Integrated computational analysis of myrcene as a dual JAK2/VEGFR2 inhibitor for cancer therapy

Integrated computational analysis of myrcene as a dual JAK2/VEGFR2 inhibitor for cancer therapy | 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 Integrated computational analysis of myrcene as a dual JAK2/VEGFR2 inhibitor for cancer therapy Cromwel Tepap Zemnou, Ramelle Ngakam This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8928128/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Cancer progression involves interconnected pathways, including angiogenesis mediated by VEGFR2 and proliferative signaling regulated by JAK2. Dual inhibition of these kinases represents a promising therapeutic strategy. In this study, we applied an integrated computational approach to evaluate myrcene, a natural monoterpene, as a potential dual JAK2/VEGFR2 inhibitor. Molecular docking revealed favorable binding within the ATP-binding pockets of VEGFR2 and JAK2, with scores of − 7.98 and − 8.31 kcal·mol⁻¹, respectively. Interactions were primarily stabilized by hydrophobic π-alkyl and π-sigma contacts, with selective hydrogen bonding observed in JAK2. Density functional theory (B3LYP/6-311G(d,p)) confirmed structural stability and a moderate HOMO-LUMO gap, supporting dispersion-driven interactions and occasional polar contacts. In 200-ns molecular dynamics simulations, the VEGFR2–myrcene complex exhibited lower ligand RMSD (1.16 Å) and higher hydrogen bond occupancy (2.10) than the JAK2 complex (RMSD 1.85 Å; hydrogen bonds 1.02), reflecting greater dynamic stability for VEGFR2. MM-GBSA analysis showed strongly favorable binding free energies for both targets (ΔG = − 26.09 kcal·mol⁻¹ for VEGFR2; ΔG = − 24.00 kcal·mol⁻¹ for JAK2), indicating that myrcene can form stable, energetically favorable complexes with both kinases. Collectively, these results support myrcene as a dual inhibitor, with pronounced VEGFR2 affinity and significant JAK2 engagement, highlighting its potential as a scaffold for the rational design of dual-target anticancer therapeutics. Myrcene Dual kinase inhibition JAK2 VEGFR2 Molecular docking Molecular dynamics simulation Cancer therapy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Cancer remains one of the leading causes of death worldwide, with an estimated 18.5–20 million new cases and approximately 9.7–10.4 million deaths reported annually in recent global assessments of cancer burden, making it the second leading cause of death globally after cardiovascular diseases [ 1 ], [ 2 ]. Tumor heterogeneity, acquired drug resistance, and dose-limiting toxicities often hinder treatment efficacy, leading to high mortality rates and treatment failure, even with significant advancements in conventional therapeutic approaches like chemotherapy, radiation, and targeted therapy. The development of novel treatment drugs with enhanced safety profiles and the ability to target several oncogenic pathways at once is now urgently needed due to these difficulties. Since it might possibly circumvent resistance mechanisms and produce synergistic effects by interfering with complementary signaling cascades necessary for tumor survival and development, multi-targeted therapy has become a particularly intriguing approach [ 3 ], [ 4 ]. Among the multiple molecular targets involved in cancer pathogenesis, the Vascular Endothelial Growth Factor Receptor 2 (VEGFR2) and Janus Kinase 2 (JAK2) play critical roles in tumor biology. VEGFR2 is the major angiogenic signaling mediator, regulating endothelial cell proliferation, motility, and survival, and hence plays a critical role in tumor neovascularization. Overexpression of VEGFR2 and its ligand VEGF has been seen in many solid tumors, including breast, colorectal, lung, and hepatocellular carcinomas, and is associated with a poor prognosis and metastatic potential [ 5 ], [ 6 ], [ 7 ], [ 8 ]. JAK2 also functions as a crucial node in the JAK/STAT signaling system, transducing signals from numerous cytokines and growth factors to regulate gene expression programs that govern cell proliferation, differentiation, and survival. Constitutive activation of JAK2, whether caused by activating mutations like JAK2V617F or by persistent upstream signaling, promotes abnormal cell proliferation and contributes to the progression of both hematological and solid tumors [ 9 ], [ 10 ]. Importantly, previous research has indicated extensive interaction between these pathways, with the VEGF/JAK2/STAT3 axis serving as a crucial signaling module in cancer progression [ 11 ], [ 12 ]. Recent research has shown that inhibiting VEGFR2 with medicines like Anlotinib has anti-tumor effects in part because it suppresses the JAK2/STAT3 pathway, underlining the therapeutic potential of targeting these kinases together [ 13 ], [ 14 ]. This functional connection provides a compelling rationale for the development of dual VEGFR2/JAK2 inhibitors that could disrupt both angiogenic signaling and direct tumor cell proliferation pathways, potentially leading to increased anti-cancer activity. Natural products have long been a rich source of therapeutic agents, accounting for over half of all licensed anticancer medicines. Terpenes, a large and structurally diverse family of plant secondary metabolites, have received substantial attention due to their wide range of biological activities, including anti-inflammatory, antioxidant, and anticancer effects. Monoterpenes in particular have been shown to exert antitumor activities by inducing apoptosis and cell cycle arrest, and by modulating oxidative stress in cancer cells [ 15 ], [ 16 ]. Myrcene (7-methyl-3-methylene-1,6-octadiene), a monoterpene prevalent in essential oils of plants such as hops, cannabis, and lemongrass, is a particularly promising option for drug development [ 17 ], [ 18 ]. Preclinical studies have shown that myrcene has anti-inflammatory, analgesic, and sedative activities, and growing data shows that it may have anticancer effects by modulating oxidative stress and apoptosis [ 19 ], [ 20 ], [ 21 ]. However, the molecular processes that underpin myrcene's potential anti-cancer effect, including its capacity to target critical oncogenic kinases, remain largely unexplored. Computational techniques and network pharmacology have transformed modern drug development by allowing for quick, cost-effective screening of putative therapeutic molecules before experimental confirmation [ 22 ]. Network pharmacology integrates biological data with computational predictions to map complex interactions between drugs, targets, and pathways, enabling the identification of multi-target effects and synergistic mechanisms within disease networks [ 23 ]. Molecular docking simulations can predict the binding modalities and affinities of small compounds to protein targets, providing atomic-level insights into ligand-receptor interactions [ 24 ]. Density functional theory simulations supplement docking research by revealing the electronic characteristics and chemical reactivity of compounds, such as frontier molecular orbital energies and molecular electrostatic potential distributions that regulate molecular recognition [ 25 ]. Molecular dynamics simulations go beyond static images by modeling the time-dependent behavior of protein-ligand complexes under physiological settings, evaluating conformational stability and contact persistence on nanosecond to microsecond timescales [ 26 ], [ 27 ]. Finally, MM-GBSA binding free energy calculations provide quantitative estimates of binding strength and determine the energetic contributions driving complex formation [ 28 ]. In this study, we used an integrated computational approach to assess the potential of myrcene as a dual inhibitor of VEGFR2 and JAK2. Molecular docking was used to predict binding affinities and interaction patterns with both targets, followed by DFT analysis to investigate myrcene's electrical characteristics and reactivity. Extensive 200 ns molecular dynamics (MD) simulations were used to evaluate the stability and conformational dynamics of myrcene-bound complexes, which were supplemented by MM-GBSA calculations to quantify binding free energies. This thorough in silico study seeks to reveal mechanistic insights into myrcene's potential anti-cancer activity and provide the groundwork for future experimental validation of this natural chemical as a lead for dual-targeted cancer therapy. 2. Methodology 2.1.Target Protein Selection and Preparation The three-dimensional crystal structures of Vascular Endothelial Growth Factor Receptor 2 (VEGFR2; PDB ID: 3WZD) and Tyrosine-Protein Kinase JAK2 (PDB ID: 6VNI) were obtained from the RCSB Protein Data Bank. These targets were chosen due to their important roles in tumor angiogenesis and cancer cell proliferation, making them clinically relevant for dual-target cancer therapy. Protein structures were created using BIOVIA Discovery Studio, which eliminated all crystallographic water molecules, heteroatoms, and co-crystallized ligands. To optimize the proteins for molecular docking simulations, polar hydrogen atoms were added, along with Gasteiger charges. The produced proteins were preserved in PDB format for future docking experiments. 2.2.Ligand Preparation The chemical structure of myrcene (PubChem CID: 31253) was extracted from the PubChem database in SDF format and translated to PDB format with OpenBabel (v2.4.0). The chemical was imported into Avogadro (v1.2.0) for geometric optimization, and the MMFF94 force field was used to minimize energy and find the lowest energy conformation. To perform docking simulations, the reduced ligand structure was stored in PDBQT format using AutoDock Tools (v1.5.7). 2.3. Molecular Docking and Interaction Analysis AutoDock 4.0 was used to determine the binding affinities and interaction modalities of myrcene with both targets. The docking grid boxes were defined to contain the full active sites, with size of 60 × 60 × 60 Å and grid spacing of 0.375 Å per protein. The grid box for VEGFR2 was focused on the ATP-binding pocket, whereas the grid for JAK2 was similarly constructed to encompass the active region of the kinase domain. Docking parameters were tuned using 300 population sizes, 27,000 generations, 1,000,000 assessments, and 100 Genetic Algorithm runs to achieve complete conformational sampling. Each protein-ligand complex's binding affinity was measured, and the optimal pose was chosen based on the lowest binding energy and most beneficial interaction patterns. BIOVIA Discovery Studio was used for post-docking analysis to detect and show critical chemical interactions between myrcene and both targets' active site residues, such as hydrogen bonds, hydrophobic contacts, and electrostatic interactions. 2.4. Protein–Protein Interaction (PPI) Network Construction and Functional Enrichment Analysis The STRING database ( https://string-db.org ) was used to generate protein–protein interaction (PPI) networks centered on VEGFR2 and JAK2. To characterize the functional relevance of the interacting proteins, Gene Ontology (GO) annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed within STRING to identify significantly enriched biological processes, molecular functions, cellular components, and signaling pathways associated with the VEGFR2 and JAK2 networks. 