026rsquo;s LigPrep tool with OPLS4 force field. The ionization and computation methods were set as \u0026lsquo;Do not change\u0026rsquo; and \u0026lsquo;Determine chiralities from 3D structure\u0026rsquo;. A single low-energy conformer of the ligand was generated which was further used for in silico docking analysis.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eReceptor grid construction and ligand docking\u003c/h3\u003e\n\u003cp\u003eWithin the workspace grid box was generated via Schr\u0026ouml;dinger\u0026rsquo;s receptor grid generation wizard, guided by the native ligand coordinates. The dimensions of the bounding box were configured to resemble those of the workspace ligand and no restrictions were applied to any atoms inside the protein's binding pocket. After that docking was carried out with prepared proteins and ligand in XP (extra precision) mode applying a scaling factor and partial charge cutoff of 0.8 and 0.15, respectively. A blind docking strategy was conducted on those PDB Ids lacking of an active inhibitor binding site.\u003c/p\u003e\n\u003ch3\u003eMolecular dynamics\u003c/h3\u003e\n\u003cp\u003eAs a computer simulation tool, molecular dynamics (MD) examines the time-dependent physical motions of atoms which captures the dynamic behaviour of the atoms, including their vibrational, rotational, and translational movements. The docked complexes with a docking score of more than \u0026ndash; 8 kcal/mol are only considered for the dynamics study. The system was configured with the system builder panel in desmond of schrodinger\u0026rsquo;s academic version. Solvation was performed with the water model of SPC by applying the orthorhombic simulation box with a 10 \u0026Aring; distance on all sides. To ensure charge neutrality, sodium cation and chloride anions were incorporated at a final ionic strength of 0.15 M and subsequently recalculation was done. Molecular dynamics simulation was set up in the NPT ensemble mode where temperature and pressure were maintained at 310 K and 1.01325 bar, respectively. 100 ns molecular dynamics run was executed with storing output every 100 ps and an approximate frame count of 1,000 for subsequent analysis. Lastly, the simulation interaction diagrams were obtained which consist of protein-ligand root-mean square deviation (RMSD), root-mean square fluctuation (RMSF), and time-dependent protein-ligand contacts data of each complex. These data were further used to analyse the MD-simulation trajectory [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003ePhysicochemical properties and toxicity assessment of morin\u003c/h2\u003e\u003cp\u003eThe chemical structure of morin obtained through PubChem (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The drug-likeness, physicochemical, and toxicological properties of the molecule were evaluated utilized SwissADME (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.swissadme.ch/\u003c/span\u003e\u003cspan address=\"http://www.swissadme.ch/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and ProTox 3.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://tox.charite.de/\u003c/span\u003e\u003cspan address=\"https://tox.charite.de/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eCell Lines\u003c/h2\u003e\u003cp\u003eThe human gastric adenocarcinoma cell line AGS was procured from NCCS, Pune, India. It was cultured using complete media consisting of v-Nutrient Mixture F-12 Ham with 10% NuSera Serum replacement solution and 200 \u0026micro;g/ml antibiotic solution, which are purchased from HiMedia, Mumbai, India. AGS cells were propagated in T-25 flasks and incubated in a humidified incubator under the controlled conditions (37\u0026deg;C, 5% CO₂). The cell line was sub-cultured by enzyme digestion with 0.25% trypsin/1 mM EDTA when the cultures became\u0026ensp;about 70\u0026ndash;80% confluent. Morin was solubilised in DMSO to obtain a 20 mM mother stock and subsequently adjusted to desired concentrations using basal media.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eCell viability assay\u003c/h2\u003e\u003cp\u003eMTT assay was performed to evaluate cell viability. It relies on the colorimetric detection of purple coloured formazan transformed through viable cell metabolism from yellow tetrazolium salt. In a 96 well plate AGS cells were seeded at a density of 1\u0026times;10\u003csup\u003e4\u003c/sup\u003e cells per well in 100 \u0026micro;l of medium. The next day, after incubation, morin treatment was given at concentrations of 6.25, 12.5, 25, 50 and 100 \u0026micro;M for 24 hours. Subsequently, media was aspirated from each well and 10 \u0026micro;l of MTT (5 mg/ml) was included. The medium was then incubated for 4 hrs at 37\u0026deg;C. Once the MTT- supplemented media was discarded, the produced purple crystals of formazan were solubilized in 200 microlitres of dimethyl sulfoxide. Reading was taken with the help of microplate reader by setting wavelength at 570 nm (23, 24).\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eExploration of morin-associated targets in GC\u003c/h2\u003e\u003cp\u003eAfter removing the duplicates, overall, 294 morin-associated targets were isolated from PharmMapper. In a similar way, 242 and 13,898 targets of GC were retrieved by using the database of Open Targets Platform and GeneCards. Subsequently, the shared genes of morin and GC were screened out by constructing a venn diagram (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Specifically, 4 common targets in \u0026ldquo;PharmMapper\u0026rdquo; and \u0026ldquo;Open Targets Platform\u0026rdquo;, 62 common targets in \u0026ldquo;PharmMapper\u0026rdquo; and \u0026ldquo;GeneCards\u0026rdquo;, and 117 common targets in \u0026ldquo;PharmMapper\u0026rdquo;, \u0026ldquo;GeneCards\u0026rdquo; and \u0026ldquo;Open Targets Platform\u0026rdquo; were obtained. Overall, 183 unique overlapping targets are listed in Table S2.