In Silico Evaluation of Lipid-Drug Conjugates: Pharmacokinetic and Pharmacodynamic Profiling for Therapeutic Repurposing of Naloxone in Migraine Management

In Silico Evaluation of Lipid-Drug Conjugates: Pharmacokinetic and Pharmacodynamic Profiling for Therapeutic Repurposing of Naloxone in Migraine Management | 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 In Silico Evaluation of Lipid-Drug Conjugates: Pharmacokinetic and Pharmacodynamic Profiling for Therapeutic Repurposing of Naloxone in Migraine Management Ami Patel, Krutika Sawant This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6687113/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Migraine, a common neurological condition, requires novel therapeutic approaches beyond current symptomatic remedies. Drug repurposing offers a rapid-track solution to this demand. Naloxone, an opioid antagonist, has been identified as a potential candidate for migraine treatment, but its limited blood-brain barrier permeability and extensive metabolism limit its clinical effectiveness. Lipid-drug conjugates enhance therapeutic efficiency by chemically conjugating drugs to lipid groups, enhancing lipophilicity and systemic bioavailability, as well as enabling targeted delivery. They facilitate lymphatic targeting (when administered orally) by avoiding first-pass metabolism and prolong the duration of therapeutic action of drug by optimising pharmacokinetic profiles. The present investigation employed In silico methods to study naloxone and its novel naloxone lipid conjugates for altered pharmacokinetic parameters and enhanced interaction with serotonin, toll-like and µ-opioid receptor for the treatment of migraine. Computational ADMET, therapeutic target predictions and molecular docking methodologies were combined for in silico predictions of naloxone and its lipid conjugates. The results revealed that lipid conjugation significantly changed naloxone's pharmacokinetic profiles and binding affinity for serotonin, toll-like and µ-opioid receptor . In silico predictions indicated the potential of naloxone and its lipid conjugates for the treatment of migraine, with results demonstrating that the lipid conjugates provide longer duration of therapeutic action compared to naloxone. This rationale-driven drug repurposing approach has potential for the design of a new, brain-delivered, and serotonin-modulating compound for migraine treatment following in vitro and in vivo validation. Naloxone Lipid-drug conjugates Drug repurposing In silico ADMET Molecular docking Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Migraine, a prevalent neurological disorder affecting 14% of adults worldwide, significantly impacts quality of life, productivity, and healthcare utilization. Current treatments focus on acute relief or reducing migraine frequency, but many patients experience insufficient relief or severe side effects, highlighting the need for new, more effective therapies (Peres et al. 2024 ). Drug repurposing is a promising approach for rapid therapeutic development, leveraging the safety profiles and pharmacokinetic properties of known drugs. Naloxone, an opioid antagonist, has been identified as a potential migraine treatment due to its potential to modulate pain pathways and inflammatory processes involved in migraine pathophysiology, reducing the time and expenses required for new treatments to enter the market (Nicolodi and Sicuteri 1992 ; Burgess 2024 ). Moreover, reported research suggests that Toll-like receptor 4 ( TLR4 ) plays a role in neuroinflammation and pain processing in the trigeminovascular system, a central region in migraine pathophysiology. Naloxone has been shown to effectively treat migraine attacks, with recent findings suggesting that both opioid-active and inactive isomers of naloxone inhibit TLR4 receptor action (Ramachandran et al. 2019 ). Naloxone's clinical effectiveness in migraine is limited by its poor oral bioavailability, poor blood-brain barrier (BBB) penetration, rapid metabolism, and short half-life, necessitating frequent administration and parenteral administration; therefore, it is critical to improve its therapeutic levels to reach the central nervous system (CNS) (Naloxone: DrugBank Online Accessed 15 April 2025). The present study explored rational drug design using naloxone lipid conjugation, aiming to overcome limitations and improve pharmacokinetic profiles of naloxone by esterifying it using fatty acids. Lipid-drug conjugates (LDCs) are a revolutionary approach to bypass the limitations of traditional drug formulations by increasing the lipophilicity of drug through covalent attachment to lipids. This enhances stability and bioavailability, reduces the rate of clearance and facilitates targeted delivery to receptors. LDCs also exploit endogenous lipid transport systems to promote lymphatic uptake by avoiding hepatic metabolism and provide sustained release to maintain therapeutic plasma concentrations. Strategic use of labile linkers protects against off-target toxicity. Synthesising naloxone lipid conjugates may increase its repurposing potential by streamlining pharmacokinetic parameters without losing pharmacodynamic activity at migraine-relevant targets. This approach allows for a carrier-free system, simplifying formulation and enhancing therapeutic outcomes. It is anticipated that naloxone's lipid conjugation will improve its BBB permeability, metabolic stability, and interaction with target molecular species in the brain (Mohapatra and Dash 2024 ; Talele et al. 2025 ). In silico modelling allows for precise prediction of conjugate behaviour, enabling rapid rational LDC design for neurological use. The present investigation used in silico modelling to analyze absorption, distribution, metabolism, excretion and toxicity (ADMET) profiles and serotonin receptor (5-HTR), TLR4 and µ-opioid receptor binding activities of lipid conjugates of naloxone. The physicochemical, pharmacokinetic and pharmacodynamic characteristics of these compounds were predicted using computational tools such as SwissADME (SwissADME Accessed 10 January 2025), pkCSM (Deep-PK Accessed 24 January 2025), ProTox (Banerjee et al. 2024 ) and molecular docking (SwissDock) (SwissDock Accessed 15 January 2025). SwissADME is a web-based tool that predicts physicochemical properties, drug-likeness, and medicinal chemistry friendliness of small molecules. It offers various predictive models, making it an effective tool for predicting ADMET profiles of drug and their conjugates (Daina et al. 2017 ). SwissADME employs models like the ESOL model and SILICOS-IT method to predict physicochemical properties, classifying it on a log scale, providing insights into the solubility of drug and its conjugates in aqueous media, lipophilicity, reactivity, etc. (Dascălu et al. 2020 ). pkCSM uses graph-based signatures to predict ADME properties from molecular structure, predicting pharmacokinetic endpoints like volume of distribution, clearance rates, renal excretion capacity, and metabolic stability. It also predicts toxicity endpoints like hepatotoxicity and mutagenicity to prevent undesirable effects from lipid conjugation ( Pires et al. 2018 ; Velloso et al. 2021 ). Similarly, ProTox is a machine learning-based tool that predicts the toxicity of small molecules, including acute oral toxicity, essential for drug safety assessment, using machine learning-based algorithms. The study explores the potential of naloxone as an agent for migraine treatment, followed by the computational methodologies used to evaluate its lipid conjugates, assessing pharmacokinetic, toxicological, and receptor-binding properties for optimal brain delivery and therapeutic efficacy. 1. Methods for Predictions SwissADME, SwissDock, Deep-PK and ProTox were utilized to predict the physicochemical properties, pharmacokinetic profiles, pharmacodynamic properties, identify target and safety of Naloxone and its lipid conjugates. 2.1 ADMET Prediction and Target Identification The SMILES (Simplified Molecular Input Line Entry System) for the structures of Naloxone Hydrochloride (NHCl), Naloxone Palmitate (NP), Naloxone Stearate (NST), Naloxone Caprate (NDC), and Naloxone Caproate (NHC) were submitted to SwissADME and pkCSM to calculate physicochemical parameters such as lipophilicity, water solubility, heavy atoms, rotatable bonds, H-bond acceptors, H-bond donors as well as ADMET parameters like intestinal absorption, BBB penetration, and potential interaction with cytochrome P450 enzymes and P-glycoprotein (P-gp), identifying metabolic hotspots for enzymatic degradation, guiding modifications to enhance stability and prolong half-life, respectively. They also anticipated possible biological targets for drug, which helped to better understand their mechanism of action and possible side effects (Rauf et al. 2023 ). The parent drug's in silico ADMET properties were compared to its lipid conjugates to assess the impact of lipid conjugation on their pharmacokinetic profiles. Following the ADMET profiling of naloxone and its lipid derivatives, the investigation was expanded to assess potential toxicity concerns. This dual focus ensures that pharmacokinetic improvements do not compromise safety, which is an important consideration for clinical translation. 2.2 Toxicity Prediction ProTox uses the SMILES representation of drug and its lipid conjugates, to forecast the toxicity of Naloxone HCl and its lipid conjugates, providing insight into their potential safety profiles (Merdekawati 2018 ). The toxicity profile of naloxone and its lipid conjugates were evaluated by comparing the in silico ProTox predictions of parent drug with its lipid conjugates. 2.3 Molecular docking studies Molecular docking study assessed the binding affinity of naloxone and its lipid conjugates to the 5-HTR using SwissDock. The crystal structure of various receptor such as serotonin receptor : 5-HTR (4IAQ), human Toll Like Receptor 4 in complex with myeloid differentiation factor 2: human TLR4/MD2 (3FXI), and µ-opioid receptor (4DKL) was downloaded from the Protein Data Bank and the protein structure was prepared using AutoDockTools. Three-dimensional structures of naloxone and its lipid conjugates were created in ChemDraw and optimized in the MMFF94 force field. Docking simulations were conducted using SwissDock's web interface, which uses a stochastic global search algorithm to probe the ligand's conformational space within the receptor binding site. The top pose was chosen based on the best binding mode (Basu et al. 2020 ; Bugnon et al 2024 ). The binding affinities and interaction profiles were compared between naloxone and its lipid conjugates to evaluate the effect of lipid conjugation on receptor binding. 