2.5. Density Functional Theory Analysis To examine Myrcene’s electronic characteristics and chemical reactivity, density functional theory (DFT) calculations were performed with Gaussian 16 using the Becke-3-Lee-Yang-Parr (B3LYP) hybrid functional and the 6-311G(d,p) basis set, an approach widely validated for predicting structural, electronic, and reactivity properties of small to medium-sized organic molecules. Geometry optimizations were carried out in the gas phase without symmetry constraints, and frequency calculations at the same level confirmed the absence of imaginary frequencies, ensuring that the optimized structure corresponds to a true local minimum on the potential energy surface. Frontier molecular orbital energies, encompassing the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO), were then used to calculate the HOMO–LUMO energy gap, which is a key predictor of chemical stability and reactivity [ 29 ]. Molecular electrostatic potential (MEP) maps were generated to visualize the charge distribution across the molecular surface, identifying regions of negative potential susceptible to electrophilic attack and regions of positive potential favoring nucleophilic interaction, thereby revealing potential interaction sites relevant to ligand binding [ 30 ]. 2.6. Molecular Dynamics Simulation Molecular dynamics simulations were performed for 200 ns using GROMACS 2023 [ 31 ]to assess the stability and conformational behavior of myrcene coupled to VEGFR2 and JAK2. The best-docked complexes served as the starting structures, with ligand topologies created by ACPYPE and ANTECHAMBER utilizing the Amber99 force field [ 32 ], [ 33 ]. To simulate physiological circumstances, each compound was dissolved in a TIP3P water box with a 10 Å buffer, neutralized with ions, and adjusted to 0.15 M NaCl concentration [ 34 ]. Energy was minimized using steepest descent and conjugate gradient techniques until forces were less than 1000 kJ·mol⁻¹·nm⁻¹. Systems were equilibrated for 200 ps each using NVT and NPT ensembles at 300 K and 1 bar, followed by 200 ns production runs with a 2 fs time step, SHAKE restrictions, and PME electrostatics [ 35 ]. Trajectory investigations included RMSD, RMSF, radius of gyration, SASA, hydrogen bonding, and principal component analysis to evaluate complex stability, flexibility, compactness, solvation, interaction persistence, and important conformational dynamics. 2.7. Binding Free Energy Calculations To evaluate myrcene's binding free energy with both targets, Molecular Mechanics with Generalized Born Surface Area calculations were performed on snapshots collected from the last 50 ns of the MD trajectories, which represented the simulation's stable phase. The binding free energy was estimated by subtracting the complex's free energy from the sum of the protein and ligand's free energies. The energy components included molecular mechanics energy (bonded, van der Waals, and electrostatic contacts), as well as solvation free energy (polar solvation using the Generalized Born model and non-polar solvation using the solvent-accessible surface area term). This approach yielded quantitative insights into the thermodynamic driving forces that underpin myrcene binding to both targets. 3. Results 3.1. Molecular Docking Analysis Molecular docking of myrcene against VEGFR2 (3WZD) and JAK2 (6VNI) exhibited high binding affinities for both targets, indicating possible dual-inhibitory activity (Table 1 ). Myrcene had a docking score of -7.98 kcal/mol for VEGFR2 and − 8.31 kcal/mol for JAK2. These data imply a significant binding potential similar to known kinase inhibitors, with somewhat higher affinity for JAK2. The three-dimensional structures of both targets are illustrated in Fig. 1 , with VEGFR2 colored orange and JAK2 colored forest green. Table 1 Molecular docking results of myrcene against VEGFR2 (3WZD) and JAK2 (6VNI). Compound PubChem ID Docking Score (kcal/mol) Myrcene 31253 3WZD (VEGFR2) 6VNI (JAK2) -7.98 -8.31 3.2. Protein-Ligand Interaction Analysis Detailed interaction profiling using BIOVIA Discovery Studio identified the critical chemical interactions that stabilize myrcene within the active regions of both protein targets (Fig. 2 ). Myrcene is stabilized predominantly by hydrophobic interactions, such as π-sigma and π-alkyl contacts. These interactions fix the ligand within the binding pockets. Other forms of interactions were detected, including salt bridges, π-cation interactions, unfavorable contacts, and hydrogen bonds (both conventional and carbon hydrogen bonds). Notably, in the JAK2-myrcene complex (PDB ID: 6VNI), hydrogen bonds were established with residues Pro1002 and Lys1005. These particular polar interactions are most likely responsible for the increased binding stability and may explain why the JAK2-myrcene complex has a higher binding affinity than the VEGFR2-myrcene complex. The combination of both strong hydrophobic interactions and stabilizing hydrogen bonds suggests that myrcene has a more favorable and long-lasting interaction profile in the JAK2 active region. 3.3. PPI network and functional enrichment analysis of VEGFR2 and JAK2 genes Analysis using the STRING database identified proteins showing direct or indirect interactions with VEGFR2 and JAK2. The JAK2 network comprised 58 nodes and 735 edges (average node degree = 25.3), indicating high connectivity among JAK2-associated proteins. The VEGFR2 network comprised 18 nodes and 96 edges (average node degree = 10.7). Protein–protein interaction (PPI) enrichment was highly significant (p < 1.0×10⁻¹⁶), suggesting the observed interactions are biologically meaningful rather than random. Subsequent functional enrichment analyses were performed to elucidate the biological relevance of the JAK2- and VEGFR2-associated networks in cancer. For the JAK2 network, GO enrichment analysis identified the top BP terms as positive regulation of STAT protein phosphorylation, type I interferon signaling pathway, and cellular response to virus. The leading MF terms included type I interferon receptor binding, cytokine receptor binding, and cytokine activity, while the main CC terms were nucleosome, chromatin, and nucleoplasm. KEGG pathway analysis revealed significant enrichment in the JAK–STAT signaling pathway, Hepatitis B, and cytosolic DNA-sensing pathway. For the VEGFR2 network, the top BP terms were calcium-mediated signaling, positive regulation of angiogenesis, and positive regulation of endothelial cell proliferation. The principal MF terms included calcium-dependent protein kinase C activity, inositol 1,4,5-trisphosphate-sensitive calcium-release channel activity, and ion channel regulator activity, whereas the most enriched CC terms were platelet dense tubular network membrane, sarcoplasmic reticulum membrane, and ryanodine receptor complex. KEGG pathway analysis demonstrated enrichment in the VEGF signaling pathway, GnRH signaling pathway, and proteoglycans in cancer. A statistical significance threshold of p < 0.05 was applied, with multiple-testing correction performed where applicable. Results are presented in Figs. 3 and 4 . 3.5. Density Functional Theory (DFT) Analysis DFT calculations at the B3LYP/6-311G(d,p) level provided detailed insights into the electronic structure and reactivity of Myrcene. The optimized geometry converged to a true minimum, as confirmed by the absence of imaginary frequencies, indicating a stable configuration suitable for interactions with protein targets. The HOMO and LUMO energies were calculated as − 0.276 and − 0.153 a.u., respectively, resulting in a HOMO–LUMO gap of 0.123 a.u., which suggests moderate chemical reactivity (Fig. 5 and Table 2 ). The relatively high HOMO energy indicates good electron-donating ability, while the LUMO energy reflects the potential for electron acceptance, supporting possible charge-transfer interactions with the kinase domains. Molecular electrostatic potential mapping revealed electron-rich regions around the conjugated double bonds, which may serve as preferential sites for electrophilic attack or hydrogen bond formation, while electron-deficient regions at the alkyl sites favor hydrophobic interactions. Additional computed descriptors, including chemical hardness (0.061 a.u.), chemical softness (8.196 a.u.⁻¹), chemical potential (0.171 Debye), electrophilicity (0.368 a.u.), maximum charge capacity (3.508), ionization energy (0.276 eV), electron affinity (0.153 eV), and dipole moment (− 0.214 a.u.), collectively indicate that Myrcene possesses balanced electronic characteristics, enabling both hydrophobic and selective polar interactions that are consistent with its favorable binding behavior observed in docking. Table 2. DFT-computed electronic and reactivity descriptors for the most stable isomer of Myrcene, including dipole moment (p), isotropic polarizability (α̃₀), HOMO–LUMO gap (ΔE_HL), chemical hardness (η), chemical softness (σ), chemical potential (μ), electrophilicity (ω), and maximum charge capacity (χ). Calculations were performed at the DFT/UB3LYP 6-311G level of theory. Parameters Myrcene Calculation Method UB3LYP Basis Set 6-311G Total Energy [a.u] -393.6237 E HOMO -0.276 E LUMO -0.153 (ΔE) [a.u] 0.123 (η) [a.u] 0.061 (δ) [a.u] -1 16.393 (χ) [a.u] 0.214 (Pi) [a.u] -0.214 (ω) [a.u] 0.368 (S) [a.u] -1 8.196 [ΔN max ] 3.508 (IE) [ev] 0.276 (EA) [ev] 0.153 (μ) [Debye] 0.171 [a.u]=atomic unit; [ev]=electron volts. 3.6. Molecular Dynamics Simulation Analysis To comprehensively assess the dynamic stability, conformational behavior, and interaction persistence of myrcene bound to VEGFR2 and JAK2, 200 ns all-atom molecular dynamics simulations were performed using GROMACS 2023. The stability and flexibility of both protein-ligand complexes were evaluated through backbone RMSD, residue-wise RMSF, radius of gyration (Rg), solvent-accessible surface area (SASA) and hydrogen bond (Hb) occupancy. Collectively, these parameters provide a robust assessment of structural integrity, compactness, and essential motions throughout the simulation trajectory. 3.6.1. Root Mean Square Deviation (RMSD) Ligand RMSD analysis was performed to evaluate the structural stability, positional retention, and equilibration behavior of myrcene within the binding pockets of VEGFR2 and JAK2 over the 200 ns molecular dynamics simulation. RMSD values were calculated relative to the initial docked conformations, providing insight into ligand mobility and binding stability throughout the trajectory. The VEGFR2–myrcene complex exhibited an average ligand RMSD of 1.16 Å, whereas the JAK2–myrcene complex showed a slightly higher average RMSD of 1.85 Å (Fig. 6 ). In both systems, myrcene underwent a short initial equilibration phase, followed by stable RMSD plateaus with minimal fluctuations for the remainder of the simulation. Notably, ligand RMSD values for both complexes remained well below the widely accepted 3.0 Å stability threshold for protein–ligand systems, indicating that myrcene remained stably anchored within the binding sites without undergoing significant displacement or reorientation. The comparatively lower ligand RMSD observed in the VEGFR2–myrcene complex suggests a more rigid and conformationally stable binding mode relative to JAK2. Nevertheless, both complexes demonstrate favorable dynamic stability, supporting the robustness of myrcene binding throughout the simulation period. 3.6.2. Root Mean Square Fluctuation (RMSF) Residue-wise RMSF analysis was conducted to examine local flexibility and identify protein regions influenced by ligand binding during the simulation. The VEGFR2–myrcene complex displayed an average RMSF of 1.69 Å, while the JAK2–myrcene complex exhibited an average RMSF of 1.61 Å (Fig. 6 ). In both systems, elevated fluctuations were primarily confined to the N-terminal and C-terminal regions, as well as surface-exposed loop segments, which are intrinsically flexible and distant from the binding sites. Crucially, residues within and surrounding the ligand-binding pockets showed markedly reduced fluctuations, indicating strong ligand-mediated stabilization of the active site regions. These observations confirm that myrcene binding restricts excessive local mobility, thereby preserving the functional architecture of both VEGFR2 and JAK2. 