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003ePPI network construction and key targets screening\u003c/h2\u003e\u003cp\u003eWe imported the 183 common targets to the STRING database by using Cytoscape 3.10.1. A STRING network (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) formed with 213 nodes and 675 edges. With the help of MCODE, a total of eight clusters (Fig. S2) were generated which are listed in Table S3. Among all the clusters, cluster 1 had the highest score and was further considered for topological parameters analysis. By using cytoHubba, degree centrality (DC), closeness centrality (CC), and betweenness centrality (BC) were analyzed (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC, AND \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). The rank of the corresponding gene of all the topological parameters are listed in Table S4, S5 and S6. Finally, with a bar graph (Fig. S3) the top 10 hub genes are shorted out which are PIK3R3, PIK3CA, PIK3CB, PIK3CD, PIK3R2, PLCG1, JAK2, IGF1R, ZAP70 and ERBB4.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eGene Ontology \u0026amp; KEGG Pathway Analysis\u003c/h2\u003e\u003cp\u003eInvolving the top ten hub genes, enrichment analyses for GO and KEGG pathways were carried out via ShinyGO 0.80. The result showed that morin versus GC exhibited considerable enrichment in 1000 biological processes, 80 cellular components, and 104 molecular functions. Among the top 20 pathways of biological processes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), many are very enriched. For cell survival and proliferation, Phosphatidylinositol-3-phosphate biosynthetic process, phosphatidylinositol phosphate biosynthetic process and phosphatidylinositol 3-kinase are playing a crucial role. On another note, endothelial cell migration, ameboidal-type cell migration and cell motility and localization have a significant correlation with tumour spread and invasion. The analysis also highlights the role of transmembrane receptor protein tyrosine kinase signaling, enzyme-linked receptor protein signaling and regulation of kinase activity which are essential for cancer cell communication and signal transduction. Upon examining the foremost 20 pathways of cellular components (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), the most significantly augmented components include various classes of the phosphatidylinositol 3-kinase (PI3K) complex which are crucial in regulating cancer cell proliferation, metabolism, and viability through the PI3K-Akt signalling pathway. Moreover, insulin receptor complex, caveolae, and plasma membrane receptor complexes are involved in signal transduction, endocytosis, and metabolic control. After assessment of 20 pathways of molecular functions (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), it was found that various phosphatidylinositol kinase activities are most significantly enriched which are mainly associated with cell survival and proliferation. Additionally, functions like insulin receptor substrate binding suggest a link to metabolic dysregulation particularly via insulin signalling.\u003c/p\u003e\u003cp\u003eBased on the KEGG pathway analysis, the hub genes were highly enriched for 128 pathways. The top twenty pathways which have a high level of enrichment are displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. While examining the GC pathway (Fig. S4) very closely, it was found that the subclass of the PI3K gene (PIK3CA, PIK3CB, PIK3CD, PIK3R2 and PIK3R3) were mainly targeted by morin in two main pathways like PI3K-Akt signaling pathway (Fig. S5) and MAPK signaling pathway. In the above two mentioned pathways, morin also targets other genes, i.e., ERBB4, IGF1R and JAK2 in the PI3K-Akt signaling pathway and ERBB4 and IGF1R in MAPK signaling pathway.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eMolecular docking\u003c/h2\u003e\u003cp\u003eDocking assessment was performed involving the ligand morin on the top 10 hub genes. The molecular docking investigations indicated that morin had good binding affinities to a number of target proteins involved in gastric cancer. Lower (more negative) docking scores meant a higher binding affinity. The docking study outcomes revealed that the maximum and minimum docking scores are \u0026minus;\u0026thinsp;11.013 kcal/mol and 2.60 kcal/mol respectively. Docking scores higher than \u0026minus;\u0026thinsp;8 kcal/mol, showed strong binding strengths. Many protein-ligand combinations including PIK3CD (-11.013 kcal/mol), ZAP70 (-10.726 kcal/mol), JAK2 (-10.535 kcal/mol), IGF1R (-9.994 kcal/mol), PIK3CA (-9.790 kcal/mol), and ERBB4 (-8.836 kcal/mol) are some well-known finding cases. These values indicate that the proteins have strong binding affinity at their active sites and further validate via molecular dynamics stimulation. There were many different types of molecular interactions found in all protein ligand complexes which include hydrogen bonding, pi\u0026ndash;pi stacking, and pi\u0026ndash;cation interactions. Hydrogen bonding interaction is the majority among all interactions and it plays an important role in stabilizing the ligand inside the active binding sites. Specifically, Pi\u0026ndash;Pi stacking interactions were seen in the PIK3CD and PIK3CA complexes with aromatic residues TRP 760 and TRP 780 respectively. Only Pi\u0026ndash;cation interactions were found in the PIK3R3 complex with LYS 242. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e lists a comprehensive summary of the docking results and protein\u0026ndash;ligand 2D interaction profiles are depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eA, Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eA, Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eA, Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eA. Figure\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003eA, and \u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003eA.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDocking scores of morin with GC related proteins.