3 Results and Discussion: 3.1 ADMET Prediction 3.1.1 SwissADME SwissADME evaluated physicochemical properties of naloxone and its lipid conjugates (NP, NST, NDC, NHC). The predicted profile of naloxone and its lipid conjugates are displayed in Table 1 , revealing significant differences amongst compounds. Table 1 Physicochemical Properties Predicted using SwissADME Parameter Naloxone Naloxone Palmitate Naloxone Stearate Naloxone Caproate Naloxone Caprate Molecular Weight 327.37 565.78 593.84 425.52 481.62 Heavy Atoms 24 41 43 31 35 Rotatable Bonds 2 18 20 8 12 H-Bond Acceptors 5 6 6 6 6 H-Bond Donors 2 1 1 1 1 Log P (Lipophilicity) 1.88 7.12 7.81 3.48 4.92 Water Solubility Freely soluble Insoluble Insoluble Insoluble Insoluble As a result of conjugation with lipids, molecular weight and the number of heavy atoms increase significantly, indicating increased lipophilicity (Bhatia et al. 2021 ). Notably, the log P values for the NP and NST conjugates are significantly higher, due to longer fatty acid chain (Bishwas and Das 2025 ). Additionally, the number of rotatable bonds rises, which may have an impact on the stability and bioavailability of drugs (Gad et al. 2025 ). These features generally suggest that lipid conjugation can significantly alter the pharmacokinetic profile of naloxone. 3.1.2 PKCSM (Deep-PK) pkCSM (Deep-PK) assessed naloxone's pharmacokinetic profiles, focusing on ADME parameters, intestinal and BBB permeation. These predictions reveal how lipid conjugation enhances naloxone's therapeutic potential by altering its pharmacokinetic profile. 3.1.2.1 Absorption Characteristics a) Caco-2 Permeability and Intestinal Absorption The Caco-2 permeability data indicated similar logPaap values for naloxone and its lipid conjugates. Naloxone had a logPaap value of -4.91, and the conjugates showed similar values: NP, NST, NDC, and NHC, with no significant difference as displayed in Fig. 1 . Human intestinal absorption predictions demonstrated that all compounds, including unmodified naloxone, are predicted to be absorbed. Naloxone has the highest absorption probability, followed by NHC, NDC, NP, and NST. Longer-chain conjugates, like NP and NST, have slightly decreased absorption predictions due to increased molecular weight, longer fatty acid chain and steric hindrance (Kim et al. 2024 ; Jamatia et al. 2025 ). Even though the intestinal absorption and Caco-2 permeability predictions indicate similar uptake between naloxone and its lipid conjugates, the benefits of LDCs are found in their altered absorption pathways and lymphatic targeting potential. During intestinal digestion, due to the higher lipophilicity of conjugates, lipid-rich chylomicrons form in the intestinal fluid, redirecting absorption from the portal circulation to the lymphatic system and improving systemic bioavailability by avoiding hepatic first-pass metabolism. Through M-cell translocation and sustained release mechanisms, the nanosized LDCs further optimize lymphatic uptake. The "Absorbed" classification has persisted despite molecular changes because Caco-2 models, which measure passive transcellular permeability, do not record active lymphatic transport processes mediated by lipid-processing pathways. b) P-Glycoprotein Interactions As revealed in Table 2 , unmodified naloxone, NP, NST, and NHC are predicted to be non-inhibitor of P-gp, while NDC is predicted to be an inhibitor. NDC's P-gp inhibitory potential could significantly improve therapeutic outcomes by reducing the efflux of P-gp substrate drug, especially in combination therapies involving naloxone and other medications affected by P-gp-mediated efflux. Nonetheless, naloxone is predicted to be a non-substrate in P-gp substrate status, while all lipid conjugates are classified as P-gp substrates. The transition from non-substrate (naloxone) to substrate status in lipid conjugates suggests that fatty acid chains introduce structural features that enable interaction with P-gp's substrate-binding domains. This altered recognition profile may enhance efflux-mediated elimination and predispose to pharmacokinetic interactions with P-gp modulators. NDC's inhibitory activity could provide adjunct benefits in multidrug regimens by competitively inhibiting P-gp-mediated efflux of co-administered substrates. Differential P-gp interactions between naloxone and esters highlight structure-dependent modulation of transporter affinity (Guan et al. 2024 ; Subbaiah et al. 2024 ). Table 2 P-Glycoprotein Interaction of Naloxone and its Lipid Conjugates Parameter Probability & Interpretation Naloxone NP NST NDC NHC P-Glycoprotein Inhibitor 0 Non-Inhibitor (High Confidence) 0.051 Non-Inhibitor (High Confidence) 0.016 Non-Inhibitor (High Confidence) 0.706 Inhibitor (Medium Confidence) 0.19 Non-Inhibitor (Medium Confidence) P-Glycoprotein Substrate 0.376 Non-Substrate (Low Confidence) 0.779 Substrate (Medium Confidence) 0.817 Substrate (Medium Confidence) 0.636 Substrate (Low Confidence) 0.537 Substrate (Low Confidence) c) Skin Permeability The skin permeability data demonstrated significant differences among compounds, with naloxone showing a log KP value of -1.71 as revealed in Fig. 2 . NP and NST exhibited significantly increased values, indicating enhanced transdermal permeation, while NHC and NDC had slightly reduced permeability (Chakraborty et al. 2025 ). 3.1.2.2 Distribution Parameters a) Blood-Brain Barrier Penetration The prediction data indicates that NP and NST have higher logBB values, suggesting higher brain penetration compared to NDC, NHC and unmodified naloxone. Longer-chain fatty acids like palmitic and stearic acid may enhance BBB penetration, allowing for more efficient central action at lower systemic concentrations (Sarma et al. 2025 ). NHC and NDC have moderate logBB values, indicating sufficient brain penetration but possibly lower efficiency than NP and NST. Longer-chain fatty acid conjugates enhance BBB permeability by increasing lipophilicity and promoting integration into endogenous lipid transport mechanisms (Pifferi et al. 2021 ). b) Plasma Protein Binding and Unbound Fraction Plasma protein binding data showed low binding for all compounds, with percentages ranging from 48.73–58.88%, indicating poor protein binding as shown in Fig. 3 . It suggests a significant amount of the drug is unbound and available for therapeutic action, potentially increasing drug distribution and bioavailability, enhancing therapeutic efficacy. The fraction unbound in human plasma revealed more substantial variations, with higher unbound fractions for lipid conjugates suggesting increased availability for tissue distribution and pharmacological action compared to unmodified naloxone (Han et al. 2021 ). c) Volume of Distribution The steady-state volume of distribution (VDss) data of naloxone indicates its tissue distribution characteristics. For naloxone, VDss value is 1.69 L/kg, followed by NHC, NDC, NP, and NST as displayed in Fig. 4 . Naloxone's higher VDss indicates more extensive tissue distribution compared to its lipid conjugates, possibly due to increased molecular size and altered physicochemical properties of conjugates. The reduced VDss of lipid conjugates may result in higher plasma concentrations, potentially enhancing plasma-dependent pharmacological effects (Das and Das 2025 ; Roy et al. 2025 ). Despite lower tissue distribution, physicochemical modifications in lipid conjugates could potentially improve targeted delivery to CNS, enabling more efficient brain uptake and therapeutic action. Higher logBB values for NP and NST indicate improved brain penetration. 3.1.2.3 Metabolic Properties The metabolic profile of naloxone and its lipid conjugates revealed distinct patterns for naloxone and its lipid conjugates, impacting their metabolism and potential drug-drug interactions as demonstrated in Table 3 . Table 3 Metabolic Profile of Naloxone and Its Lipid Conjugates Parameter Probability & Interpretation Naloxone NP NST NDC NHC Breast Cancer Resistance Protein 0.091 Non-Inhibitor (High Confidence) 0.497 Non-Inhibitor (Low Confidence) 0.572 Inhibitor (Low Confidence) 0.284 Non-Inhibitor (Medium Confidence) 0.181 Non-Inhibitor (Medium Confidence) CYP 1A2 Inhibitor 0.008 Non-Inhibitor (High Confidence) 0.004 Non-Inhibitor (High Confidence) 0.003 Non-Inhibitor (High Confidence) 0.018 Non-Inhibitor (High Confidence) 0.015 Non-Inhibitor (High Confidence) CYP 1A2 Substrate 0.576 Substrate (Low Confidence) 0.289 Non-Substrate (Medium Confidence) 0.249 Non-Substrate (Medium Confidence) 0.43 Non-Substrate (Low Confidence) 0.52 Substrate (Low Confidence) CYP 2C19 Inhibitor 0.009 Non-Inhibitor (High Confidence) 0.006 Non-Inhibitor (High Confidence) 0.004 Non-Inhibitor (High Confidence) 0.025 Non-Inhibitor (High Confidence) 0.016 Non-Inhibitor (High Confidence) CYP 2C19 Substrate 0.537 Substrate (Low Confidence) 0.489 Non-Substrate (Low Confidence) 0.467 Non-Substrate (Low Confidence) 0.531 Substrate (Low Confidence) 0.52 Substrate (Low Confidence) CYP 2C9 Inhibitor 0.001 Non-Inhibitor (High Confidence) 0.026 Non-Inhibitor (High Confidence) 0.027 Non-Inhibitor (High Confidence) 0.018 Non-Inhibitor (High Confidence) 0.029 Non-Inhibitor (High Confidence) CYP 2C9 Substrate 0.296 Non-Substrate (Medium Confidence) 0 Non-Substrate (High Confidence) 0 Non-Substrate (High Confidence) 0 Non-Substrate (High Confidence) 0.008 Non-Substrate (High Confidence) CYP 2D6 Inhibitor 0.602 Inhibitor (Low Confidence) 0.883 Inhibitor (High Confidence) 0.579 Inhibitor (Low Confidence) 0.999 Inhibitor (High Confidence) 0.993 Inhibitor (High Confidence) CYP 2D6 Substrate 0.469 Non-Substrate (Low Confidence) 0.36 Non-Substrate (Low Confidence) 0.336 Non-Substrate (Low Confidence) 0.419 Non-Substrate (Low Confidence) 0.445 Non-Substrate (Low Confidence) CYP 3A4 Inhibitor 0.034 Non-Inhibitor (High Confidence) 0.563 Inhibitor (Low Confidence) 0.551 Inhibitor (Low Confidence) 0.614 Inhibitor (Low Confidence) 0.392 Non-Inhibitor (Low Confidence) CYP 3A4 Substrate 0.807 Substrate (Medium Confidence) 0.372 Non-Substrate (Low Confidence) 0.282 Non-Substrate (Medium Confidence) 0.608 Substrate (Low Confidence) 0.632 Substrate (Low Confidence) OATP1B1 0.09 Non-Inhibitor (High Confidence) 0.064 Non-Inhibitor (High Confidence) 0.04 Non-Inhibitor (High Confidence) 0.219 Non-Inhibitor (Medium Confidence) 0.253 Non-Inhibitor (Medium Confidence) OATP1B3 0.047 Non-Inhibitor (High Confidence) 0.43 Non-Inhibitor (Low Confidence) 0.475 Non-Inhibitor (Low Confidence) 0.262 Non-Inhibitor (Medium Confidence) 0.14 Non-Inhibitor (High Confidence) The metabolic profiles of naloxone and its lipid conjugates reveal their potential interaction with CYP enzymes and transporters. Naloxone is metabolised by CYP1A2 and CYP2C19 , indicating its susceptibility to these enzymes. However, its lipid conjugates have different levels of metabolic independence, with none being processed by CYP1A2 except NHC. However, they inhibit CYP2D6 , which may affect the metabolism of co-administered drugs. NP, NST and NDT also inhibit CYP3A4 , impacting the metabolism of drugs that are substrates of CYP3A4 . Strong inhibitory potential is shown by NDC, especially against CYP2D6 and CYP3A4 enzymes. However, the lack of inhibition of OATP1B1 and OATP1B3 transporters reduces the likelihood of transporter-related adverse effects, suggesting a favourable safety profile in this regard (Goyzueta-Mamani et al. 2025 ). Predicting the metabolism of compounds revealed that naloxone and its lipid conjugates have distinct interactions with metabolic transporters, including Breast Cancer Resistance Protein ( BCRP), Organic Anion Transporting Polypeptide 1B1 (OATP1B1) , and Organic Anion Transporting Polypeptide 1B3 (OATP1B3 Naloxone, NP, and NST, are non-inhibitors of OATP1B1 and OATP1B3 , thereby minimizing the potential for transporter-mediated drug-drug interactions (Costa et al. 2025; Kciuk et al. 2025 ; Othman et al. 2025 ). The structural changes brought about by lipid conjugation, which affect enzyme recognition and metabolism, are reflected in the metabolic properties of naloxone and its lipid conjugates. These variations highlight the necessity of evaluating the metabolic profile of each conjugate separately in order to precisely forecast pharmacokinetic behaviour and interaction risks. 