3.6.3. Radius of Gyration (Rg) The radius of gyration was analyzed to assess changes in protein compactness and overall folding stability upon ligand binding. The average Rg value for the VEGFR2–myrcene complex was 2.052 Å, while the JAK2–myrcene complex exhibited an average Rg of 2.0417 Å (Fig. 6 ). Both complexes maintained stable Rg profiles throughout the 200 ns simulation, with only minor oscillations. The absence of significant Rg fluctuations indicates that myrcene binding did not promote protein unfolding or large-scale structural expansion. Instead, both proteins retained their compact tertiary structures, further supporting the structural robustness of the complexes. 3.6.4. Solvent Accessible Surface Area (SASA) SASA analysis was performed to monitor changes in protein surface exposure and to detect potential unfolding or major conformational rearrangements during the simulation. The VEGFR2-myrcene complex exhibited an average SASA of 16,776.1 Ų, whereas the JAK2-myrcene complex showed an average SASA of 15,159.3 Ų (Fig. 6 ). SASA trajectories for both systems remained stable over time, with no abrupt increases indicative of solvent exposure due to structural destabilization. These findings suggest that myrcene binding does not significantly alter the solvent accessibility of either protein and that both complexes preserve their folded states throughout the simulation. 3.6.5. Hydrogen Bond Analysis Hydrogen bond analysis was conducted to evaluate the persistence and stability of intermolecular interactions between myrcene and both target proteins. The VEGFR2–myrcene complex formed an average of 2.10 hydrogen bonds, while the JAK2–myrcene complex maintained an average of 1.02 hydrogen bonds during the simulation (Fig. 6 ). Although myrcene is predominantly hydrophobic, the presence of persistent hydrogen bonds highlights favorable ligand accommodation within the binding pockets. The higher hydrogen bond occupancy observed in the VEGFR2 complex may partially explain its lower RMSD and enhanced stability compared to the JAK2 complex, indicating a more optimal interaction network. 3.7. Binding Free Energy Calculations (MM-GBSA) MM-GBSA analysis revealed substantial differences in the thermodynamic profiles governing myrcene binding to VEGFR2 and JAK2 (Table 3 ). The VEGFR2–myrcene complex exhibited a strongly favorable binding free energy (ΔG = − 26.09 kcal·mol⁻¹), dominated by a pronounced enthalpic contribution (ΔH = − 41.78 kcal·mol⁻¹). The relatively modest entropic penalty (− TΔS = 15.69 kcal·mol⁻¹) indicates limited loss of conformational freedom upon binding, consistent with a compact and well-stabilized interaction. The low standard deviation and SEM values further support good convergence of the MD trajectories and the robustness of the calculated energetics for this complex. In contrast, although the JAK2–myrcene complex also displayed a favorable binding free energy (ΔG = − 24.00 kcal·mol⁻¹), its thermodynamic signature differed markedly. Binding to JAK2 was characterized by a strongly favorable enthalpic term (ΔH = − 39.74 kcal·mol⁻¹), comparable in magnitude to that observed for VEGFR2; however, this gain was accompanied by a larger entropic penalty (− TΔS = 15.74 kcal·mol⁻¹). The elevated SD and SEM values for the JAK2 complex suggest increased conformational variability and reduced stability of myrcene within the binding pocket, indicating that the favorable enthalpy arises from transient or less optimally retained interactions. Table 3 MM-GBSA Binding Energy Components of VEGFR2-Myrcene and JAK2-Myrcene Complexes Complex Parameter ΔH (kcal·mol⁻¹) −TΔS (kcal·mol⁻¹) ΔG (kcal·mol⁻¹) VEGFR2–Myrcene Average −41.78 15.69 −26.09 SD 3.59 0.12 3.59 SEM 0.05 0.00 3.59 JAK2–Myrcene Average −39.74 15.74 −24.00 SD 5.15 5.85 7.79 SEM 0.34 0.38 7.79 4. Discussion This study paint a consistent and mechanistically coherent picture of myrcene as a bioactive monoterpene whose physicochemical properties and binding behavior confer clear, therapeutically relevant engagement with kinase targets most notably VEGFR2 with secondary, context-dependent compatibility with JAK2. Molecular docking established that myrcene can be accommodated within the ATP-binding pockets of both VEGFR2 and JAK2, producing energetically favorable poses (docking scores − 7.98 and − 8.31 kcal/mol, respectively) that justify further, higher-resolution interrogation. Previous studies indicate that docking scores below − 5.0 kcal/mol generally reflect strong binding affinity and stable protein–ligand interactions [ 29 ], [ 30 ], [ 31 ]. Post-docking interaction profiling clarified the nature of these engagements: myrcene’s binding is dominated by hydrophobic contacts (π-sigma and π-alkyl interactions) that tightly pack the ligand inside hydrophobic subpockets, while a limited set of polar contacts including hydrogen bonds in the JAK2 docked pose with Pro1002 and Lys1005 adds local stabilization. Thus, docking and interaction mapping together indicate that myrcene occupies chemically sensible binding modes in both kinases, with hydrophobic complementarity as the primary recognition motif and occasional polar anchoring that can modulate affinity. At the network level, our protein–protein interaction and pathway enrichment analyses situate VEGFR2 and JAK2 within distinct but biologically coherent signaling modules that are relevant to cancer pathophysiology. JAK2 is a central mediator of cytokine receptor signaling and downstream STAT activation, an axis that is frequently dysregulated in malignancies and implicated in processes such as proliferation, immune regulation, and angiogenesis. Constitutive activation of the JAK2/STAT3 pathway has been observed across diverse solid tumors and is associated with enhanced expression of angiogenic factors including VEGF and basic fibroblast growth factor (bFGF), as well as poorer clinical outcomes, reinforcing its role as a highly connected oncogenic signaling hub. Indeed, the JAK2/STAT3 axis promotes tumor angiogenesis and supports tumor-host interactions through modulation of both proliferative and immune-linked signaling pathways [ 12 ], [ 39 ]. In contrast, VEGFR2 is a principal receptor tyrosine kinase driving angiogenesis through direct mediation of vascular endothelial growth factor (VEGF) signals. Upon ligand binding, VEGFR2 undergoes dimerization and autophosphorylation, initiating downstream cascades that regulate endothelial cell proliferation, migration, and survival processes fundamental to neovascularization in tumoral contexts. The VEGF/VEGFR2 axis is widely recognized as a cornerstone of pathological angiogenesis in cancer and forms the basis for numerous anti-angiogenic therapeutic strategies [ 40 ], [ 41 ]. The distinct enrichment of JAK–STAT and cytokine signaling pathways around JAK2, compared with the angiogenesis and endothelial proliferation networks centered on VEGFR2, corroborates the biological plausibility of targeting these kinases concurrently in oncology. Whereas modulation of VEGFR2 would be expected to disrupt tumor blood vessel formation, interference with JAK2 signaling could exert broader effects on proliferative and immune-related processes. Together, these complementary mechanisms support the therapeutic rationale for dual-targeting strategies in cancer that aim to suppress both angiogenic and tumor-intrinsic oncogenic signaling. Quantum-chemical characterization via DFT provides mechanistic depth to the structural and network findings by revealing the intrinsic electronic properties that govern myrcene’s interactions with protein targets. Geometry optimization converged to a true minimum, as confirmed by frequency calculations, indicating a stable molecular configuration suitable for binding studies. The frontier molecular orbital analysis showed a HOMO–LUMO gap consistent with moderate chemical reactivity, enabling Myrcene to participate in weak charge-transfer interactions while primarily engaging through dispersion forces. Molecular electrostatic potential mapping localized electron-rich regions around the conjugated double bonds and areas of mild positive potential at alkylated sites. This distribution rationalizes why myrcene, although largely nonpolar, can achieve van der Waals and dispersion-driven stabilization within hydrophobic protein pockets, while still retaining the capacity for occasional, targeted polar interactions when appropriately oriented. These quantum-chemical descriptors thus complement the docking and MD results, explaining how myrcene’s electronic structure underpins both its preferential engagement with VEGFR2 and its limited, context-dependent compatibility with JAK2 [ 42 ]. By providing a detailed map of reactive sites and electronic distribution, DFT not only validates observed binding patterns but also informs rational modifications to enhance multi-target activity, particularly in regions where polar contacts could be introduced to improve JAK2 binding without disrupting VEGFR2 stabilization. Long-timescale molecular dynamics simulations combined with MM-GBSA free-energy decomposition offer decisive and integrative evidence for distinguishing target preference and elucidating the underlying binding mechanism beyond what static docking models can reveal. While docking scores provide a rapid, approximate ranking of ligand poses based on simplified scoring functions, they lack explicit accounting for solvent dynamics, protein flexibility, and entropic contributions inherent to physiological conditions. In contrast, extended MD sampling captures the dynamic evolution of the protein–ligand complex over hundreds of nanoseconds, enabling exploration of relevant configurational space and identification of stable binding modes that may not be apparent from a single snapshot alone [ 43 ], [ 44 ]. Subsequent MM-GBSA rescoring leverages an ensemble of equilibrated structures from the simulation trajectory to compute binding free energies by incorporating molecular mechanics energies and solvent contributions through implicit solvation models, and can improve affinity predictions relative to isolated docking scores [ 45 ]. Across the 200 ns molecular dynamics simulations, the VEGFR2–myrcene complex exhibited a lower average ligand RMSD of 1.16 Å, modest RMSF values for binding-site residues, a stable radius of gyration, and a consistent SASA profile, indicative of a compact and well-sequestered complex. Hydrogen-bond analysis revealed persistent interactions (≈ 2.10 H-bonds), complementing the hydrophobic packing and confirming stable ligand retention. MM-GBSA decomposition showed a strongly favorable overall binding free energy (ΔG ≈ − 26.09 kcal·mol⁻¹), dominated by a large negative enthalpy (ΔH ≈ − 41.78 kcal·mol⁻¹) with a moderate entropic penalty (− TΔS ≈ 15.69 kcal·mol⁻¹). These results indicate that Myrcene forms a highly stable and energetically favorable complex with VEGFR2, consistent with DFT-predicted electronic characteristics that support dispersion-driven and selective polar interactions. In addition, the JAK2–myrcene complex also displayed favorable binding energetics. Although ligand RMSD was slightly higher (1.85 Å) and hydrogen-bond occupancy lower (≈ 1.02 H-bonds), the MM-GBSA-calculated binding free energy (ΔG ≈ − 24.00 kcal·mol⁻¹) remains strongly negative. The enthalpic contribution (ΔH ≈ − 39.74 kcal·mol⁻¹) is comparable to VEGFR2, while the slightly higher entropic penalty (− TΔS ≈ 15.74 kcal·mol⁻¹) reflects modest conformational flexibility. These values indicate that Myrcene also binds favorably to JAK2, though with slightly reduced dynamic stability relative to VEGFR2. Taken together, the multi-tiered computational evidence supports the positioning of myrcene as a VEGFR2-centered lead scaffold with demonstrable potential for adjunctive JAK2 modulation. The concordance among docking geometry, interaction