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS. no\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTarget protein\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePDB ID\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eKey residues located within the active site\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eType of interaction\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDocking score (kcal/mol)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003ePIK3R3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e5ZUT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGLU 7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e-5.125\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eALA 56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eARG 14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLEU 221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLYS 242\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePi-Cation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003ePIK3CA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e8EXL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGLU 849\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e-9.790\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eVAL 851\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTRP 780\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePi\u0026ndash;Pi stacking\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePIK3CB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e\u003cp\u003eNo PDB ID found\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003ePIK3CD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e6PYR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eVAL 828\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e-11.013\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGLU 826\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLYS 779\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTRP 760\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePi\u0026ndash;Pi stacking\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePIK3R2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e7RNU\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eASP 337\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e-2.603\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eARG 340\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003ePLCG1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e7NXE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHIE 607\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e-6.597\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTHR 596\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSER 588\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGLU 589\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eJAK2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e4D1S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGLU 930\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e-10.535\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLEU 932\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePRO 933\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eIGF1R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e5FXS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMET 1082\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e-9.994\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGLU 1080\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eASP 1153\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGLN 1007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eZAP70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e1U59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eASP 479\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e-10.726\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eALA 417\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eERBB4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e3BBT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMET 774\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e-8.836\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eASP 836\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHydrogen bond\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eMolecular dynamics\u003c/h2\u003e\u003cdiv id=\"Sec20\" class=\"Section3\"\u003e\u003ch2\u003eJAK2 (PDB- 4D1S) and Morin\u003c/h2\u003e\u003cp\u003eThe protein RMSD (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eB) showed that there was a stable conformation from initial to 100 ns with minimal fluctuation between 0.942 and 2.84 \u0026Aring;. Ligand RMSD was more or less stable, and there is a continuous interaction of protein and ligand. At some points (0.3\u0026ndash;0.5, 1.1\u0026ndash;1.7, 22.1\u0026ndash;24.8, 72.2\u0026ndash;72.6, 73.8, 74.6\u0026ndash;75.1 ns), ligand RMSD is more than protein RMSD, but that is negligible. The vertical bars with a green colour indicate that the protein residues interact with the ligand (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eC). The residues which are in contact with the ligand, i.e., LEU 932, MET 929, GLY 856, TYR 931, LYS 857, ARG 980, ASP 994, PRO 933, GLY 858, GLU 930, VAL 863, SER 936, ARG 938, LYS 943, LEU 855, TYR 934, ASP 939, GLN 853, LEU 983, and ALA 880. Also, there is low fluctuation during contact. Overall, a protein RMSF value is less than 2.5 \u0026Aring;, indicating good stability. During molecular docking (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eA), morin formed hydrogen bonds with the GLU 930, LEU 932 and PRO 933 residues of JAK2. Further, molecular dynamic simulations (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eD \u0026amp; \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eE) promoted new significant binding contacts of morin with JAK2 residues LEU855 and ALA880.