3.1.2.4 Excretion Parameters a) Clearance The clearance data revealed significant differences between naloxone and its lipid conjugates, with naloxone displaying the highest clearance rate at 23.09 L/min, followed by NHC, NDC, NP, and NST as mentioned in Fig. 5 . This suggests that lipid conjugation significantly reduces naloxone's elimination rate. The reduction in clearance rate of lipid conjugate's is due to factors like increased lipophilicity, reduced renal filtration, and altered metabolism pathways. This is a key pharmacokinetic advantage, potentially resulting in prolonged systemic exposure and extended duration of therapeutic action, potentially enhancing tissue distribution and protein binding (Kalita et al. 2025 ). b) Renal Transporter Interactions The Organic Cation Transporter 2 (OCT2) interaction data indicates that naloxone is predicted to be an OCT2 inhibitor, while all lipid conjugates are classified as non-inhibitors. This suggests that lipid conjugation alters the molecular recognition by OCT2 , potentially affecting naloxone's renal secretion and interaction with co-administered drugs that are OCT2 substrates. The reduced OCT2 inhibitory potential of lipid conjugates may contribute to their altered clearance profile and reduce the risk of renal drug-drug interactions (Çevik et al. 2025 ). 3.1.2.5 Comprehensive Comparison of Individual Lipid Conjugates a) Naloxone Palmitate NP offers several pharmacokinetic advantages over unmodified naloxone. Its reduced clearance suggests extended systemic exposure, potentially resulting in prolonged therapeutic action. Its classification as a P-gp substrate may contribute to reduced elimination through P-gp-mediated efflux mechanisms. Its improved BBB penetration offers potential advantages. Moreover, the enhanced skin permeability of NP allows it to be absorbed via the transdermal route. NP's metabolic profile differs significantly from naloxone, with notable changes such as being classified as a non-substrate for CYP1A2 and CYP3A4 and enhanced inhibitory potential for CYP2D6 and CYP3A4 . These metabolic alterations could affect the compound's stability and drug-drug interactions. Therefore, NP is suitable for both oral and transdermal applications requiring sustained action. b) Naloxone Stearate NST has the most significant lipophilicity-related effects among the conjugates studied. NST indicated improved BBB penetration and reduced clearance, suggesting enhanced CNS targeting and prolonged systemic exposure. Its enhanced skin permeability suggests potential for transdermal delivery, allowing efficient absorption without permeation enhancers or specialized formulations. It also has the highest unbound fraction, indicating increased pharmacological action. NST is predicted to inhibit BCRP, potentially influencing the pharmacokinetics of BCRP substrate drugs and due to its high lipophilicity, making it a promising candidate for oral and transdermal delivery. c) Naloxone Caprate NDC offers a balanced approach to lipid conjugation, offering moderate improvements in pharmacokinetic parameters without the extreme shifts seen with longer-chain conjugates. Its intermediate clearance reduction suggests moderately extended systemic exposure, while its improved Caco-2 permeability indicates enhanced membrane permeation potential. NDC is predicted to be a P-gp inhibitor, which could have significant implications for co-administered drugs that are P-gp substrates. It also demonstrated the highest plasma protein binding percentage, which might contribute to its reduced clearance by limiting the fraction available for glomerular filtration. The metabolic profile of NDC includes inhibition of CYP2D6 and CYP3A4 , suggesting potential for metabolic drug-drug interactions in clinical applications. The compound showed improvement in both BBB penetration and intestinal absorption, indicating enhanced CNS delivery and oral bioavailability. d) Naloxone Caproate NHC offers modest improvements in selected pharmacokinetic parameters while preserving many characteristics of the parent compound. Its intermediate clearance reduction suggests moderately extended systemic exposure, while its maintained intestinal absorption probability indicates preserved absorption properties. NHC maintains substrate status for CYP1A2 , suggesting preserved metabolic pathways, but showed enhanced CYP2D6 inhibitory potential, indicating potential for specific metabolic drug-drug interactions. Its plasma protein binding percentage is the lowest among all compounds, suggesting slightly enhanced free fraction available for pharmacological action. 3.1.2.6 Therapeutic Implications Lipid conjugation of naloxone with fatty acids provides several pharmacokinetic and pharmacodynamic advantages. Conjugates facilitate longer durations of therapeutic action than naloxone, providing relief against pain attacks and other life-threatening opioid effects. They have potential for oral delivery for migraine, neuroinflammation, and opioid toxicity treatment. These compounds have potential for BBB penetration, implying better CNS targeting and allowing for lower effective doses with fewer peripheral side effects. The increased lipophilicity of lipid conjugates allows for better diffusion across biological membranes. The ester linkage between naloxone and fatty acids is rapidly hydrolysed by enzyme, allowing the active compound to be released at target site, potentially improving therapeutic specificity and duration of action. Lipid conjugation also alters recognition by metabolic enzymes and transporters, potentially enhancing bioavailability. These modifications make lipid-based delivery systems more feasible, potentially optimising pharmacokinetic parameters and therapeutic performance. Their pharmacodynamic interactions with migraine-relevant targets, such as serotonin, toll-like and opioid receptors as well as other therapeutic targets, were further investigated to confirm their therapeutic utility. 3.2 Target Prediction and Pharmacodynamic Effects Along with opioid receptors, naloxone does interact with receptors and enzymes outside the opioid system, making it potential for migraine treatment and other neurological and/or physiological disorders. Its activity in pain modulation pathways, neuroinflammation, vascular function, and neurotransmitter regulation is significant in migraine pathophysiology. Table 4 summarized predicted target and pharmacodynamic action of naloxone and its lipid derivatives based on migraine relief and therapeutic potential. Table 4 Predicted Target and Pharmacodynamic Action Naloxone and its Lipid Derivatives Target Common Name Target Class Pharmacodynamic Effect Probability NHC NP NSt NDC NHC Mu opioid receptor GPCR Modulates pain pathways and central sensitization; potential role in migraine pain relief (Wang and Thyagarajan 2022 ) 0.9713 0.3597 0.4688 0.7917 0.7866 Delta opioid receptor GPCR Regulates analgesia, mood, and inflammatory responses; possible anti-migraine effects (El Daibani and Pradhan 2025 ) 0.9713 0.3597 0.4688 0.7917 0.7866 Kappa opioid receptor GPCR Influences nociception, stress, and inflammation; potential in migraine and chronic pain (Weng 2024 ) 0.9713 0.3597 0.4688 0.7743 0.7866 Cytochrome P450 2D6 Enzyme Metabolizes drugs and neurotransmitters; could influence efficacy of migraine treatments (Yamoune et al. 2025 ) 0.9713 0.2259 0.296 0.4075 0.3441 Adenosine A3 receptor GPCR Anti-inflammatory, neuroprotective, and vasomodulatory effects relevant to migraine (Silvestro et al. 2023 ) 0.9713 0.2259 0.1715 0.3638 0.2958 C-C chemokine receptor type 5 (CCR5) GPCR Modulates immune response and neuroinflammation; may play a role in neurogenic inflammation in migraine (Sudershan et al. 2023 ) 0.9713 0.11 0.162 0.3462 0.4326 Toll-like receptor 4 Toll-like receptor Regulates neuroinflammation and pain sensitization, making it a target for migraine and neurodegenerative disorders (Saleki et al. 2024 ) 0.2096 0.1457 0.1809 0.1892 0.2556 HERG (hERG KCNH2) Ion channel Regulates cardiac repolarization; inhibition can reduce migraine-associated cardiovascular risks (Rouhana et al. 2021 ) 0.1047 0.0744 0.0661 0.1106 0.1189 Sigma opioid receptor Membrane receptor Modulates stress response, addiction, and neuroprotection; potential relevance in migraine-related stress triggers (Zorrilla 2024 ) 0.1047 0 0.0661 0.1106 0.1189 Nociceptin receptor GPCR Inhibits pain transmission and modulates migraine pathways (Kavya et al. 2025 ) 0.1047 0.0744 0.0661 0.1106 0.1189 Cholecystokinin B receptor GPCR Involved in anxiety, pain, and digestion; may contribute to migraine-associated nausea and sensory hypersensitivity (Aczél 2022 ) 0 0.0744 0.0661 0.1106 0.1189 Beta-3 adrenergic receptor GPCR Regulates vascular tone and metabolism; potential target for migraine and metabolic disorders (Read et al. 2025 ) 0 0.0744 0 0.1106 0.1189 Serotonin 2a (5-HT2a) receptor GPCR Affects mood, vasoconstriction, and cortical spreading depression, key factors in migraine pathophysiology (Sakeer et al. 2024) 0.1047 0 0 0 0.1189 Receptor protein-tyrosine kinase erbB-2 Kinase Involved in neuronal plasticity and pain sensitization; potential role in chronic migraine (Giraud et al. 2021 ) 0 0.0744 0 0.1106 0.1189 Epidermal growth factor receptor erbB1 Kinase Implicated in neuroprotection and pain regulation; potential relevance in migraine-associated neuroinflammation (Vellapandian 2023 ) 0 0 0 0.1106 0.1189 Serotonin 4 (5-HT4) receptor GPCR Modulates neuronal excitability and gut motility, linking it to migraine-associated gastric symptoms (Guerrero 2019 ) 0.1047 0 0 0.1106 0.1189 Opioid growth factor receptor-like protein 1 Unclassified protein Regulates neuroimmune functions and nociception, making it relevant to migraine treatment (Jayathilake et al. 2025 ) 0.1047 0.0744 0.0661 0.1106 0.1189 Matrix metalloproteinase 9 (MMP9) Protease Involved in BBB permeability and neuroinflammation, key factors in migraine pathogenesis (Curry-Koski et al. 2025 ) 0 0.0744 0 0.1106 0.1189 Phosphodiesterase 10A Enzyme Regulates dopamine signalling ; may play a role in migraine and psychiatric comorbidities (Barbagallo et al. 2024 ) 0.1047 0 0 0.1106 0.1189 Thrombin (Factor IIa, F2) Protease Involved in coagulation and vascular dysfunction, potential risk factor for migraine-associated stroke (Hassan et al. 2021 ) 0 0 0 0.1106 0.1189 Tyrosine-protein kinase JAK2 Kinase Plays a role in immune response regulation; possible link to neuroinflammatory migraine mechanisms (Kohandel et al. 2021 ; Krämer et al. 2023 ) 0 0 0 0.1106 0.1189 Histone deacetylase 3 Epigenetic regulator Modulates gene expression and neuronal plasticity; potential migraine and neurodegeneration target (Gazerani 2024 ) 0 0 0 0.1106 0.1189 Melanin-concentrating hormone receptor 1 GPCR Regulates appetite and circadian rhythms, possibly linked to migraine-triggering factors (Goadsby et al. 2017 ; Stanyer 2023 ) 0 0 0 0.1106 0.1189 Predicted target profiles and pharmacodynamic actions of naloxone hydrochloride (NHC) and its lipid derivatives, naloxone palmitate (NP), naloxone stearate (NSt), naloxone caprate (NDC), and naloxone caproate (NHC), showed notable differences that could affect their therapeutic potential, particularly in the treatment of migraine and related neuroinflammatory conditions. Naloxone and its lipid conjugates can bind to the three major opioid receptors (mu (OPRM1), delta (OPRD1), and kappa (OPRK1)) (Rushendran and Chitra 2024 ). Its well-known function as a potent opioid antagonist, modulating pain pathways and central sensitization, both of which are required for migraine pain relief, is supported by its affinity for opioid receptors (Li et al. 2023 ). In addition to opioid receptors, NHC has a high predicted affinity for adenosine A3 and cytochrome P450 2D6 (CYP2D6) receptors, which are linked to neuroinflammation and drug metabolism, respectively. Notably, NP and NDC exhibit a moderate affinity for phosphodiesterase 10A (PDE10A), an enzyme that controls dopamine signaling and is connected to symptoms of migraines like photophobia and nausea (Villar-Martinez and Goadsby 2022 ; Rushendran et al. 2023 ; El-Naggar et al. 2025 ). All compounds are predicted to target the immune-modulatory receptors CCR5 and toll-like receptor 4 (TLR4) (Ciechanowska and Mika 2024 ). Given TLR4's role in neuroinflammation and pain sensitization, this suggests that naloxone and its lipid conjugates could effectively regulate neuroinflammatory cascades implicated in migraine pathophysiology (Babu et al. 2024 ; Sharma et al. 2024 ). Differential affinities are also seen in ion channels and other receptors linked to neurological and cardiovascular functions (Cuciureanu et al. 2024 ). For example, all compounds weakly target the hERG potassium channel, which controls cardiac repolarization and may affect cardiovascular risks associated with migraines, but NDC and NHC target it slightly more. Similarly, sigma opioid receptors, which regulate neuroprotection and stress response to migraine triggers, exhibit weak binding in NP and NSt and a low but noticeable affinity in NDC and NHC. Serotonin receptors, particularly 5-HT2a and 5-HT4, are important in migraine due to their roles in vasoconstriction, cortical spreading depression, and gastrointestinal symptoms (Borończyk et al. 2025 ). Naloxone shows an affinity for these receptors. This suggests that naloxone may have a broader impact on serotonergic pathways implicated in migraine aura and associated symptoms. Other targets specific to lipid conjugates are matrix metalloproteinase 9 (MMP9), which is predicted to be bound by NP and NDC and is involved in neuroinflammation and blood-brain barrier permeability (Bhatia et al. 2025 ). This could have a positive impact on migraine control by stabilizing the blood-brain barrier and lowering neurovascular inflammation (Savvidou et al. 2025 ). Likewise, kinases implicated in immunological regulation and neuroprotection, including JAK2 and epidermal growth factor receptor (EGFR), exhibit increased predicted affinity in NDC, indicating additional neuroprotective advantages (Fu and Liu 2023 ; Panda et al. 2024 ). NP is predicted to bind to ceramide glucosyltransferase , an enzyme vital for glycosphingolipid synthesis, which may impact inflammation and pain mechanisms in migraines (Liu et al. 2025 ). It is also predicted to bind to smoothened homolog, a key element in the Hedgehog signalling pathway, which influences cell growth, differentiation, and tissue patterning, potentially influencing neurogenesis and inflammation (Parashar et al. 2024 ). Aside from migraine, NP's preference for VEGFRs, beta-3 adrenergic receptors , and epidermal growth factor receptor points towards uses in metabolic disease, cardiovascular disease, and neurodegeneration (Sheikh et al. 2024 ; Islam et al. 2025 ; Miliotou et al. 2025 ). NSt's effects on Histone deacetylase 3 and vascular growth factors imply therapeutic advantages in neurodegenerative diseases, vascular disease, and chronic pain disorders (Costanzo et al. 2025 ). Apart from migraine, the interactions of NHC with PI3K signal pathways, VEGFRs , and Histone deacetylase 3 confer neuroprotective and metabolic regulating effects, giving it applicability in aging-linked cognitive impairment, epilepsy, and metabolic disorders (de la Monte 2023 ). Thus, lipid conjugates may provide a more comprehensive modulation of migraine-related symptoms like anxiety and metabolic dysfunction. Overall, the evidence points to naloxone hydrochloride's primary mechanisms of action as strong opioid receptor antagonist and serotonergic and neuroimmune pathway modulation, which enables it to effectively reduce acute migraine pain and control neuroinflammation. By contrast, the lipid conjugates exhibit a varied pharmacodynamic profile, exhibiting significant binding affinity to opioid receptors, increased interaction with immune receptors, enzymes, and signaling pathways linked to neuroinflammation, the integrity of the blood-brain barrier, and the regulation of neurotransmitters. By focusing on underlying pathophysiological mechanisms other than opioid receptor blockade, this change may offer benefits in the treatment of chronic migraines. Furthermore, there may be a chance for better symptom management in migraine subtypes marked by neurovascular dysfunction and sensory hypersensitivity due to the lipid conjugate's anticipated modulation of dopamine signaling, BBB permeability factors, and stress-related receptors. Their potential neuroprotective and metabolic advantages are further highlighted by their interaction with kinases and growth factor receptors, broadening their therapeutic range to include co-morbid conditions like stroke risk and neurodegeneration. While therapeutic efficacy of developed compounds depends on target engagement, safety is the key to the viability for clinical translational. Therefore, to ensure that improved pharmacokinetics and receptor binding do not present unanticipated risks, the following section elucidates the toxicity profiles of these derivatives. 3.3 Toxicity Analysis ProTox was employed to examine the predicted patterns of toxicity for naloxone and its lipid conjugates as shown in Table 5 . Table 5 Toxicity Analysis Naloxone and its Lipid Conjugates Endpoint Naloxone and its Lipid Conjugates Organ Toxicity Hepatotoxicity Inactive Neurotoxicity Inactive Nephrotoxicity Inactive Respiratory Toxicity Active Cardiotoxicity Inactive Metabolism CYP1A2 Inactive CYP2C19 Inactive CYP2C9 Inactive CYP2D6 Active CYP3A4 Inactive CYP2E1 Inactive At the organ level, ProTox predicted that all compounds, including naloxone and its lipid conjugates, are expected to be inactive for hepatotoxicity, neurotoxicity, nephrotoxicity, and cardiotoxicity. However, all compounds are predicted to be active for respiratory toxicity, as respiratory depression is a recognized toxic effect of opioid overdose. All compounds are predicted to be inactive for carcinogenicity, mutagenicity, and ecotoxicity, indicating no significant risks. Preclinical data demonstrating naloxone's protective effects against opioid-induced hepatic damage, as demonstrated by histopathological improvements in animal models despite unchanged serum biomarkers, is consistent with hepatotoxicity predictions of inactivity. Clinical data for naloxone supports neurotoxicity predictions, wherein adverse neurological events (rare seizures in 4% of cases, transient confusion in 20% of cases) are expected pharmacological reversal effects rather than intrinsic neurotoxicity. Although there are no cardiotoxic events reported in paediatric studies, cardiovascular assessments show predictable dose-dependent responses, including transient tachycardia (4–6% incidence) and isolated case reports of hypertension/pulmonary edema in adults (Wermeling 2015 ; Rzasa and Galinkin 2018; USFDA Label, Accessed 02 January 2025). This integrated analysis positions lipid-conjugated naloxone derivatives as promising candidates with manageable safety profiles for migraine treatment applications. After establishing favourable safety, pharmacokinetic profiles, and potential targets for naloxone and its lipid conjugates, the next section examines the structural basis of receptor interactions. This clarifies how lipid conjugation alters binding affinities for 5-HTR, TLR4, and µ-opioid receptors for the treatment of migraine. 3.4 Molecular docking studies Molecular docking experiments were conducted to analyse the binding affinity of naloxone and its lipid conjugates against three key migraine pathophysiological receptors: 5-HTR , TLR4 , and µ-opioid receptor (Eberhardt et al. 2021 ; Bugnon et al. 2024 ). Table 6 demonstrated that all compounds, including naloxone and lipid conjugates, exhibited strong binding affinities (≤ -4.0 kcal/mol) against these receptors, indicating their potential therapeutic use in migraine treatment. Table 6 Binding Affinity of compounds with Target Receptors Compounds Target Receptor 5HT TL4 Opioid receptor NHCl -5.937 to -3.646 -6.550 to -5.116 -6.015 to -3.138 NP -4.909 to -3.512 -5.406 to -2.768 -5.821 to -4.204 NST -4.231 to -2.996 -5.680 to -2.824 -5.435 to -3.039 NDC -5.298 to -3.256 -6.539 to -4.516 -6.028 to -3.401 NHC -5.74 to -3.756 -6.359 to -4.546 -5.562 to -3.867 5-HTR is a well-documented target in migraine treatment, with triptans functioning as selective agonists at 5-HT1B/1D receptors to treat migraine. Naloxone and its lipid conjugates, effectively interact with 5-HTR s as displayed in Fig. 6 (a), modulating serotonergic pathways within migraine attacks (Pehlivanlar et al. 2024 ). The Table 5 indicates that naloxone and its lipid conjugates can effectively treat migraines by binding with 5-HTR . Alongside, TLR4 receptor plays key role in migraine-related neuroinflammation, causing mast cell degranulation and trigeminal nerve sensitization (Soylu et al. 2025 ). Naloxone and its lipid conjugates have high binding affinity for TLR4 , suggesting lipid conjugation doesn't impair TLR4 recognition (Fig. 6 (b)), suggesting potential anti-inflammatory effects to counter migraine pain. Likewise, the µ- opioid receptor is a target of interest in chronic migraine patients, who tend to have altered endogenous opioid neurotransmission during an attack (García-Domínguez 2024 ). Naloxone and its lipid conjugates have the optimum binding affinity (Fig. 6 (c)), suggesting they modulate opioid signalling pathways involved in pain processing. Thus, the molecular docking data showed that naloxone and its lipid conjugates are effective for migraine treatment due to their optimal binding affinities towards serotonin, TLR4, and µ-opioid receptors . These compounds can rectify pain modulation, neuroinflammation, and serotonergic dysregulation. Yet, further in vitro and in vivo investigations are needed to confirm these predictions and enhance their use as targeted drugs for migraine patients. 