mapping, quantum-chemical descriptors, sustained MD stability, and strongly favorable MM-GBSA energetics for VEGFR2 provides a robust mechanistic rationale for pursuing myrcene-derived optimization toward anti-angiogenic therapeutics. At the same time, the observed, albeit weaker, engagement with JAK2 highlights an accessible chemical space for scaffold elaboration aimed at multi-target modulation: directed substitutions informed by DFT-derived electrostatic maps and MD-derived contact snapshots could introduce persistent polar anchors in the JAK2 pocket without sacrificing the dispersion-driven enthalpic benefits that underpin VEGFR2 binding. Overall, the results demonstrate a coherent and actionable pathway from molecular recognition to biological relevance, supporting further medicinal-chemistry and experimental follow-up to translate these in silico insights into preclinical candidates for cancer therapy 5. Conclusion This study provides a detailed computational evaluation of myrcene as a potential dual inhibitor of VEGFR2 and JAK2, which are important kinases implicated in cancer angiogenesis and proliferative signaling. Molecular docking identified energetically advantageous binding poses in both targets' ATP-binding pockets, which were predominantly sustained by hydrophobic contacts and selective hydrogen bonds. Quantum-chemical DFT research validated myrcene's structural stability, moderate HOMO-LUMO gap, and favorable electronic distribution, allowing for both dispersion-driven and occasional polar contacts within protein pockets. Extended MD simulations revealed that myrcene forms a compact, dynamically stable complex with VEGFR2 while preserving favorable binding energies with JAK2. MM-GBSA free-energy studies revealed energetically favorable interactions with both kinases, despite a modest decrease in dynamic stability with JAK2. Overall, these multi-tiered computational results place myrcene as a dual VEGFR2/JAK2 inhibitor, with a predominant preference for VEGFR2 and demonstrable involvement with JAK2. The findings provide a molecular foundation for further optimizing myrcene-derived scaffolds for multi-target anticancer therapies, as well as evidence for experimental validation in preclinical models. Declarations Funding This work was not supported by any funding or grant. Conflict of Interests The authors report there are no competing interests to declare. Authorship contributions Cromwel Tepap Zemnou: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Supervision, Resources, Writing – original draft, Writing – review & editing. Ramelle Ngakam: Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Data Availability Statement All data generated or analyzed during this study are included in this article. References F. Bray et al. , “Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries,” CA: A Cancer Journal for Clinicians , vol. 74, no. 3, pp. 229–263, 2024, doi: 10.3322/caac.21834. 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Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 10 May, 2026 Reviewers agreed at journal 01 Apr, 2026 Reviews received at journal 24 Mar, 2026 Reviewers agreed at journal 03 Mar, 2026 Reviewers agreed at journal 03 Mar, 2026 Reviewers invited by journal 02 Mar, 2026 Editor assigned by journal 21 Feb, 2026 Submission checks completed at journal 21 Feb, 2026 First submitted to journal 20 Feb, 2026 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8928128","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":599514134,"identity":"6d5ec554-aa2d-4538-9538-8d8c69000c77","order_by":0,"name":"Cromwel Tepap Zemnou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCklEQVRIiWNgGAWjYPCDChiDDZ8qZmTOGZK1MLYRoYW/gf/g44KaO/b8YmcPPuadd1jO4Pbhoxs+lDHImfcvwKpF4gAzs/GMY8+YJWfnJRvzbjtsbHAuLe3mjHMMxjI3HmDVYsDAzCbNw3aYzeB2jpk0UEvihjM8Zrd52xgSZ0gcwKWF/TfPv8M89mAtcw7Xg7X8xa+FjZm37bCEgTRIS8PhBAOQFkaQFv4G7H45zGwsPbPvmYHE7RxjwznH0g1nnmFLu9lzTsJYQgJHiLU3Pvxc8A0YYrNzDB+8qbGW5zvDfOzGjzIbOQl+7A4DRQsQYUoCrZBIwK6FAYcWkAtw2DIKRsEoGAUjDQAA6SBZg/MPU+wAAAAASUVORK5CYII=","orcid":"","institution":"EuroMed University of Fes (UEMF)","correspondingAuthor":true,"prefix":"","firstName":"Cromwel","middleName":"Tepap","lastName":"Zemnou","suffix":""},{"id":599514135,"identity":"69a95180-85ba-45e3-92db-c96bfc68b9d1","order_by":1,"name":"Ramelle Ngakam","email":"","orcid":"","institution":"University of Dschang","correspondingAuthor":false,"prefix":"","firstName":"Ramelle","middleName":"","lastName":"Ngakam","suffix":""}],"badges":[],"createdAt":"2026-02-20 17:38:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8928128/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8928128/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103817670,"identity":"301d3afe-626e-45e2-b21e-db2c9ae71ce3","added_by":"auto","created_at":"2026-03-03 09:27:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":311188,"visible":true,"origin":"","legend":"\u003cp\u003eSpace-filling representations of Vascular Endothelial Growth Factor Receptor 2 (PDB ID: 3WZD) and Tyrosine-Protein Kinase JAK2 (PDB ID: 6VNI) proteins colored orange and forest green respectively, analyzed using ChimeraX 1.9.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8928128/v1/21310ac79f73bb81e8822124.png"},{"id":103817667,"identity":"1672dc95-ab06-42c0-9601-929809d20f96","added_by":"auto","created_at":"2026-03-03 09:27:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":226876,"visible":true,"origin":"","legend":"\u003cp\u003eProtein-Ligand Interaction Analysis of Vascular Endothelial Growth Factor Receptor 2 (PDB ID: 3WZD) and Tyrosine-Protein Kinase JAK2 (PDB ID: 6VNI) targets with myrcene.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8928128/v1/28b31e11fbfb32d862ae4f56.png"},{"id":104401210,"identity":"ca8bd740-2a06-40c6-a525-b3ed020a7a40","added_by":"auto","created_at":"2026-03-11 12:12:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":498931,"visible":true,"origin":"","legend":"\u003cp\u003ePPI network and functional pathway enrichment analysis of JAK2. (A) PPI network of JAK2-interacting proteins identified using STRING. (B–D) GO enrichment analysis showing significantly enriched BP (B), MF (C), and CC (D). (E) KEGG pathway enrichment analysis of JAK2-associated genes (p \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8928128/v1/a7ac96b9bdf9c303122a2476.png"},{"id":104400726,"identity":"27d6484a-fdda-43be-882f-603925a382c2","added_by":"auto","created_at":"2026-03-11 12:10:49","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":392031,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePPI network and functional pathway enrichment analysis of VEGFR2 (KDR)\u003c/strong\u003e. (A) PPI network of VEGFR2-interacting proteins identified using STRING. (B–D) GO enrichment analysis showing significantly enriched BP (B), MF (C), and CC (D). (E) KEGG pathway enrichment analysis of VEGFR2-associated genes (p \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8928128/v1/d84f1ebd9e5bc2219d508c27.png"},{"id":103817669,"identity":"a5384b84-7a0a-4a21-8ecd-ac85cb18c948","added_by":"auto","created_at":"2026-03-03 09:27:54","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":146246,"visible":true,"origin":"","legend":"\u003cp\u003eDFT analysis of myrcene. (A) Optimized geometry of the most stable isomer of myrcene. (BIsosurfaces of the HOMO, LUMO and MEP mapped onto the total electron density of the most stable isomer. Isovalue for molecular orbitals: |0.02 a.u.|; isovalue for electron density: |0.0004 a.u.|\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8928128/v1/4916dc5c5354f3406c2f7eb5.png"},{"id":104400422,"identity":"8cb42262-16e0-4d2f-a3bb-a12f0ebaf99f","added_by":"auto","created_at":"2026-03-11 12:09:56","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":110621,"visible":true,"origin":"","legend":"\u003cp\u003eMD results over 200 ns for VEGFR2–myrcene and JAK2–myrcene complexes illustrating structural stability and conformational dynamics through RMSD, RMSF, Rg, hydrogen bonding, and SASA analyses.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8928128/v1/eaf238a041c21149414c5e0e.png"},{"id":104407961,"identity":"e735d5be-db9d-4e2b-bb06-3915a66777f9","added_by":"auto","created_at":"2026-03-11 12:41:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2622832,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8928128/v1/15d37591-eec0-4ad5-827b-3fe7a64fbf35.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrated computational analysis of myrcene as a dual JAK2/VEGFR2 inhibitor for cancer therapy","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCancer remains one of the leading causes of death worldwide, with an estimated 18.5\u0026ndash;20\u0026nbsp;million new cases and approximately 9.7\u0026ndash;10.4\u0026nbsp;million deaths reported annually in recent global assessments of cancer burden, making it the second leading cause of death globally after cardiovascular diseases [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Tumor heterogeneity, acquired drug resistance, and dose-limiting toxicities often hinder treatment efficacy, leading to high mortality rates and treatment failure, even with significant advancements in conventional therapeutic approaches like chemotherapy, radiation, and targeted therapy. The development of novel treatment drugs with enhanced safety profiles and the ability to target several oncogenic pathways at once is now urgently needed due to these difficulties. Since it might possibly circumvent resistance mechanisms and produce synergistic effects by interfering with complementary signaling cascades necessary for tumor survival and development, multi-targeted therapy has become a particularly intriguing approach [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmong the multiple molecular targets involved in cancer pathogenesis, the Vascular Endothelial Growth Factor Receptor 2 (VEGFR2) and Janus Kinase 2 (JAK2) play critical roles in tumor biology. VEGFR2 is the major angiogenic signaling mediator, regulating endothelial cell proliferation, motility, and survival, and hence plays a critical role in tumor neovascularization. Overexpression of VEGFR2 and its ligand VEGF has been seen in many solid tumors, including breast, colorectal, lung, and hepatocellular carcinomas, and is associated with a poor prognosis and metastatic potential [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. JAK2 also functions as a crucial node in the JAK/STAT signaling system, transducing signals from numerous cytokines and growth factors to regulate gene expression programs that govern cell proliferation, differentiation, and survival. Constitutive activation of JAK2, whether caused by activating mutations like JAK2V617F or by persistent upstream signaling, promotes abnormal cell proliferation and contributes to the progression of both hematological and solid tumors [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eImportantly, previous research has indicated extensive interaction between these pathways, with the VEGF/JAK2/STAT3 axis serving as a crucial signaling module in cancer progression [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Recent research has shown that inhibiting VEGFR2 with medicines like Anlotinib has anti-tumor effects in part because it suppresses the JAK2/STAT3 pathway, underlining the therapeutic potential of targeting these kinases together [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This functional connection provides a compelling rationale for the development of dual VEGFR2/JAK2 inhibitors that could disrupt both angiogenic signaling and direct tumor cell proliferation pathways, potentially leading to increased anti-cancer activity.