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003ePIK3CA (PDB- 8EXL) and Morin\u003c/h2\u003e\u003cp\u003eThe protein RMSD (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eB) initiates from 1.345 \u0026Aring; and gradually increases until 25 ns, then maintains a steady state up to 43.8 ns. Furthermore, scaling up was observed at 46.1 ns with the RMSD value of 4.362 \u0026Aring; and ended up with 3.249 \u0026Aring;. Ligand RMSD is more or less stable with a minimum of 0.476 \u0026Aring; and a maximum of 2.651 \u0026Aring;. The RMSD value of the ligand was less than the protein RMSD, which indicates the ligand was localized in its binding site throughout the stimulation period. Up to residue index 400, protein RMSF (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eC) was fluctuating, then stabilized for all residues except residues 730 and 804 with RMSF of 4.195 \u0026Aring; and 4.936 \u0026Aring;. There is minimal fluctuation during contact of ligand with protein. The residues which are in contact with the ligand, i.e., MET 922, ASP 810, MET 772, ILE 848, GLN 859, SER 773, PHE 934, THR 856, LYS 802, SER 774, ASP 805, TRP 780, VAL 851, ARG 770, ILE 800, GLU 849, ALA 775, TYR 836, SER 919, ILE 932, SER 854, and ASP 933. During molecular docking (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eA), morin interacted with PIK3CA by the formation of pi\u0026ndash;pi stacking with TRP 780 along with hydrogen bonding linked to VAL 851 and GLU 849. Further, molecular dynamic simulations (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eD \u0026amp; \u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eE) promoted new significant binding contacts between ILE 800, ILE 932, LYS 802, MET 922, ILE 848 and ASP 810 residues in PIK3CA and morin.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003ePIK3CD (PDB- 6PYR) and Morin\u003c/h2\u003e\u003cp\u003eIn the initial time, protein RMSD (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eB) was fluctuating, and after 25 ns, it was stabilized till 70 ns with the RMSD around 4 \u0026Aring;. Then it was again fluctuating and it ended up with 4.226 \u0026Aring;. Ligand RMSD was initiated from 0.671 \u0026Aring; and gradually increased. After 25 ns, it maintained a steady state until 70 ns, followed by a gradual decrease. This complex has the best docking score, but molecular dynamics simulations confirmed unstable ligand-protein interactions that deny morin\u0026rsquo;s binding stability. Throughout the stimulation period, protein RMSF (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eC) was fluctuating, but there was minimal fluctuation while it contacted the ligand with few exceptions. The residues which are in contact with the ligand, i.e., PHE 912, ASP 787, SER 842, MET 752, ASP 897, LYS 841, ILE 910, GLU 826, ILE 777, ASP 782, MET 900, TRP 760, VAL 828, THR 833, ASN 836, ARG 830, LYS 779, ASP 832, TYR 813, SER 754, ILE 825, VAL 827, SER 831, and ASP 911. Molecular docking (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eA) results showing that morin interacted with PIK3CD by the formation of pi\u0026ndash;pi stacking with TRP 760 and hydrogen bonds with VAL 828, GLU 826 and LYS 779 residues. Molecular dynamic simulations (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eD \u0026amp; \u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eE) promoted new binding contacts between ILE 777, SER 831, ASP 832M, MET 900 and ASP 911 residues of PIK3CD and morin.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003eIGF1R (PDB- 5FXS) and Morin\u003c/h2\u003e\u003cp\u003eThe starting protein RMSD (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eB) was 1.516 \u0026Aring; and fluctuated until 20 ns. Thereafter, it maintained a steady state around 3 \u0026Aring; with minimal deviation and ended up with 3.506 \u0026Aring;. From initial to 26.2 ns, ligand RMSD fluctuates between 0.452 \u0026Aring; and 2.453 \u0026Aring;. Then it reached around 3 \u0026Aring; and maintained stable conformation till the end, except for a deviation around 50 ns. The protein RMSF (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eC) was below 3 \u0026Aring; from the residue index 9 to 305, except for the range of 120 to 126. The residues which are in contact with the ligand, i.e., VAL 1013, GLU 1015, ALA 1031, LYS 1033, VAL 1063, MET 1079, GLU 1080, LEU 1081, MET 1082, THR 1083, ARG 1084, GLY 1085, ASP 1086, SER 1089, ARG 1139, MET 1142, ASP 1153, PHE 1154, GLY 1155, MET 1156, THR 1157, ILE 1160, and TYR 1161. Here the number of contacts between ligand and protein is more. Molecular docking (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eA) results revealed that morin formed hydrogen bonds with MET 1082, GLU 1080, ASP 1153 and GLN 1007 residues of 5FXS. Further, molecular dynamic simulations (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eD \u0026amp; \u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eE) promoted new binding contacts between MET 1156 residues of 5FXS and morin.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003eZAP70 (PDB- 1U59) and Morin\u003c/h2\u003e\u003cp\u003eThe protein RMSD (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003eB) initiated from 1.11 \u0026Aring; and showed a stable confirmation until 60 ns. Then a gradual increase up showed around 3.5 \u0026Aring; and ended up with 3.095 \u0026Aring;. Ligand RMSD is fluctuating throughout the stimulation period. Around 80 ns, it was deviated more and reached around 3 \u0026Aring;. Up to 60 ns, the RMSD of the ligand is more than the RMSD of the protein in most of the cases that indicate the ligand drifted away from the binding pocket. There is minimal fluctuation while the ligand and protein come into contact, and it is below RMSF 2 \u0026Aring; (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003eC). The residues which are in contact with the ligand, i.e., PHE 349, ASN 466, GLY 420, LEU 344, LYS 369, GLU 343, CYS 346, VAL 352, GLU 415, GLY 419, PRO 421, SER 478, MET 414, ARG 465, ASP 479, GLU 386, ASN 348, VAL 467, PHE 480, LYS 424, ALA 367, GLY 418, LEU 468, GLN 354, and ALA 417. A 2D diagram of molecular docking (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003eA) revealed that morin formed hydrogen bonds with the ASP 479 and ALA residues of ZAP70. Molecular dynamic simulations (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003eD \u0026amp; \u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003eE) promoted new binding contacts between LEU 344, GLU 415, ARG 465 and SER 478 residues in ZAP70 and morin.