4. Conclusion The study presents a promising in silico investigation on naloxone as repurposed drug for migraine treatment. Selective conjugation of naloxone with lipid groups has led to the discovery of novel derivatives exhibiting enhanced pharmacokinetics and enhanced affinity for the serotonin, toll-like, and µ-opioid receptor , a crucial target in migraine pathophysiology, highlighting the potential of naloxone and its lipid conjugates for migraine treatment. The computational simulations revealed that lipid conjugates significantly alter pharmacokinetic parameters, resulting in prolonged duration of therapeutic effect and enhancing naloxone brain delivery, by altering its physicochemical parameters. Naloxone and its lipid conjugates are effective for migraine treatments due to their optimal binding affinity to serotonin, toll-like, and µ-opioid receptors , resolving pain modulation, neuroinflammation, and serotonergic dysregulation, providing an avenue for targeted intervention into migraine mechanisms. The results are based on in silico results, which are a basis for future experimental verification. Follow-up in vitro and in vivo investigations are necessary to establish the BBB permeability, metabolic stability, and receptor binding profiles of these conjugates. Clinical trials are needed to establish the efficacy and safety of these compounds in migraine patients. This investigation underscores the potential of drug repurposing and rational design in unmet medical needs. 5. Future Perspectives The study confirms the use of naloxone lipid conjugates for migraine treatment, indicating altered pharmacokinetic parameters, allowing for prolonged duration of therapeutic action, and targeting 5-HTR, TLR4, and mu-opioid receptors. However, further experimental evidence is needed to validate these findings and drive the repurposing approach towards clinics. In vitro investigation is needed to characterize the BBB permeability and metabolic stability of lipid conjugates synthesized through cell-based assays (Eltanameli et al. 2024 ) and enzymatic models of degradation (Lee et al. 2024 ). This will provide insights into the compound's potential for brain penetration and circulating half-life, as well as verify their binding with 5-HTR subtypes involved in migraine. Lead candidates identified from in vitro screens should be evaluated in vivo with animal models of migraine to measure their effectiveness against migraine behaviour, determine their pharmacokinetic profiles, and assess their therapeutic window. Safety and tolerability determinations are also necessary for these novel compounds. Present exploration suggests that rational drug design, lipid conjugation, and targeting the BBB can be applied to other repurposed medications and neurological diseases, potentially improving the delivery and effectiveness of migraine drugs or identifying new therapeutic targets. Utilizing advanced computational modelling methodologies like molecular dynamics simulations (Cordeiro et al. 2024; Park et al. 2024 ; Kaur et al. 2025 ) and machine learning can improve the design of lipid conjugates, predict their interaction with biological systems, and enhance understanding of action mechanisms, ultimately improving the pharmacological features of these drugs (Sharma et al. 2025 ; Gülave et al. 2025 ). The translation of research into clinical settings relies on creating safe, effective, and commercially available naloxone lipid conjugates. Future research should focus on process optimization, clinical trials, and patient compliance optimization. Combining computational design, experimental verification, and clinical translation will unlock therapeutic benefits and redefine migraine treatment. Abbreviations 5-HTR: Serotonin Receptor BBB: Blood-Brain Barrier BCRP: Breast Cancer Resistance Protein CNS: Central Nervous System MMP9: Matrix metalloproteinase 9 NDC: Naloxone Caprate NHC: Naloxone Caproate NHCl: Naloxone Hydrochloride NP: Naloxone Palmitate NST: Naloxone Stearate OCT2: The Organic Cation Transporter 2 P-gp: P-glycoprotein TLR4: Toll-like Receptor 4 VDss: Volume of Distribution Declarations Acknowledgements: The authors gratefully acknowledge the support of their respective institutions. This research was supported by the Prime Minister’s Fellowship. The funding body had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Compliance with Ethical Standards: This article does not contain any studies with human participants or animals performed by any of the authors. Competing Interests and Funding: The authors declare that they have no known competing interests that could have influenced the work reported in this paper. The authors gratefully acknowledge the support of their respective institutions. This research was supported by the Prime Minister’s Fellowship. The funding body had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Author Contributions: All authors have equally contributed to this research work. All authors have read and approved the final manuscript. References Aczél T. (2022) Mechanisms of trigeminal activation and sensitisation: implications for migraine pathophysiology (Doctoral dissertation, University of Pécs (Hungary)). Babu N, Gadepalli A, Akhilesh, Sharma D, Singh AK, Chouhan D, Agrawal S, Tiwari V. (2024) TLR-4: a promising target for chemotherapy-induced peripheral neuropathy. Mol. Biol. 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12:53:14","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6687113/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6687113/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91409777,"identity":"1783e395-a591-43a7-929a-f685e1c15d09","added_by":"auto","created_at":"2025-09-16 08:26:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":21847,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e(a) Cacco-2 Permeability and (b) Intestinal Permeability Prediction of Naloxone and its Lipid Conjugates\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6687113/v1/6934ddf1dd35ba128a924edf.png"},{"id":91409778,"identity":"135b1e60-7163-448e-9527-1c79d1008d2f","added_by":"auto","created_at":"2025-09-16 08:26:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":10017,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSkin Permeability of Naloxone and its Lipid Conjugates\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6687113/v1/c7746a150ad241e42bfcf218.png"},{"id":91409781,"identity":"9d50b22d-f398-48c1-bae9-602524499f87","added_by":"auto","created_at":"2025-09-16 08:26:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":11000,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePlasma Protein Binding of Naloxone and its Lipid Conjugates\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6687113/v1/0278f878c4a7a77f37607a6e.png"},{"id":91411282,"identity":"0e869bc1-0849-4668-ab56-c287e2270351","added_by":"auto","created_at":"2025-09-16 08:42:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":10416,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eVDss of Naloxone and its Lipid Conjugates\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6687113/v1/6c8de27fa3d8537109635af9.png"},{"id":91410113,"identity":"47d6ec2e-02c2-4d78-8cea-8e63686553dc","added_by":"auto","created_at":"2025-09-16 08:34:56","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":10701,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eClearance Rate of Naloxone and its Lipid Conjugates\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6687113/v1/2941a9face7ffb295f440894.png"},{"id":91411285,"identity":"c82c2b42-ada2-4623-bbe4-e6c2eec1fb9c","added_by":"auto","created_at":"2025-09-16 08:42:57","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2035031,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular Docking of Target Receptors: a) 5-HT b) TL4 c) Opioid receptor\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6687113/v1/8b62cb17d54738907d68b29e.jpeg"},{"id":92807928,"identity":"6b09ce06-676a-41b5-8114-664476b9943d","added_by":"auto","created_at":"2025-10-05 14:31:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3891230,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6687113/v1/17b115fa-7f5c-4d6b-8e7e-3c5923233f2d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"In Silico Evaluation of Lipid-Drug Conjugates: Pharmacokinetic and Pharmacodynamic Profiling for Therapeutic Repurposing of Naloxone in Migraine Management","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eMigraine, a prevalent neurological disorder affecting 14% of adults worldwide, significantly impacts quality of life, productivity, and healthcare utilization. Current treatments focus on acute relief or reducing migraine frequency, but many patients experience insufficient relief or severe side effects, highlighting the need for new, more effective therapies (Peres et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Drug repurposing is a promising approach for rapid therapeutic development, leveraging the safety profiles and pharmacokinetic properties of known drugs. Naloxone, an opioid antagonist, has been identified as a potential migraine treatment due to its potential to modulate pain pathways and inflammatory processes involved in migraine pathophysiology, reducing the time and expenses required for new treatments to enter the market (Nicolodi and Sicuteri \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Burgess \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Moreover, reported research suggests that \u003cem\u003eToll-like receptor 4\u003c/em\u003e (\u003cem\u003eTLR4\u003c/em\u003e) plays a role in neuroinflammation and pain processing in the trigeminovascular system, a central region in migraine pathophysiology. Naloxone has been shown to effectively treat migraine attacks, with recent findings suggesting that both opioid-active and inactive isomers of naloxone inhibit \u003cem\u003eTLR4\u003c/em\u003e receptor action (Ramachandran et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNaloxone's clinical effectiveness in migraine is limited by its poor oral bioavailability, poor blood-brain barrier (BBB) penetration, rapid metabolism, and short half-life, necessitating frequent administration and parenteral