\u003c/p\u003e \u003cp\u003eNatural products have long been a rich source of therapeutic agents, accounting for over half of all licensed anticancer medicines. Terpenes, a large and structurally diverse family of plant secondary metabolites, have received substantial attention due to their wide range of biological activities, including anti-inflammatory, antioxidant, and anticancer effects. Monoterpenes in particular have been shown to exert antitumor activities by inducing apoptosis and cell cycle arrest, and by modulating oxidative stress in cancer cells [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Myrcene (7-methyl-3-methylene-1,6-octadiene), a monoterpene prevalent in essential oils of plants such as hops, cannabis, and lemongrass, is a particularly promising option for drug development [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Preclinical studies have shown that myrcene has anti-inflammatory, analgesic, and sedative activities, and growing data shows that it may have anticancer effects by modulating oxidative stress and apoptosis [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, the molecular processes that underpin myrcene's potential anti-cancer effect, including its capacity to target critical oncogenic kinases, remain largely unexplored.\u003c/p\u003e \u003cp\u003eComputational techniques and network pharmacology have transformed modern drug development by allowing for quick, cost-effective screening of putative therapeutic molecules before experimental confirmation [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Network pharmacology integrates biological data with computational predictions to map complex interactions between drugs, targets, and pathways, enabling the identification of multi-target effects and synergistic mechanisms within disease networks [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Molecular docking simulations can predict the binding modalities and affinities of small compounds to protein targets, providing atomic-level insights into ligand-receptor interactions [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Density functional theory simulations supplement docking research by revealing the electronic characteristics and chemical reactivity of compounds, such as frontier molecular orbital energies and molecular electrostatic potential distributions that regulate molecular recognition [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Molecular dynamics simulations go beyond static images by modeling the time-dependent behavior of protein-ligand complexes under physiological settings, evaluating conformational stability and contact persistence on nanosecond to microsecond timescales [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Finally, MM-GBSA binding free energy calculations provide quantitative estimates of binding strength and determine the energetic contributions driving complex formation [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, we used an integrated computational approach to assess the potential of myrcene as a dual inhibitor of VEGFR2 and JAK2. Molecular docking was used to predict binding affinities and interaction patterns with both targets, followed by DFT analysis to investigate myrcene's electrical characteristics and reactivity. Extensive 200 ns molecular dynamics (MD) simulations were used to evaluate the stability and conformational dynamics of myrcene-bound complexes, which were supplemented by MM-GBSA calculations to quantify binding free energies. This thorough in silico study seeks to reveal mechanistic insights into myrcene's potential anti-cancer activity and provide the groundwork for future experimental validation of this natural chemical as a lead for dual-targeted cancer therapy.\u003c/p\u003e"},{"header":"2. Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1.Target Protein Selection and Preparation\u003c/h2\u003e \u003cp\u003eThe three-dimensional crystal structures of Vascular Endothelial Growth Factor Receptor 2 (VEGFR2; PDB ID: 3WZD) and Tyrosine-Protein Kinase JAK2 (PDB ID: 6VNI) were obtained from the RCSB Protein Data Bank. These targets were chosen due to their important roles in tumor angiogenesis and cancer cell proliferation, making them clinically relevant for dual-target cancer therapy. Protein structures were created using BIOVIA Discovery Studio, which eliminated all crystallographic water molecules, heteroatoms, and co-crystallized ligands. To optimize the proteins for molecular docking simulations, polar hydrogen atoms were added, along with Gasteiger charges. The produced proteins were preserved in PDB format for future docking experiments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2.Ligand Preparation\u003c/h2\u003e \u003cp\u003eThe chemical structure of myrcene (PubChem CID: 31253) was extracted from the PubChem database in SDF format and translated to PDB format with OpenBabel (v2.4.0). The chemical was imported into Avogadro (v1.2.0) for geometric optimization, and the MMFF94 force field was used to minimize energy and find the lowest energy conformation. To perform docking simulations, the reduced ligand structure was stored in PDBQT format using AutoDock Tools (v1.5.7).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Molecular Docking and Interaction Analysis\u003c/h2\u003e \u003cp\u003eAutoDock 4.0 was used to determine the binding affinities and interaction modalities of myrcene with both targets. The docking grid boxes were defined to contain the full active sites, with size of 60 \u0026times; 60 \u0026times; 60 \u0026Aring; and grid spacing of 0.375 \u0026Aring; per protein. The grid box for VEGFR2 was focused on the ATP-binding pocket, whereas the grid for JAK2 was similarly constructed to encompass the active region of the kinase domain. Docking parameters were tuned using 300 population sizes, 27,000 generations, 1,000,000 assessments, and 100 Genetic Algorithm runs to achieve complete conformational sampling. Each protein-ligand complex's binding affinity was measured, and the optimal pose was chosen based on the lowest binding energy and most beneficial interaction patterns. BIOVIA Discovery Studio was used for post-docking analysis to detect and show critical chemical interactions between myrcene and both targets' active site residues, such as hydrogen bonds, hydrophobic contacts, and electrostatic interactions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Protein\u0026ndash;Protein Interaction (PPI) Network Construction and Functional Enrichment Analysis\u003c/h2\u003e \u003cp\u003eThe STRING database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://string-db.org\u003c/span\u003e\u003cspan address=\"https://string-db.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used to generate protein\u0026ndash;protein interaction (PPI) networks centered on VEGFR2 and JAK2. To characterize the functional relevance of the interacting proteins, Gene Ontology (GO) annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed within STRING to identify significantly enriched biological processes, molecular functions, cellular components, and signaling pathways associated with the VEGFR2 and JAK2 networks.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Density Functional Theory Analysis\u003c/h2\u003e \u003cp\u003eTo examine Myrcene\u0026rsquo;s electronic characteristics and chemical reactivity, density functional theory (DFT) calculations were performed with Gaussian 16 using the Becke-3-Lee-Yang-Parr (B3LYP) hybrid functional and the 6-311G(d,p) basis set, an approach widely validated for predicting structural, electronic, and reactivity properties of small to medium-sized organic molecules. Geometry optimizations were carried out in the gas phase without symmetry constraints, and frequency calculations at the same level confirmed the absence of imaginary frequencies, ensuring that the optimized structure corresponds to a true local minimum on the potential energy surface. Frontier molecular orbital energies, encompassing the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO), were then used to calculate the HOMO\u0026ndash;LUMO energy gap, which is a key predictor of chemical stability and reactivity [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Molecular electrostatic potential (MEP) maps were generated to visualize the charge distribution across the molecular surface, identifying regions of negative potential susceptible to electrophilic attack and regions of positive potential favoring nucleophilic interaction, thereby revealing potential interaction sites relevant to ligand binding [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Molecular Dynamics Simulation\u003c/h2\u003e \u003cp\u003eMolecular dynamics simulations were performed for 200 ns using GROMACS 2023 [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]to assess the stability and conformational behavior of myrcene coupled to VEGFR2 and JAK2. The best-docked complexes served as the starting structures, with ligand topologies created by ACPYPE and ANTECHAMBER utilizing the Amber99 force field [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. To simulate physiological circumstances, each compound was dissolved in a TIP3P water box with a 10 \u0026Aring; buffer, neutralized with ions, and adjusted to 0.15 M NaCl concentration [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Energy was minimized using steepest descent and conjugate gradient techniques until forces were less than 1000 kJ\u0026middot;mol⁻\u0026sup1;\u0026middot;nm⁻\u0026sup1;. Systems were equilibrated for 200 ps each using NVT and NPT ensembles at 300 K and 1 bar, followed by 200 ns production runs with a 2 fs time step, SHAKE restrictions, and PME electrostatics [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Trajectory investigations included RMSD, RMSF, radius of gyration, SASA, hydrogen bonding, and principal component analysis to evaluate complex stability, flexibility, compactness, solvation, interaction persistence, and important conformational dynamics.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Binding Free Energy Calculations\u003c/h2\u003e \u003cp\u003eTo evaluate myrcene's binding free energy with both targets, Molecular Mechanics with Generalized Born Surface Area calculations were performed on snapshots collected from the last 50 ns of the MD trajectories, which represented the simulation's stable phase. The binding free energy was estimated by subtracting the complex's free energy from the sum of the protein and ligand's free energies. The energy components included molecular mechanics energy (bonded, van der Waals, and electrostatic contacts), as well as solvation free energy (polar solvation using the Generalized Born model and non-polar solvation using the solvent-accessible surface area term). This approach yielded quantitative insights into the thermodynamic driving forces that underpin myrcene binding to both targets.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Molecular Docking Analysis\u003c/h2\u003e \u003cp\u003eMolecular docking of myrcene against VEGFR2 (3WZD) and JAK2 (6VNI) exhibited high binding affinities for both targets, indicating possible dual-inhibitory activity (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Myrcene had a docking score of -7.98 kcal/mol for VEGFR2 and \u0026minus;\u0026thinsp;8.31 kcal/mol for JAK2. These data imply a significant binding potential similar to known kinase inhibitors, with somewhat higher affinity for JAK2. The three-dimensional structures of both targets are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, with VEGFR2 colored orange and JAK2 colored forest green.\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\u003eMolecular docking results of myrcene against VEGFR2 (3WZD) and JAK2 (6VNI).