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003eERBB4 (PDB- 3BBT) and Morin\u003c/h2\u003e\u003cp\u003eThe protein RMSD (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003eB) starts from 1.226 \u0026Aring; and rapidly fluctuates till 68 ns, indicating changes in the structural conformation. After that, it stabilised at around 5 \u0026Aring;. Ligand RMSD has a minimum of 0.41 \u0026Aring; and a high of 2.327 \u0026Aring;, making it relatively stable. A lower ligand RMSD than that of the protein suggests that the ligand remained at its binding site during the stimulation period. There is not much variation when the ligand and protein come into contact, and it is below 1.6 \u0026Aring; (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003eC). The residues which are in contact with the ligand, i.e., GLN 772, LYS 709, THR 835, LEU 825, ALA 724, GLU 781, HIS 776, GLY 700, VAL 707, LEU 699, CYS 778, MET 774, THR 771, SER 701, ARG 822, GLY 777, PRO 775, ASP 836, LEU 769, and ASN 823. During molecular docking (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003eA), morin formed H-bonds with the MET 774 and ASP 836 residues of ERBB4. Molecular dynamic simulations (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003eD \u0026amp; \u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003eE) promoted new binding contacts between GLN 722, GLU 781, ARG 822 and ASN 823 residues of ERBB4 and morin.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\u003ch2\u003ePhysicochemical properties and toxicity assessment of morin\u003c/h2\u003e\u003cp\u003eThe ADME information of morin was retrieved from SwissADME and shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e15\u003c/span\u003eA. Morin is a drug-like compound which is freely soluble in water with moderate lipophilicity (iLOGP 1.47) property. It is rapidly absorbed through the gastrointestinal tract and poorly permeable to the blood-brain barrier. Apart from this, it also follows Lipinski's rule of five. Morin\u0026rsquo;s toxicity profile was evaluated using the ProTox-II (version 3.0) platform, and the report predicted that morin comes under toxicity class V, which implies it may be harmful if swallowed (2000\u0026thinsp;\u0026lt;\u0026thinsp;LD₅₀ \u0026le; 5000 mg/kg), with a lethal dose (LD₅₀) of 3919 mg/kg (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e15\u003c/span\u003eB). It has a moderate safety profile with selective organ-specific hazards, according to projections of organ toxicity. Morin is active for nephrotoxicity and respiratory toxicity but inactive for hepatotoxicity, carcinogenicity, cardiotoxicity and neurotoxicity (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e15\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePhysicochemical Properties of Morin\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ePhysicochemical Properties\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFormula\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC\u003csub\u003e15\u003c/sub\u003eH\u003csub\u003e10\u003c/sub\u003eO\u003csub\u003e7\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMolecular weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e302.24 g/mol\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNum. heavy atoms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNum. arom. heavy atoms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNum. rotatable bonds\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNum. H-bond acceptors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNum. H-bond donors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMolar Refractivity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e78.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLipophilicity\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLog Po/w (iLOGP)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWater Solubility\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLog\u0026nbsp;\u003cem\u003eS\u003c/em\u003e\u0026nbsp;(ESOL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-3.16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSolubility\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.11e-01 mg/ml; 6.98e-04 mol/l\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClass\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSoluble\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePharmacokinetics\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGI absorption\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBBB permeant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCYP1A2 inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCYP2C19 inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCYP2C9 inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCYP2D6 inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCYP3A4 inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLog\u0026nbsp;\u003cem\u003eK\u003c/em\u003e\u003csub\u003ep\u003c/sub\u003e\u0026nbsp;(skin permeation)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-7.05 cm/s\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDruglikeness\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLipinski\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\u003ch2\u003eCell viability\u003c/h2\u003e\u003cp\u003eThe cytotoxic effect of morin on the AGS cell line was evaluated using the MTT assay. Cells were cultured and exposed to the morin with the concentration of 3.125\u0026ndash;100 \u0026micro;M. After 24 hrs of treatment with morin, viable cell count decreased in a concentration-dependent manner. The IC\u003csub\u003e50\u003c/sub\u003e value (Fig.