administration; therefore, it is critical to improve its therapeutic levels to reach the central nervous system (CNS) (Naloxone: DrugBank Online Accessed 15 April 2025). The present study explored rational drug design using naloxone lipid conjugation, aiming to overcome limitations and improve pharmacokinetic profiles of naloxone by esterifying it using fatty acids. Lipid-drug conjugates (LDCs) are a revolutionary approach to bypass the limitations of traditional drug formulations by increasing the lipophilicity of drug through covalent attachment to lipids. This enhances stability and bioavailability, reduces the rate of clearance and facilitates targeted delivery to receptors. LDCs also exploit endogenous lipid transport systems to promote lymphatic uptake by avoiding hepatic metabolism and provide sustained release to maintain therapeutic plasma concentrations. Strategic use of labile linkers protects against off-target toxicity. Synthesising naloxone lipid conjugates may increase its repurposing potential by streamlining pharmacokinetic parameters without losing pharmacodynamic activity at migraine-relevant targets. This approach allows for a carrier-free system, simplifying formulation and enhancing therapeutic outcomes. It is anticipated that naloxone's lipid conjugation will improve its BBB permeability, metabolic stability, and interaction with target molecular species in the brain (Mohapatra and Dash \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Talele et al. \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cem\u003eIn silico\u003c/em\u003e modelling allows for precise prediction of conjugate behaviour, enabling rapid rational LDC design for neurological use. The present investigation used \u003cem\u003ein silico\u003c/em\u003e modelling to analyze absorption, distribution, metabolism, excretion and toxicity (ADMET) profiles and \u003cem\u003eserotonin receptor (5-HTR), TLR4\u003c/em\u003e and \u003cem\u003e\u0026micro;-opioid receptor\u003c/em\u003e binding activities of lipid conjugates of naloxone. The physicochemical, pharmacokinetic and pharmacodynamic characteristics of these compounds were predicted using computational tools such as SwissADME (SwissADME Accessed 10 January 2025), pkCSM (Deep-PK Accessed 24 January 2025), ProTox (Banerjee et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and molecular docking (SwissDock) (SwissDock Accessed 15 January 2025). SwissADME is a web-based tool that predicts physicochemical properties, drug-likeness, and medicinal chemistry friendliness of small molecules. It offers various predictive models, making it an effective tool for predicting ADMET profiles of drug and their conjugates (Daina et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). SwissADME employs models like the ESOL model and SILICOS-IT method to predict physicochemical properties, classifying it on a log scale, providing insights into the solubility of drug and its conjugates in aqueous media, lipophilicity, reactivity, etc. (Dascălu et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). pkCSM uses graph-based signatures to predict ADME properties from molecular structure, predicting pharmacokinetic endpoints like volume of distribution, clearance rates, renal excretion capacity, and metabolic stability. It also predicts toxicity endpoints like hepatotoxicity and mutagenicity to prevent undesirable effects from lipid conjugation ( Pires et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Velloso et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Similarly, ProTox is a machine learning-based tool that predicts the toxicity of small molecules, including acute oral toxicity, essential for drug safety assessment, using machine learning-based algorithms. The study explores the potential of naloxone as an agent for migraine treatment, followed by the computational methodologies used to evaluate its lipid conjugates, assessing pharmacokinetic, toxicological, and receptor-binding properties for optimal brain delivery and therapeutic efficacy.\u003c/p\u003e"},{"header":"1. Methods for Predictions","content":"\u003cp\u003eSwissADME, SwissDock, Deep-PK and ProTox were utilized to predict the physicochemical properties, pharmacokinetic profiles, pharmacodynamic properties, identify target and safety of Naloxone and its lipid conjugates.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 ADMET Prediction and Target Identification\u003c/h2\u003e\u003cp\u003eThe SMILES (Simplified Molecular Input Line Entry System) for the structures of Naloxone Hydrochloride (NHCl), Naloxone Palmitate (NP), Naloxone Stearate (NST), Naloxone Caprate (NDC), and Naloxone Caproate (NHC) were submitted to SwissADME and pkCSM to calculate physicochemical parameters such as lipophilicity, water solubility, heavy atoms, rotatable bonds, H-bond acceptors, H-bond donors as well as ADMET parameters like intestinal absorption, BBB penetration, and potential interaction with cytochrome P450 enzymes and P-glycoprotein (P-gp), identifying metabolic hotspots for enzymatic degradation, guiding modifications to enhance stability and prolong half-life, respectively. They also anticipated possible biological targets for drug, which helped to better understand their mechanism of action and possible side effects (Rauf et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The parent drug's \u003cem\u003ein silico\u003c/em\u003e ADMET properties were compared to its lipid conjugates to assess the impact of lipid conjugation on their pharmacokinetic profiles. Following the ADMET profiling of naloxone and its lipid derivatives, the investigation was expanded to assess potential toxicity concerns. This dual focus ensures that pharmacokinetic improvements do not compromise safety, which is an important consideration for clinical translation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Toxicity Prediction\u003c/h2\u003e\u003cp\u003eProTox uses the SMILES representation of drug and its lipid conjugates, to forecast the toxicity of Naloxone HCl and its lipid conjugates, providing insight into their potential safety profiles (Merdekawati \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The toxicity profile of naloxone and its lipid conjugates were evaluated by comparing the \u003cem\u003ein silico\u003c/em\u003e ProTox predictions of parent drug with its lipid conjugates.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Molecular docking studies\u003c/h2\u003e\u003cp\u003eMolecular docking study assessed the binding affinity of naloxone and its lipid conjugates to the \u003cem\u003e5-HTR\u003c/em\u003e using SwissDock. The crystal structure of various receptor such as \u003cem\u003eserotonin receptor\u003c/em\u003e: \u003cem\u003e5-HTR\u003c/em\u003e (4IAQ), \u003cem\u003ehuman Toll Like Receptor 4\u003c/em\u003e in complex with \u003cem\u003emyeloid differentiation factor 2: human TLR4/MD2\u003c/em\u003e (3FXI), and \u003cem\u003e\u0026micro;-opioid receptor\u003c/em\u003e (4DKL) was downloaded from the Protein Data Bank and the protein structure was prepared using AutoDockTools. Three-dimensional structures of naloxone and its lipid conjugates were created in ChemDraw and optimized in the MMFF94 force field. Docking simulations were conducted using SwissDock's web interface, which uses a stochastic global search algorithm to probe the ligand's conformational space within the receptor binding site. The top pose was chosen based on the best binding mode (Basu et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Bugnon et al \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The binding affinities and interaction profiles were compared between naloxone and its lipid conjugates to evaluate the effect of lipid conjugation on receptor binding.\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Results and Discussion:","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 ADMET Prediction\u003c/h2\u003e\n \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.1 SwissADME\u003c/h2\u003e\n \u003cp\u003eSwissADME evaluated physicochemical properties of naloxone and its lipid conjugates (NP, NST, NDC, NHC). The predicted profile of naloxone and its lipid conjugates are displayed in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, revealing significant differences amongst compounds.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePhysicochemical Properties Predicted using SwissADME\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNaloxone\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNaloxone Palmitate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNaloxone Stearate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNaloxone Caproate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNaloxone Caprate\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMolecular Weight\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e327.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e565.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e593.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e425.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e481.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeavy Atoms\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRotatable Bonds\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eH-Bond Acceptors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eH-Bond Donors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLog P (Lipophilicity)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eWater Solubility\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFreely soluble\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInsoluble\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInsoluble\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInsoluble\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInsoluble\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eAs a result of conjugation with lipids, molecular weight and the number of heavy atoms increase significantly, indicating increased lipophilicity (Bhatia et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Notably, the log P values for the NP and NST conjugates are significantly higher, due to longer fatty acid chain (Bishwas and Das \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). Additionally, the number of rotatable bonds rises, which may have an impact on the stability and bioavailability of drugs (Gad et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). These features generally suggest that lipid conjugation can significantly alter the pharmacokinetic profile of naloxone.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.2 PKCSM (Deep-PK)\u003c/h2\u003e\n \u003cp\u003epkCSM (Deep-PK) assessed naloxone\u0026apos;s pharmacokinetic profiles, focusing on ADME parameters, intestinal and BBB permeation. These predictions reveal how lipid conjugation enhances naloxone\u0026apos;s therapeutic potential by altering its pharmacokinetic profile.