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePubChem ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\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=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMyrcene\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e31253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3WZD (VEGFR2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6VNI (JAK2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-8.31\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=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Protein-Ligand Interaction Analysis\u003c/h2\u003e \u003cp\u003eDetailed interaction profiling using BIOVIA Discovery Studio identified the critical chemical interactions that stabilize myrcene within the active regions of both protein targets (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Myrcene is stabilized predominantly by hydrophobic interactions, such as π-sigma and π-alkyl contacts. These interactions fix the ligand within the binding pockets. Other forms of interactions were detected, including salt bridges, π-cation interactions, unfavorable contacts, and hydrogen bonds (both conventional and carbon hydrogen bonds).\u003c/p\u003e \u003cp\u003eNotably, in the JAK2-myrcene complex (PDB ID: 6VNI), hydrogen bonds were established with residues Pro1002 and Lys1005. These particular polar interactions are most likely responsible for the increased binding stability and may explain why the JAK2-myrcene complex has a higher binding affinity than the VEGFR2-myrcene complex. The combination of both strong hydrophobic interactions and stabilizing hydrogen bonds suggests that myrcene has a more favorable and long-lasting interaction profile in the JAK2 active region.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.3. PPI network and functional enrichment analysis of VEGFR2 and JAK2 genes\u003c/h2\u003e \u003cp\u003eAnalysis using the STRING database identified proteins showing direct or indirect interactions with VEGFR2 and JAK2. The JAK2 network comprised 58 nodes and 735 edges (average node degree\u0026thinsp;=\u0026thinsp;25.3), indicating high connectivity among JAK2-associated proteins. The VEGFR2 network comprised 18 nodes and 96 edges (average node degree\u0026thinsp;=\u0026thinsp;10.7). Protein\u0026ndash;protein interaction (PPI) enrichment was highly significant (p\u0026thinsp;\u0026lt;\u0026thinsp;1.0\u0026times;10⁻\u0026sup1;⁶), suggesting the observed interactions are biologically meaningful rather than random.\u003c/p\u003e \u003cp\u003eSubsequent functional enrichment analyses were performed to elucidate the biological relevance of the JAK2- and VEGFR2-associated networks in cancer. For the JAK2 network, GO enrichment analysis identified the top BP terms as positive regulation of STAT protein phosphorylation, type I interferon signaling pathway, and cellular response to virus. The leading MF terms included type I interferon receptor binding, cytokine receptor binding, and cytokine activity, while the main CC terms were nucleosome, chromatin, and nucleoplasm. KEGG pathway analysis revealed significant enrichment in the JAK\u0026ndash;STAT signaling pathway, Hepatitis B, and cytosolic DNA-sensing pathway.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor the VEGFR2 network, the top BP terms were calcium-mediated signaling, positive regulation of angiogenesis, and positive regulation of endothelial cell proliferation. The principal MF terms included calcium-dependent protein kinase C activity, inositol 1,4,5-trisphosphate-sensitive calcium-release channel activity, and ion channel regulator activity, whereas the most enriched CC terms were platelet dense tubular network membrane, sarcoplasmic reticulum membrane, and ryanodine receptor complex. KEGG pathway analysis demonstrated enrichment in the VEGF signaling pathway, GnRH signaling pathway, and proteoglycans in cancer. A statistical significance threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was applied, with multiple-testing correction performed where applicable. Results are presented in Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Density Functional Theory (DFT) Analysis\u003c/h2\u003e \u003cp\u003eDFT calculations at the B3LYP/6-311G(d,p) level provided detailed insights into the electronic structure and reactivity of Myrcene. The optimized geometry converged to a true minimum, as confirmed by the absence of imaginary frequencies, indicating a stable configuration suitable for interactions with protein targets. The HOMO and LUMO energies were calculated as \u0026minus;\u0026thinsp;0.276 and \u0026minus;\u0026thinsp;0.153 a.u., respectively, resulting in a HOMO\u0026ndash;LUMO gap of 0.123 a.u., which suggests moderate chemical reactivity (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The relatively high HOMO energy indicates good electron-donating ability, while the LUMO energy reflects the potential for electron acceptance, supporting possible charge-transfer interactions with the kinase domains. Molecular electrostatic potential mapping revealed electron-rich regions around the conjugated double bonds, which may serve as preferential sites for electrophilic attack or hydrogen bond formation, while electron-deficient regions at the alkyl sites favor hydrophobic interactions. Additional computed descriptors, including chemical hardness (0.061 a.u.), chemical softness (8.196 a.u.⁻\u0026sup1;), chemical potential (0.171 Debye), electrophilicity (0.368 a.u.), maximum charge capacity (3.508), ionization energy (0.276 eV), electron affinity (0.153 eV), and dipole moment (\u0026minus;\u0026thinsp;0.214 a.u.), collectively indicate that Myrcene possesses balanced electronic characteristics, enabling both hydrophobic and selective polar interactions that are consistent with its favorable binding behavior observed in docking.\u003c/p\u003e \u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e DFT-computed electronic and reactivity descriptors for the most stable isomer of Myrcene, including dipole moment (p), isotropic polarizability (\u0026alpha;̃₀), HOMO\u0026ndash;LUMO gap (\u0026Delta;E_HL), chemical hardness (\u0026eta;), chemical softness (\u0026sigma;), chemical potential (\u0026mu;), electrophilicity (\u0026omega;), and maximum charge capacity (\u0026chi;). Calculations were performed at the DFT/UB3LYP 6-311G level of theory.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"510\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.4118%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.5882%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMyrcene\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.4118%;\"\u003e\n \u003cp\u003eCalculation Method\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.5882%;\"\u003e\n \u003cp\u003eUB3LYP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.4118%;\"\u003e\n \u003cp\u003eBasis Set\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.5882%;\"\u003e\n \u003cp\u003e6-311G\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.4118%;\"\u003e\n \u003cp\u003eTotal Energy [a.u]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.5882%;\"\u003e\n \u003cp\u003e-393.6237\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.4118%;\"\u003e\n \u003cp\u003eE\u003csub\u003eHOMO\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.5882%;\"\u003e\n \u003cp\u003e-0.276\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.4118%;\"\u003e\n \u003cp\u003eE\u003csub\u003eLUMO\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.5882%;\"\u003e\n \u003cp\u003e-0.153\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.4118%;\"\u003e\n \u003cp\u003e(\u0026Delta;E) [a.u]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.5882%;\"\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.4118%;\"\u003e\n \u003cp\u003e(\u0026eta;) [a.u]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.5882%;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.4118%;\"\u003e\n \u003cp\u003e(\u0026delta;) [a.u]\u003csup\u003e-1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.5882%;\"\u003e\n \u003cp\u003e16.393\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.4118%;\"\u003e\n \u003cp\u003e(\u0026chi;) [a.u]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.5882%;\"\u003e\n \u003cp\u003e0.214\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.4118%;\"\u003e\n \u003cp\u003e(Pi) [a.u]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.5882%;\"\u003e\n \u003cp\u003e-0.214\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.4118%;\"\u003e\n \u003cp\u003e(\u0026omega;) [a.u]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.5882%;\"\u003e\n \u003cp\u003e0.368\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.4118%;\"\u003e\n \u003cp\u003e(S) [a.u]\u003csup\u003e-1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.5882%;\"\u003e\n \u003cp\u003e8.196\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.4118%;\"\u003e\n \u003cp\u003e[\u0026Delta;N\u003csub\u003emax\u003c/sub\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.5882%;\"\u003e\n \u003cp\u003e3.508\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.4118%;\"\u003e\n \u003cp\u003e(IE) [ev]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.5882%;\"\u003e\n \u003cp\u003e0.276\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.4118%;\"\u003e\n \u003cp\u003e(EA) [ev]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.5882%;\"\u003e\n \u003cp\u003e0.153\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.4118%;\"\u003e\n \u003cp\u003e(\u0026mu;) [Debye]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.5882%;\"\u003e\n \u003cp\u003e0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e[a.u]=atomic unit; [ev]=electron volts.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.6. Molecular Dynamics Simulation Analysis\u003c/h2\u003e \u003cp\u003eTo comprehensively assess the dynamic stability, conformational behavior, and interaction persistence of myrcene bound to VEGFR2 and JAK2, 200 ns all-atom molecular dynamics simulations were performed using GROMACS 2023. The stability and flexibility of both protein-ligand complexes were evaluated through backbone RMSD, residue-wise RMSF, radius of gyration (Rg), solvent-accessible surface area (SASA) and hydrogen bond (Hb) occupancy. Collectively, these parameters provide a robust assessment of structural integrity, compactness, and essential motions throughout the simulation trajectory.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.6.1. Root Mean Square Deviation (RMSD)\u003c/h2\u003e \u003cp\u003eLigand RMSD analysis was performed to evaluate the structural stability, positional retention, and equilibration behavior of myrcene within the binding pockets of VEGFR2 and JAK2 over the 200 ns molecular dynamics simulation. RMSD values were calculated relative to the initial docked conformations, providing insight into ligand mobility and binding stability throughout the trajectory.\u003c/p\u003e \u003cp\u003eThe VEGFR2\u0026ndash;myrcene complex exhibited an average ligand RMSD of 1.16 \u0026Aring;, whereas the JAK2\u0026ndash;myrcene complex showed a slightly higher average RMSD of 1.85 \u0026Aring; (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). In both systems, myrcene underwent a short initial equilibration phase, followed by stable RMSD plateaus with minimal fluctuations for the remainder of the simulation. Notably, ligand RMSD values for both complexes remained well below the widely accepted 3.0 \u0026Aring; stability threshold for protein\u0026ndash;ligand systems, indicating that myrcene remained stably anchored within the binding sites without undergoing significant displacement or reorientation.\u003c/p\u003e \u003cp\u003eThe comparatively lower ligand RMSD observed in the VEGFR2\u0026ndash;myrcene complex suggests a more rigid and conformationally stable binding mode relative to JAK2. Nevertheless, both complexes demonstrate favorable dynamic stability, supporting the robustness of myrcene binding throughout the simulation period.