\u0026nbsp;\u003cspan refid=\"Fig16\" class=\"InternalRef\"\u003e16\u003c/span\u003e) was found to be 78.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8 \u0026micro;M (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eNatural products have been renowned for millennia and have established themselves as a rich and reliable source of therapeutic agents due to their availability and lower adverse effects compared to chemotherapeutic drugs [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. As stated in Pratas et al. (2024), apigenin is a naturally occurring flavonoid that exerts anti-GC activity by blocking cellular growth and causing apoptosis through the Akt/Bad/Bcl2/Bax-associated mitochondrial pathway [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In a separate study, Wang et al. (2023) showed that astragalin flavonoid decreased cell survival, migration, and invasion, increased apoptosis, and suppressed the PI3K/AKT signaling pathway which leads to effective anti-tumor activity in GC [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Several studies have shown that morin has antiproliferative and apoptosis induction properties in several types of tumours including breast cancer, melanoma, colorectal cancer, lymphoblastic leukaemia, tongue squamous cell carcinoma, lung cancer, head and neck squamous carcinoma, ovarian cancer, prostate cancer, hepatocellular carcinoma, bladder cancer, multiple myeloma and mammary carcinogenesis [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The cellular and molecular mechanism of action of morin against GC is still unknown. Only one or two key targets cannot reveal the actual underlying mechanism of action. So, utilising network pharmacology analysis, we can identify complex interactions between various pathways and key targets of morin on GC. This study aims to anticipate the key targets of morin associated with various pathological pathways of GC by in silico study and further validate them by in vitro experiments.\u003c/p\u003e\u003cp\u003eInitially, we identified 183 common target genes between morin and GC from various databases. Then, the PPI network was constructed in the cytposcape platform and the top 10 hub genes were sorted depending upon the topological parameters rank. Among the ten hub genes, five are coming under PI3K class (PIK3R3, PIK3CA, PIK3CB, PIK3CD, PIK3R2) and the others are PLCG1, JAK2, IGF1R, ZAP70 and ERBB4. It was found that morin predominately targets the PI3K-Akt signaling pathway and MAPK signaling pathway after analysis of the KEGG pathway related to gastric cancer. Morin mainly targets the upstream and downstream molecules of the PI3K-AKT cascade. Latest findings have shown that the PI3K-AKT axis has a significant impact on the processes of cell survival, proliferation, migration and apoptosis in GC [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDocking analysis has shown that morin strongly binds to the critical target proteins, including PIK3CD (-11.01 kcal/mol), ZAP70 (-10.72 kcal/mol), JAK2 (-10.53 kcal/mol), IGF1R (-9.99 kcal/mol), PIK3CA (-9.79 kcal/mol), and ERBB4 (-8.83 kcal/mol). Further, molecular dynamics simulations validated that morin has good binding stability with proteins like PIK3CA, JAK2, and IGF1R by forming new interactions and minimal fluctuations over a 100 ns period.\u003c/p\u003e\u003cp\u003ePIK3CA mutations were infrequent, but amplification was highly prevalent in GC and\u0026ensp;it may be a predominant mechanism of PI3K/Akt activation in GC [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. JAK2 and the transmembrane tyrosine kinase receptor produced by the IGF1R gene are implicated mainly in physiological events like cellular proliferation and survival. It is necessary\u0026ensp;for subsequent triggering of PI3K/AKT/mTOR signaling cascade in GC [\u003cspan additionalcitationids=\"CR33 CR34\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Shutting off the PI3K/AKT signaling pathway efficiently reduces mTOR function. As noted by Wang et al. (2023), the pathway\u0026rsquo;s inhibition leads to the activation of proapoptotic factors like Bax and caspase-9 [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Furthermore, Morgos et al. (2024) mentioned that blocking PI3K/AKT signaling results in the downstream inhibition of mTOR activity, thus eliminating survival signals and inducing apoptosis in GC cells by triggering mitochondrial pro-apoptotic pathways [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDrug-likeness evaluation showed that morin has good pharmacokinetic properties and low toxicity so that it\u0026ensp;could be a potential drug candidate. Concurrently, in vitro assays were conducted to support the findings of the in-silico study and elucidate the mechanisms of action of morin against GC. In vitro cell viability assay also confirmed the antiproliferative property of morin against the GC cell line. Although the IC\u003csub\u003e50\u003c/sub\u003e value is moderate (84.17\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2 \u0026micro;M), it aligns with the general range of natural flavonoids and provides a rationale for the future to design more active semi-synthetic derivatives or to use them in combination with existing chemotherapeutic drugs.\u003c/p\u003e\u003cp\u003eOur study is limited due to the absence of mechanistic exploration beyond cytotoxicity and in vivo validation. Further studies are needed to explore apoptotic markers, cell cycle regulation, and the compound\u0026rsquo;s efficacy in xenograft gastric tumor models. In addition, evaluation of combination strategies with standard chemotherapeutics such as 5-FU or cisplatin could uncover synergistic potential and improve clinical relevance.