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e3.6.2. Root Mean Square Fluctuation (RMSF)\u003c/h2\u003e \u003cp\u003eResidue-wise RMSF analysis was conducted to examine local flexibility and identify protein regions influenced by ligand binding during the simulation.\u003c/p\u003e \u003cp\u003eThe VEGFR2\u0026ndash;myrcene complex displayed an average RMSF of 1.69 \u0026Aring;, while the JAK2\u0026ndash;myrcene complex exhibited an average RMSF of 1.61 \u0026Aring; (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). In both systems, elevated fluctuations were primarily confined to the N-terminal and C-terminal regions, as well as surface-exposed loop segments, which are intrinsically flexible and distant from the binding sites.\u003c/p\u003e \u003cp\u003eCrucially, residues within and surrounding the ligand-binding pockets showed markedly reduced fluctuations, indicating strong ligand-mediated stabilization of the active site regions. These observations confirm that myrcene binding restricts excessive local mobility, thereby preserving the functional architecture of both VEGFR2 and JAK2.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e3.6.3. Radius of Gyration (Rg)\u003c/h2\u003e \u003cp\u003eThe radius of gyration was analyzed to assess changes in protein compactness and overall folding stability upon ligand binding.\u003c/p\u003e \u003cp\u003eThe average Rg value for the VEGFR2\u0026ndash;myrcene complex was 2.052 \u0026Aring;, while the JAK2\u0026ndash;myrcene complex exhibited an average Rg of 2.0417 \u0026Aring; (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Both complexes maintained stable Rg profiles throughout the 200 ns simulation, with only minor oscillations.\u003c/p\u003e \u003cp\u003eThe absence of significant Rg fluctuations indicates that myrcene binding did not promote protein unfolding or large-scale structural expansion. Instead, both proteins retained their compact tertiary structures, further supporting the structural robustness of the complexes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e3.6.4. Solvent Accessible Surface Area (SASA)\u003c/h2\u003e \u003cp\u003eSASA analysis was performed to monitor changes in protein surface exposure and to detect potential unfolding or major conformational rearrangements during the simulation.\u003c/p\u003e \u003cp\u003eThe VEGFR2-myrcene complex exhibited an average SASA of 16,776.1 \u0026Aring;\u0026sup2;, whereas the JAK2-myrcene complex showed an average SASA of 15,159.3 \u0026Aring;\u0026sup2; (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). SASA trajectories for both systems remained stable over time, with no abrupt increases indicative of solvent exposure due to structural destabilization.\u003c/p\u003e \u003cp\u003eThese findings suggest that myrcene binding does not significantly alter the solvent accessibility of either protein and that both complexes preserve their folded states throughout the simulation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e3.6.5. Hydrogen Bond Analysis\u003c/h2\u003e \u003cp\u003eHydrogen bond analysis was conducted to evaluate the persistence and stability of intermolecular interactions between myrcene and both target proteins.\u003c/p\u003e \u003cp\u003eThe VEGFR2\u0026ndash;myrcene complex formed an average of 2.10 hydrogen bonds, while the JAK2\u0026ndash;myrcene complex maintained an average of 1.02 hydrogen bonds during the simulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Although myrcene is predominantly hydrophobic, the presence of persistent hydrogen bonds highlights favorable ligand accommodation within the binding pockets.\u003c/p\u003e \u003cp\u003eThe higher hydrogen bond occupancy observed in the VEGFR2 complex may partially explain its lower RMSD and enhanced stability compared to the JAK2 complex, indicating a more optimal interaction network.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.7. Binding Free Energy Calculations (MM-GBSA)\u003c/h2\u003e \u003cp\u003eMM-GBSA analysis revealed substantial differences in the thermodynamic profiles governing myrcene binding to VEGFR2 and JAK2 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The VEGFR2\u0026ndash;myrcene complex exhibited a strongly favorable binding free energy (ΔG\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;26.09 kcal\u0026middot;mol⁻\u0026sup1;), dominated by a pronounced enthalpic contribution (ΔH\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;41.78 kcal\u0026middot;mol⁻\u0026sup1;). The relatively modest entropic penalty (\u0026minus;\u0026thinsp;TΔS\u0026thinsp;=\u0026thinsp;15.69 kcal\u0026middot;mol⁻\u0026sup1;) indicates limited loss of conformational freedom upon binding, consistent with a compact and well-stabilized interaction. The low standard deviation and SEM values further support good convergence of the MD trajectories and the robustness of the calculated energetics for this complex.\u003c/p\u003e \u003cp\u003eIn contrast, although the JAK2\u0026ndash;myrcene complex also displayed a favorable binding free energy (ΔG\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;24.00 kcal\u0026middot;mol⁻\u0026sup1;), its thermodynamic signature differed markedly. Binding to JAK2 was characterized by a strongly favorable enthalpic term (ΔH\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;39.74 kcal\u0026middot;mol⁻\u0026sup1;), comparable in magnitude to that observed for VEGFR2; however, this gain was accompanied by a larger entropic penalty (\u0026minus;\u0026thinsp;TΔS\u0026thinsp;=\u0026thinsp;15.74 kcal\u0026middot;mol⁻\u0026sup1;). The elevated SD and SEM values for the JAK2 complex suggest increased conformational variability and reduced stability of myrcene within the binding pocket, indicating that the favorable enthalpy arises from transient or less optimally retained interactions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMM-GBSA Binding Energy Components of VEGFR2-Myrcene and JAK2-Myrcene Complexes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eΔH (kcal\u0026middot;mol⁻\u0026sup1;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;TΔS (kcal\u0026middot;mol⁻\u0026sup1;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eΔG (kcal\u0026middot;mol⁻\u0026sup1;)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVEGFR2\u0026ndash;Myrcene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;41.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;26.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSEM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJAK2\u0026ndash;Myrcene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;39.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;24.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSEM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.79\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"},{"header":"4. Discussion","content":"\u003cp\u003eThis study paint a consistent and mechanistically coherent picture of myrcene as a bioactive monoterpene whose physicochemical properties and binding behavior confer clear, therapeutically relevant engagement with kinase targets most notably VEGFR2 with secondary, context-dependent compatibility with JAK2. Molecular docking established that myrcene can be accommodated within the ATP-binding pockets of both VEGFR2 and JAK2, producing energetically favorable poses (docking scores\u0026thinsp;\u0026minus;\u0026thinsp;7.98 and \u0026minus;\u0026thinsp;8.31 kcal/mol, respectively) that justify further, higher-resolution interrogation. Previous studies indicate that docking scores below \u0026minus;\u0026thinsp;5.0 kcal/mol generally reflect strong binding affinity and stable protein\u0026ndash;ligand interactions [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Post-docking interaction profiling clarified the nature of these engagements: myrcene\u0026rsquo;s binding is dominated by hydrophobic contacts (π-sigma and π-alkyl interactions) that tightly pack the ligand inside hydrophobic subpockets, while a limited set of polar contacts including hydrogen bonds in the JAK2 docked pose with Pro1002 and Lys1005 adds local stabilization. Thus, docking and interaction mapping together indicate that myrcene occupies chemically sensible binding modes in both kinases, with hydrophobic complementarity as the primary recognition motif and occasional polar anchoring that can modulate affinity.\u003c/p\u003e \u003cp\u003eAt the network level, our protein\u0026ndash;protein interaction and pathway enrichment analyses situate VEGFR2 and JAK2 within distinct but biologically coherent signaling modules that are relevant to cancer pathophysiology. JAK2 is a central mediator of cytokine receptor signaling and downstream STAT activation, an axis that is frequently dysregulated in malignancies and implicated in processes such as proliferation, immune regulation, and angiogenesis. Constitutive activation of the JAK2/STAT3 pathway has been observed across diverse solid tumors and is associated with enhanced expression of angiogenic factors including VEGF and basic fibroblast growth factor (bFGF), as well as poorer clinical outcomes, reinforcing its role as a highly connected oncogenic signaling hub. Indeed, the JAK2/STAT3 axis promotes tumor angiogenesis and supports tumor-host interactions through modulation of both proliferative and immune-linked signaling pathways [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. In contrast, VEGFR2 is a principal receptor tyrosine kinase driving angiogenesis through direct mediation of vascular endothelial growth factor (VEGF) signals. Upon ligand binding, VEGFR2 undergoes dimerization and autophosphorylation, initiating downstream cascades that regulate endothelial cell proliferation, migration, and survival processes fundamental to neovascularization in tumoral contexts. The VEGF/VEGFR2 axis is widely recognized as a cornerstone of pathological angiogenesis in cancer and forms the basis for numerous anti-angiogenic therapeutic strategies [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The distinct enrichment of JAK\u0026ndash;STAT and cytokine signaling pathways around JAK2, compared with the angiogenesis and endothelial proliferation networks centered on VEGFR2, corroborates the biological plausibility of targeting these kinases concurrently in oncology. Whereas modulation of VEGFR2 would be expected to disrupt tumor blood vessel formation, interference with JAK2 signaling could exert broader effects on proliferative and immune-related processes. Together, these complementary mechanisms support the therapeutic rationale for dual-targeting strategies in cancer that aim to suppress both angiogenic and tumor-intrinsic oncogenic signaling.\u003c/p\u003e \u003cp\u003eQuantum-chemical characterization via DFT provides mechanistic depth to the structural and network findings by revealing the intrinsic electronic properties that govern myrcene\u0026rsquo;s interactions with protein targets. Geometry optimization converged to a true minimum, as confirmed by frequency calculations, indicating a stable molecular configuration suitable for binding studies. The frontier molecular orbital analysis showed a HOMO\u0026ndash;LUMO gap consistent with moderate chemical reactivity, enabling Myrcene to participate in weak charge-transfer interactions while primarily engaging through dispersion forces. Molecular electrostatic potential mapping localized electron-rich regions around the conjugated double bonds and areas of mild positive potential at alkylated sites. This distribution rationalizes why myrcene, although largely nonpolar, can achieve van der Waals and dispersion-driven stabilization within hydrophobic protein pockets, while still retaining the capacity for occasional, targeted polar interactions when appropriately oriented. These quantum-chemical descriptors thus complement the docking and MD results, explaining how myrcene\u0026rsquo;s electronic structure underpins both its preferential engagement with VEGFR2 and its limited, context-dependent compatibility with JAK2 [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. By providing a detailed map of reactive sites and electronic distribution, DFT not only validates observed binding patterns but also informs rational modifications to enhance multi-target activity, particularly in regions where polar contacts could be introduced to improve JAK2 binding without disrupting VEGFR2 stabilization.\u003c/p\u003e \u003cp\u003eLong-timescale molecular dynamics simulations combined with MM-GBSA free-energy decomposition offer decisive and integrative evidence for distinguishing target preference and elucidating the underlying binding mechanism beyond what static docking models can reveal. While docking scores provide a rapid, approximate ranking of ligand poses based on simplified scoring functions, they lack explicit accounting for solvent dynamics, protein flexibility, and entropic contributions inherent to physiological conditions. In contrast, extended MD sampling captures the dynamic evolution of the protein\u0026ndash;ligand complex over hundreds of nanoseconds, enabling exploration of relevant configurational space and identification of stable binding modes that may not be apparent from a single snapshot alone [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Subsequent MM-GBSA rescoring leverages an ensemble of equilibrated structures from the simulation trajectory to compute binding free energies by incorporating molecular mechanics energies and solvent contributions through implicit solvation models, and can improve affinity predictions relative to isolated docking scores [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAcross the 200 ns molecular dynamics simulations, the VEGFR2\u0026ndash;myrcene complex exhibited a lower average ligand RMSD of 1.16 \u0026Aring;, modest RMSF values for binding-site residues, a stable radius of gyration, and a consistent SASA profile, indicative of a compact and well-sequestered complex. Hydrogen-bond analysis revealed persistent interactions (\u0026asymp;\u0026thinsp;2.10 H-bonds), complementing the hydrophobic packing and confirming stable ligand retention. MM-GBSA decomposition showed a strongly favorable overall binding free energy (ΔG\u0026thinsp;\u0026asymp;\u0026thinsp;\u0026minus;\u0026thinsp;26.09 kcal\u0026middot;mol⁻\u0026sup1;), dominated by a large negative enthalpy (ΔH\u0026thinsp;\u0026asymp;\u0026thinsp;\u0026minus;\u0026thinsp;41.78 kcal\u0026middot;mol⁻\u0026sup1;) with a moderate entropic penalty (\u0026minus;\u0026thinsp;TΔS\u0026thinsp;\u0026asymp;\u0026thinsp;15.69 kcal\u0026middot;mol⁻\u0026sup1;). These results indicate that Myrcene forms a highly stable and energetically favorable complex with VEGFR2, consistent with DFT-predicted electronic characteristics that support dispersion-driven and selective polar interactions. In addition, the JAK2\u0026ndash;myrcene complex also displayed favorable binding energetics. Although ligand RMSD was slightly higher (1.85 \u0026Aring;) and hydrogen-bond occupancy lower (\u0026asymp;\u0026thinsp;1.02 H-bonds), the MM-GBSA-calculated binding free energy (ΔG\u0026thinsp;\u0026asymp;\u0026thinsp;\u0026minus;\u0026thinsp;24.00 kcal\u0026middot;mol⁻\u0026sup1;) remains strongly negative. The enthalpic contribution (ΔH\u0026thinsp;\u0026asymp;\u0026thinsp;\u0026minus;\u0026thinsp;39.74 kcal\u0026middot;mol⁻\u0026sup1;) is comparable to VEGFR2, while the slightly higher entropic penalty (\u0026minus;\u0026thinsp;TΔS\u0026thinsp;\u0026asymp;\u0026thinsp;15.74 kcal\u0026middot;mol⁻\u0026sup1;) reflects modest conformational flexibility. These values indicate that Myrcene also binds favorably to JAK2, though with slightly reduced dynamic stability relative to VEGFR2.\u003c/p\u003e \u003cp\u003eTaken together, the multi-tiered computational evidence supports the positioning of myrcene as a VEGFR2-centered lead scaffold with demonstrable potential for adjunctive JAK2 modulation. The concordance among docking geometry, interaction mapping, quantum-chemical descriptors, sustained MD stability, and strongly favorable MM-GBSA energetics for VEGFR2 provides a robust mechanistic rationale for pursuing myrcene-derived optimization toward anti-angiogenic therapeutics. At the same time, the observed, albeit weaker, engagement with JAK2 highlights an accessible chemical space for scaffold elaboration aimed at multi-target modulation: directed substitutions informed by DFT-derived electrostatic maps and MD-derived contact snapshots could introduce persistent polar anchors in the JAK2 pocket without sacrificing the dispersion-driven enthalpic benefits that underpin VEGFR2 binding. Overall, the results demonstrate a coherent and actionable pathway from molecular recognition to biological relevance, supporting further medicinal-chemistry and experimental follow-up to translate these in silico insights into preclinical candidates for cancer therapy\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study provides a detailed computational evaluation of myrcene as a potential dual inhibitor of VEGFR2 and JAK2, which are important kinases implicated in cancer angiogenesis and proliferative signaling. Molecular docking identified energetically advantageous binding poses in both targets' ATP-binding pockets, which were predominantly sustained by hydrophobic contacts and selective hydrogen bonds. Quantum-chemical DFT research validated myrcene's structural stability, moderate HOMO-LUMO gap, and favorable electronic distribution, allowing for both dispersion-driven and occasional polar contacts within protein pockets. Extended MD simulations revealed that myrcene forms a compact, dynamically stable complex with VEGFR2 while preserving favorable binding energies with JAK2. MM-GBSA free-energy studies revealed energetically favorable interactions with both kinases, despite a modest decrease in dynamic stability with JAK2. Overall, these multi-tiered computational results place myrcene as a dual VEGFR2/JAK2 inhibitor, with a predominant preference for VEGFR2 and demonstrable involvement with JAK2. The findings provide a molecular foundation for further optimizing myrcene-derived scaffolds for multi-target anticancer therapies, as well as evidence for experimental validation in preclinical models.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was not supported by any funding or grant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interests \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report there are no competing interests to declare. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthorship contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCromwel Tepap Zemnou:\u0026nbsp;\u003c/strong\u003eConceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Supervision, Resources, Writing – original draft, Writing – review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRamelle Ngakam:\u0026nbsp;\u003c/strong\u003eData curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Not applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eF. 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Phys.\u003c/em\u003e, vol. 22, no. 17, pp. 9656\u0026ndash;9663, May 2020, doi: 10.1039/D0CP00831A.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"chemical-papers","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"chpa","sideBox":"Learn more about [Chemical Papers](http://link.springer.com/journal/11696)","snPcode":"11696","submissionUrl":"https://www.editorialmanager.com/CHPA/default.aspx","title":"Chemical Papers","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Myrcene, Dual kinase inhibition, JAK2, VEGFR2, Molecular docking, Molecular dynamics simulation, Cancer therapy","lastPublishedDoi":"10.21203/rs.3.rs-8928128/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8928128/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCancer progression involves interconnected pathways, including angiogenesis mediated by VEGFR2 and proliferative signaling regulated by JAK2. Dual inhibition of these kinases represents a promising therapeutic strategy. In this study, we applied an integrated computational approach to evaluate myrcene, a natural monoterpene, as a potential dual JAK2/VEGFR2 inhibitor. Molecular docking revealed favorable binding within the ATP-binding pockets of VEGFR2 and JAK2, with scores of \u0026minus;\u0026thinsp;7.98 and \u0026minus;\u0026thinsp;8.31 kcal\u0026middot;mol⁻\u0026sup1;, respectively. Interactions were primarily stabilized by hydrophobic π-alkyl and π-sigma contacts, with selective hydrogen bonding observed in JAK2. Density functional theory (B3LYP/6-311G(d,p)) confirmed structural stability and a moderate HOMO-LUMO gap, supporting dispersion-driven interactions and occasional polar contacts. In 200-ns molecular dynamics simulations, the VEGFR2\u0026ndash;myrcene complex exhibited lower ligand RMSD (1.16 \u0026Aring;) and higher hydrogen bond occupancy (2.10) than the JAK2 complex (RMSD 1.85 \u0026Aring;; hydrogen bonds 1.02), reflecting greater dynamic stability for VEGFR2. MM-GBSA analysis showed strongly favorable binding free energies for both targets (ΔG\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;26.09 kcal\u0026middot;mol⁻\u0026sup1; for VEGFR2; ΔG\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;24.00 kcal\u0026middot;mol⁻\u0026sup1; for JAK2), indicating that myrcene can form stable, energetically favorable complexes with both kinases. Collectively, these results support myrcene as a dual inhibitor, with pronounced VEGFR2 affinity and significant JAK2 engagement, highlighting its potential as a scaffold for the rational design of dual-target anticancer therapeutics.\u003c/p\u003e","manuscriptTitle":"Integrated computational analysis of myrcene as a dual JAK2/VEGFR2 inhibitor for cancer therapy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-03 09:27:44","doi":"10.21203/rs.3.rs-8928128/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-10T14:40:34+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"63784541518746741032659146320932875821","date":"2026-04-01T15:48:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-24T05:09:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"244425992461871050737413513315116706462","date":"2026-03-03T14:37:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"231596168285141437491795662820075441981","date":"2026-03-03T12:28:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-02T18:04:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-21T16:46:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-21T15:33:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"Chemical Papers","date":"2026-02-20T17:26:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"chemical-papers","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"chpa","sideBox":"Learn more about [Chemical Papers](http://link.springer.com/journal/11696)","snPcode":"11696","submissionUrl":"https://www.editorialmanager.com/CHPA/default.aspx","title":"Chemical Papers","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e2efdbac-3da1-404d-8e01-d9c8e23cf99a","owner":[],"postedDate":"March 3rd, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-10T14:40:34+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-19T13:53:36+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-03 09:27:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8928128","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8928128","identity":"rs-8928128","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}