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn summary, the present study provided the mechanistic insight into the anti-cancer potential of the natural flavonoid morin in GC. In this present study, we identify some key targets of morin against GC by employing network pharmacology analysis. From KEGG pathway analysis it was revealed that morin mainly targets the PI3K-AKT axis in GC pathophysiology. Furthermore, supreme targets (PIK3CA, JAK2, and IGF1R) were summarized depending upon the binding affinity and stability from molecular docking and dynamics analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig17\" class=\"InternalRef\"\u003e17\u003c/span\u003e). In vitro cell viability assay also revealed that morin produces concentration-dependent cytotoxicity on the AGS cell line. Network pharmacology, molecular docking, molecular dynamics and MTT assay along with ADME and toxicity analysis also showed its favourable pharmacokinetic profile and low predicted toxicity, making it a drug-like candidate. Our findings suggest that morin interferes with key oncogenic proteins in GC and can be considered a potential lead compound for further studies. This study primarily relies on databases to predict the targets. The main limitations are some of the targets may be overlooked and these databases are updated from time to time. Lastly, our findings need to be validated through more molecular-level in vitro and distinct in vivo experiments. Future experiments involving in vitro mechanistic studies (western blotting/RT PCR) and in vivo models will be essential to understand its complete anti-cancer mechanism and therapeutic relevance.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclarations Conflict of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThe authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through the Small Research Project under grant number RGP1/149/46. This research work was supported by a University Seed Grant from Amrita Vishwa Vidyapeetham, Kochi.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eN.N. wrote the main manuscript, prepared the figures, and performed the investigation. S.S. carried out data curation, formal analysis, validation and software. B.M. contributed to supervision and software. N.M. contributed to funding acquisition and investigation. S.S. and U.K.R. contributed to concept discussion and writing. M.K.J. contributed to conceptualisation, methodology, funding acquisition, and supervision. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through the Small Research Project under grant number RGP1/149/46.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe authors declare that the data supporting the findings of this study are available within the paper and its Supplementary Information files. Should any raw data files be needed in another format, they are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, et al (2021) Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 71:209\u0026ndash;249. https://doi.org/10.3322/caac.21660\u003c/li\u003e\n\u003cli\u003eRawla P, Barsouk A (2019) Epidemiology of gastric cancer: global trends, risk factors and prevention. Gastroenterology Review 14:26\u0026ndash;38. https://doi.org/10.5114/pg.2018.80001\u003c/li\u003e\n\u003cli\u003eAng T, Fock K (2014) Clinical epidemiology of gastric cancer. 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Arch Pharm Res 42:531\u0026ndash;542. https://doi.org/10.1007/s12272-019-01158-5\u003c/li\u003e\n\u003cli\u003eGao J, Yang S, Xie G, et al (2022) Integrating Network Pharmacology and Experimental Verification to Explore the Pharmacological Mechanisms of Aloin Against Gastric Cancer. Drug Des Devel Ther Volume 16:1947\u0026ndash;1961. https://doi.org/10.2147/DDDT.S360790\u003c/li\u003e\n\u003cli\u003eHuang Y, Lin J, Yi W, et al (2020) Research on the Potential Mechanism of Gentiopicroside Against Gastric Cancer Based on Network Pharmacology. Drug Des Devel Ther Volume 14:5109\u0026ndash;5118. https://doi.org/10.2147/DDDT.S270757\u003c/li\u003e\n\u003cli\u003eQu Y, Yang X, Li J, et al (2021) Network Pharmacology and Molecular Docking Study of Zhishi-Baizhu Herb Pair in the Treatment of Gastric Cancer. Evidence-Based Complementary and Alternative Medicine 2021:1\u0026ndash;18. https://doi.org/10.1155/2021/2311486\u003c/li\u003e\n\u003cli\u003eDagar N, Jadhav HR, Gaikwad AB (2025) Network pharmacology combined with molecular docking and dynamics to assess the synergism of esculetin and phloretin against acute kidney injury-diabetes comorbidity. Mol Divers 29:1\u0026ndash;19. https://doi.org/10.1007/s11030-024-10829-5\u003c/li\u003e\n\u003cli\u003eShrivastava S, Jeengar MK, Thummuri D, et al (2017) Cardamonin, a chalcone, inhibits human triple negative breast cancer cell invasiveness by downregulation of Wnt/\u0026beta;‐catenin signaling cascades and reversal of epithelial\u0026ndash;mesenchymal transition. 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Biomedicine \u0026amp; Pharmacotherapy 172:116251. https://doi.org/10.1016/j.biopha.2024.116251\u003c/li\u003e\n\u003cli\u003eWang Z, Lv J, Li X, Lin Q (2021) The flavonoid Astragalin shows anti‐tumor activity and inhibits PI3K/AKT signaling in gastric cancer. Chem Biol Drug Des 98:779\u0026ndash;786. https://doi.org/10.1111/cbdd.13933\u003c/li\u003e\n\u003cli\u003eFang W-L, Huang K-H, Lan Y-T, et al (2016) Mutations in PI3K/AKT pathway genes and amplifications of PIK3CA are associated with patterns of recurrence in gastric cancers. Oncotarget 7:6201\u0026ndash;6220. https://doi.org/10.18632/oncotarget.6641\u003c/li\u003e\n\u003cli\u003eMatsuoka T, Yashiro M (2014) The Role of PI3K/Akt/mTOR Signaling in Gastric Carcinoma. 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World J Gastroenterol 21:2949. https://doi.org/10.3748/wjg.v21.i10.2949\u003c/li\u003e\n\u003cli\u003eHuang Y, Kang W, Ma Z, et al (2019) NUCKS1 promotes gastric cancer cell aggressiveness by upregulating IGF-1R and subsequently activating the PI3K/Akt/mTOR signaling pathway. Carcinogenesis 40:370\u0026ndash;379. https://doi.org/10.1093/carcin/bgy142\u003c/li\u003e\n\u003cli\u003eGuo C, Chu H, Gong Z, et al (2021) HOXB13 promotes gastric cancer cell migration and invasion via IGF-1R upregulation and subsequent activation of PI3K/AKT/mTOR signaling pathway. Life Sci 278:119522. https://doi.org/10.1016/j.lfs.2021.119522\u003c/li\u003e\n\u003cli\u003eMorgos D-T, Stefani C, Miricescu D, et al (2024) Targeting PI3K/AKT/mTOR and MAPK Signaling Pathways in Gastric Cancer. Int J Mol Sci 25:1848. https://doi.org/10.3390/ijms25031848\u003c/li\u003e\n\u003cli\u003eCuesta C, Ar\u0026eacute;valo-Alameda C, Castellano E (2021) The Importance of Being PI3K in the RAS Signaling Network. Genes (Basel) 12:1094. https://doi.org/10.3390/genes12071094\u003c/li\u003e\n\u003cli\u003eLi X, Huang X, Chang M, et al (2024) Updates on altered signaling pathways in tumor drug resistance. Visualized Cancer Medicine 5:6. https://doi.org/10.1051/vcm/2024007\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"molecular-diversity","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"modi","sideBox":"Learn more about [Molecular Diversity](http://link.springer.com/journal/11030)","snPcode":"11030","submissionUrl":"https://submission.nature.com/new-submission/11030/3","title":"Molecular Diversity","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Gastric cancer, Morin, Network pharmacology, Molecular docking, Molecular dynamics, AGS cells","lastPublishedDoi":"10.21203/rs.3.rs-7632832/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7632832/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGastric cancer (GC), widely known as stomach cancer, is a critical health concern across the world. It ranks among the world’s five most common cancer types and is third in terms of fatalities from tumour disease. Natural products have been renowned for millennia and are highly reputable as a fashionable supply of therapeutic agents. Morin is a natural flavonoid found in a range of plants within the Rosaceae, Fagaceae, and chiefly Moraceae families. Network pharmacology, molecular docking, molecular dynamics simulations, and an in vitro cytotoxicity study were conducted. \u0026nbsp;We have identified the top 10 hub genes (PIK3R3, PIK3CA, PIK3CB, PIK3CD, PIK3R2, PLCG1, JAK2, IGF1R, ZAP70, ERBB4) from network pharmacology analysis. Further molecular docking analysis revealed that morin has high binding affinities to PIK3CD (-11.01 kcal/mol), ZAP70 (-10.72 kcal/mol), JAK2 (-10.53 kcal/mol), IGF1R (-9.99 kcal/mol), PIK3CA (-9.79 kcal/mol), and ERBB4 (-8.83 kcal/mol). Molecular dynamics simulations confirmed the binding stability of morin with proteins like JAK2, PIK3CA, and IGF1R. The MTT assay demonstrated a significant escalation in the cytotoxicity of AGS GC cells following treatment with higher concentrations of morin. From in silico study results, we identified key oncogenic targets of morin which mainly work through PI3K-Akt pathway of GC which can be used as a reference for further research. An in vitro cytotoxicity study revealed that morin effectively inhibits the proliferation of AGS GC cells.\u003c/p\u003e","manuscriptTitle":"Morin Modulates Key Targets and Pathways Associated with Gastric Cancer: Network Pharmacology, Molecular Docking, Molecular Dynamics, ADMET, and In‑Vitro Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-25 17:46:07","doi":"10.21203/rs.3.rs-7632832/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-06T00:17:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-05T17:37:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-04T14:29:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-03T17:19:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-27T13:07:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"100822238981788345320292709787903681951","date":"2025-09-19T10:36:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"46905593938641946664222207792517300840","date":"2025-09-18T06:40:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"28085908376552543841596714295087500122","date":"2025-09-17T13:00:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"338913467948204904202967124105876506807","date":"2025-09-17T11:48:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-17T11:08:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"45828699138082399359807631846515279508","date":"2025-09-17T11:02:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"145908452172964371820215304631800334136","date":"2025-09-17T10:49:23+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-17T10:34:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-17T09:43:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-17T08:22:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"Molecular Diversity","date":"2025-09-16T17:06:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"molecular-diversity","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"modi","sideBox":"Learn more about [Molecular Diversity](http://link.springer.com/journal/11030)","snPcode":"11030","submissionUrl":"https://submission.nature.com/new-submission/11030/3","title":"Molecular Diversity","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"06afe7a2-97c2-4884-b7e0-26bfec10ed09","owner":[],"postedDate":"September 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-13T16:04:24+00:00","versionOfRecord":{"articleIdentity":"rs-7632832","link":"https://doi.org/10.1007/s11030-026-11535-0","journal":{"identity":"molecular-diversity","isVorOnly":false,"title":"Molecular Diversity"},"publishedOn":"2026-04-10 15:58:52","publishedOnDateReadable":"April 10th, 2026"},"versionCreatedAt":"2025-09-25 17:46:07","video":"","vorDoi":"10.1007/s11030-026-11535-0","vorDoiUrl":"https://doi.org/10.1007/s11030-026-11535-0","workflowStages":[]},"version":"v1","identity":"rs-7632832","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7632832","identity":"rs-7632832","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}