\u003c/p\u003e\n \u003cdiv id=\"Sec10\" class=\"Section4\"\u003e\n \u003ch2\u003e3.1.2.1 Absorption Characteristics\u003c/h2\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003ea) Caco-2 Permeability and Intestinal Absorption\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eThe Caco-2 permeability data indicated similar logPaap values for naloxone and its lipid conjugates. Naloxone had a logPaap value of -4.91, and the conjugates showed similar values: NP, NST, NDC, and NHC, with no significant difference as displayed in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eHuman intestinal absorption predictions demonstrated that all compounds, including unmodified naloxone, are predicted to be absorbed. Naloxone has the highest absorption probability, followed by NHC, NDC, NP, and NST. Longer-chain conjugates, like NP and NST, have slightly decreased absorption predictions due to increased molecular weight, longer fatty acid chain and steric hindrance (Kim et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e; Jamatia et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). Even though the intestinal absorption and Caco-2 permeability predictions indicate similar uptake between naloxone and its lipid conjugates, the benefits of LDCs are found in their altered absorption pathways and lymphatic targeting potential. During intestinal digestion, due to the higher lipophilicity of conjugates, lipid-rich chylomicrons form in the intestinal fluid, redirecting absorption from the portal circulation to the lymphatic system and improving systemic bioavailability by avoiding hepatic first-pass metabolism. Through M-cell translocation and sustained release mechanisms, the nanosized LDCs further optimize lymphatic uptake. The \u0026quot;Absorbed\u0026quot; classification has persisted despite molecular changes because Caco-2 models, which measure passive transcellular permeability, do not record active lymphatic transport processes mediated by lipid-processing pathways.\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003eb) P-Glycoprotein Interactions\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eAs revealed in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, unmodified naloxone, NP, NST, and NHC are predicted to be non-inhibitor of P-gp, while NDC is predicted to be an inhibitor. NDC\u0026apos;s P-gp inhibitory potential could significantly improve therapeutic outcomes by reducing the efflux of P-gp substrate drug, especially in combination therapies involving naloxone and other medications affected by P-gp-mediated efflux. Nonetheless, naloxone is predicted to be a non-substrate in P-gp substrate status, while all lipid conjugates are classified as P-gp substrates. The transition from non-substrate (naloxone) to substrate status in lipid conjugates suggests that fatty acid chains introduce structural features that enable interaction with P-gp\u0026apos;s substrate-binding domains. This altered recognition profile may enhance efflux-mediated elimination and predispose to pharmacokinetic interactions with P-gp modulators. NDC\u0026apos;s inhibitory activity could provide adjunct benefits in multidrug regimens by competitively inhibiting P-gp-mediated efflux of co-administered substrates. Differential P-gp interactions between naloxone and esters highlight structure-dependent modulation of transporter affinity (Guan et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e; Subbaiah et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eP-Glycoprotein Interaction of Naloxone and its Lipid Conjugates\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eProbability \u0026amp; Interpretation\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNaloxone\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNST\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNDC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNHC\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP-Glycoprotein Inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.706\u003c/p\u003e\n \u003cp\u003eInhibitor (Medium Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (Medium Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP-Glycoprotein Substrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.376\u003c/p\u003e\n \u003cp\u003eNon-Substrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.779\u003c/p\u003e\n \u003cp\u003eSubstrate (Medium Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.817\u003c/p\u003e\n \u003cp\u003eSubstrate (Medium Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.636\u003c/p\u003e\n \u003cp\u003eSubstrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.537\u003c/p\u003e\n \u003cp\u003eSubstrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003ec) Skin Permeability\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eThe skin permeability data demonstrated significant differences among compounds, with naloxone showing a log KP value of -1.71 as revealed in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. NP and NST exhibited significantly increased values, indicating enhanced transdermal permeation, while NHC and NDC had slightly reduced permeability (Chakraborty et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec11\" class=\"Section4\"\u003e\n \u003ch2\u003e3.1.2.2 Distribution Parameters\u003c/h2\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003ea) Blood-Brain Barrier Penetration\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eThe prediction data indicates that NP and NST have higher logBB values, suggesting higher brain penetration compared to NDC, NHC and unmodified naloxone. Longer-chain fatty acids like palmitic and stearic acid may enhance BBB penetration, allowing for more efficient central action at lower systemic concentrations (Sarma et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). NHC and NDC have moderate logBB values, indicating sufficient brain penetration but possibly lower efficiency than NP and NST. Longer-chain fatty acid conjugates enhance BBB permeability by increasing lipophilicity and promoting integration into endogenous lipid transport mechanisms (Pifferi et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003eb) Plasma Protein Binding and Unbound Fraction\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003ePlasma protein binding data showed low binding for all compounds, with percentages ranging from 48.73\u0026ndash;58.88%, indicating poor protein binding as shown in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eIt suggests a significant amount of the drug is unbound and available for therapeutic action, potentially increasing drug distribution and bioavailability, enhancing therapeutic efficacy. The fraction unbound in human plasma revealed more substantial variations, with higher unbound fractions for lipid conjugates suggesting increased availability for tissue distribution and pharmacological action compared to unmodified naloxone (Han et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003ec) Volume of Distribution\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eThe steady-state volume of distribution (VDss) data of naloxone indicates its tissue distribution characteristics. For naloxone, VDss value is 1.69 L/kg, followed by NHC, NDC, NP, and NST as displayed in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eNaloxone\u0026apos;s higher VDss indicates more extensive tissue distribution compared to its lipid conjugates, possibly due to increased molecular size and altered physicochemical properties of conjugates. The reduced VDss of lipid conjugates may result in higher plasma concentrations, potentially enhancing plasma-dependent pharmacological effects (Das and Das \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e; Roy et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). Despite lower tissue distribution, physicochemical modifications in lipid conjugates could potentially improve targeted delivery to CNS, enabling more efficient brain uptake and therapeutic action. Higher logBB values for NP and NST indicate improved brain penetration.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec12\" class=\"Section4\"\u003e\n \u003ch2\u003e3.1.2.3 Metabolic Properties\u003c/h2\u003e\n \u003cp\u003eThe metabolic profile of naloxone and its lipid conjugates revealed distinct patterns for naloxone and its lipid conjugates, impacting their metabolism and potential drug-drug interactions as demonstrated in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMetabolic Profile of Naloxone and Its Lipid Conjugates\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eProbability \u0026amp; Interpretation\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNaloxone\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNST\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNDC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNHC\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBreast Cancer Resistance Protein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.497\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.572\u003c/p\u003e\n \u003cp\u003eInhibitor (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.284\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (Medium Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.181\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (Medium Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCYP 1A2 Inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCYP 1A2 Substrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.576\u003c/p\u003e\n \u003cp\u003eSubstrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.289\u003c/p\u003e\n \u003cp\u003eNon-Substrate (Medium Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.249\u003c/p\u003e\n \u003cp\u003eNon-Substrate (Medium Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003cp\u003eNon-Substrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003cp\u003eSubstrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCYP 2C19 Inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCYP 2C19 Substrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.537\u003c/p\u003e\n \u003cp\u003eSubstrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.489\u003c/p\u003e\n \u003cp\u003eNon-Substrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.467\u003c/p\u003e\n \u003cp\u003eNon-Substrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.531\u003c/p\u003e\n \u003cp\u003eSubstrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003cp\u003eSubstrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCYP 2C9 Inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCYP 2C9 Substrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.296\u003c/p\u003e\n \u003cp\u003eNon-Substrate (Medium Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003eNon-Substrate (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003eNon-Substrate (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003eNon-Substrate (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003cp\u003eNon-Substrate (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCYP 2D6 Inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.602\u003c/p\u003e\n \u003cp\u003eInhibitor (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.883\u003c/p\u003e\n \u003cp\u003eInhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.579\u003c/p\u003e\n \u003cp\u003eInhibitor (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003cp\u003eInhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.993\u003c/p\u003e\n \u003cp\u003eInhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCYP 2D6 Substrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.469\u003c/p\u003e\n \u003cp\u003eNon-Substrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003cp\u003eNon-Substrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.336\u003c/p\u003e\n \u003cp\u003eNon-Substrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.419\u003c/p\u003e\n \u003cp\u003eNon-Substrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.445\u003c/p\u003e\n \u003cp\u003eNon-Substrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCYP 3A4 Inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.563\u003c/p\u003e\n \u003cp\u003eInhibitor (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.551\u003c/p\u003e\n \u003cp\u003eInhibitor (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.614\u003c/p\u003e\n \u003cp\u003eInhibitor (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.392\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCYP 3A4 Substrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003cp\u003eSubstrate (Medium Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.372\u003c/p\u003e\n \u003cp\u003eNon-Substrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.282\u003c/p\u003e\n \u003cp\u003eNon-Substrate (Medium Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.608\u003c/p\u003e\n \u003cp\u003eSubstrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.632\u003c/p\u003e\n \u003cp\u003eSubstrate (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOATP1B1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.219\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (Medium Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.253\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (Medium Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOATP1B3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.475\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (Low Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.262\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (Medium Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003cp\u003eNon-Inhibitor (High Confidence)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eThe metabolic profiles of naloxone and its lipid conjugates reveal their potential interaction with \u003cem\u003eCYP\u003c/em\u003e enzymes and transporters. Naloxone is metabolised by \u003cem\u003eCYP1A2\u003c/em\u003e and \u003cem\u003eCYP2C19\u003c/em\u003e, indicating its susceptibility to these enzymes. However, its lipid conjugates have different levels of metabolic independence, with none being processed by \u003cem\u003eCYP1A2\u003c/em\u003e except NHC. However, they inhibit \u003cem\u003eCYP2D6\u003c/em\u003e, which may affect the metabolism of co-administered drugs. NP, NST and NDT also inhibit \u003cem\u003eCYP3A4\u003c/em\u003e, impacting the metabolism of drugs that are substrates of \u003cem\u003eCYP3A4\u003c/em\u003e. Strong inhibitory potential is shown by NDC, especially against CYP2D6 and CYP3A4 enzymes. However, the lack of inhibition of OATP1B1 and OATP1B3 transporters reduces the likelihood of transporter-related adverse effects, suggesting a favourable safety profile in this regard (Goyzueta-Mamani et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). Predicting the metabolism of compounds revealed that naloxone and its lipid conjugates have distinct interactions with metabolic transporters, including Breast Cancer Resistance Protein (\u003cem\u003eBCRP), Organic Anion Transporting Polypeptide 1B1 (OATP1B1)\u003c/em\u003e, and \u003cem\u003eOrganic Anion Transporting Polypeptide 1B3 (OATP1B3\u003c/em\u003eNaloxone, NP, and NST, are non-inhibitors of \u003cem\u003eOATP1B1\u003c/em\u003e and \u003cem\u003eOATP1B3\u003c/em\u003e, thereby minimizing the potential for transporter-mediated drug-drug interactions (Costa et al. 2025; Kciuk et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e; Othman et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe structural changes brought about by lipid conjugation, which affect enzyme recognition and metabolism, are reflected in the metabolic properties of naloxone and its lipid conjugates. These variations highlight the necessity of evaluating the metabolic profile of each conjugate separately in order to precisely forecast pharmacokinetic behaviour and interaction risks.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec13\" class=\"Section4\"\u003e\n \u003ch2\u003e3.1.2.4 Excretion Parameters\u003c/h2\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003ea) Clearance\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eThe clearance data revealed significant differences between naloxone and its lipid conjugates, with naloxone displaying the highest clearance rate at 23.09 L/min, followed by NHC, NDC, NP, and NST as mentioned in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eThis suggests that lipid conjugation significantly reduces naloxone\u0026apos;s elimination rate. The reduction in clearance rate of lipid conjugate\u0026apos;s is due to factors like increased lipophilicity, reduced renal filtration, and altered metabolism pathways. This is a key pharmacokinetic advantage, potentially resulting in prolonged systemic exposure and extended duration of therapeutic action, potentially enhancing tissue distribution and protein binding (Kalita et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003eb) Renal Transporter Interactions\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003e\u003cem\u003eThe Organic Cation Transporter 2 (OCT2)\u003c/em\u003e interaction data indicates that naloxone is predicted to be an \u003cem\u003eOCT2\u003c/em\u003e inhibitor, while all lipid conjugates are classified as non-inhibitors. This suggests that lipid conjugation alters the molecular recognition by \u003cem\u003eOCT2\u003c/em\u003e, potentially affecting naloxone\u0026apos;s renal secretion and interaction with co-administered drugs that are \u003cem\u003eOCT2\u003c/em\u003e substrates. The reduced \u003cem\u003eOCT2\u003c/em\u003e inhibitory potential of lipid conjugates may contribute to their altered clearance profile and reduce the risk of renal drug-drug interactions (\u0026Ccedil;evik et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec14\" class=\"Section4\"\u003e\n \u003ch2\u003e3.1.2.5 Comprehensive Comparison of Individual Lipid Conjugates\u003c/h2\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003ea) Naloxone Palmitate\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eNP offers several pharmacokinetic advantages over unmodified naloxone. Its reduced clearance suggests extended systemic exposure, potentially resulting in prolonged therapeutic action. Its classification as a P-gp substrate may contribute to reduced elimination through P-gp-mediated efflux mechanisms. Its improved BBB penetration offers potential advantages. Moreover, the enhanced skin permeability of NP allows it to be absorbed via the transdermal route. NP\u0026apos;s metabolic profile differs significantly from naloxone, with notable changes such as being classified as a non-substrate for \u003cem\u003eCYP1A2\u003c/em\u003e and \u003cem\u003eCYP3A4\u003c/em\u003e and enhanced inhibitory potential for \u003cem\u003eCYP2D6\u003c/em\u003e and \u003cem\u003eCYP3A4\u003c/em\u003e. These metabolic alterations could affect the compound\u0026apos;s stability and drug-drug interactions. Therefore, NP is suitable for both oral and transdermal applications requiring sustained action.\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003eb) Naloxone Stearate\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eNST has the most significant lipophilicity-related effects among the conjugates studied. NST indicated improved BBB penetration and reduced clearance, suggesting enhanced CNS targeting and prolonged systemic exposure. Its enhanced skin permeability suggests potential for transdermal delivery, allowing efficient absorption without permeation enhancers or specialized formulations. It also has the highest unbound fraction, indicating increased pharmacological action. NST is predicted to inhibit BCRP, potentially influencing the pharmacokinetics of BCRP substrate drugs and due to its high lipophilicity, making it a promising candidate for oral and transdermal delivery.\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003ec) Naloxone Caprate\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eNDC offers a balanced approach to lipid conjugation, offering moderate improvements in pharmacokinetic parameters without the extreme shifts seen with longer-chain conjugates. Its intermediate clearance reduction suggests moderately extended systemic exposure, while its improved Caco-2 permeability indicates enhanced membrane permeation potential. NDC is predicted to be a P-gp inhibitor, which could have significant implications for co-administered drugs that are P-gp substrates. It also demonstrated the highest plasma protein binding percentage, which might contribute to its reduced clearance by limiting the fraction available for glomerular filtration. The metabolic profile of NDC includes inhibition of \u003cem\u003eCYP2D6\u003c/em\u003e and \u003cem\u003eCYP3A4\u003c/em\u003e, suggesting potential for metabolic drug-drug interactions in clinical applications. The compound showed improvement in both BBB penetration and intestinal absorption, indicating enhanced CNS delivery and oral bioavailability.\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003ed) Naloxone Caproate\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eNHC offers modest improvements in selected pharmacokinetic parameters while preserving many characteristics of the parent compound. Its intermediate clearance reduction suggests moderately extended systemic exposure, while its maintained intestinal absorption probability indicates preserved absorption properties. NHC maintains substrate status for \u003cem\u003eCYP1A2\u003c/em\u003e, suggesting preserved metabolic pathways, but showed enhanced \u003cem\u003eCYP2D6\u003c/em\u003e inhibitory potential, indicating potential for specific metabolic drug-drug interactions. Its plasma protein binding percentage is the lowest among all compounds, suggesting slightly enhanced free fraction available for pharmacological action.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec15\" class=\"Section4\"\u003e\n \u003ch2\u003e3.1.2.6 Therapeutic Implications\u003c/h2\u003e\n \u003cp\u003eLipid conjugation of naloxone with fatty acids provides several pharmacokinetic and pharmacodynamic advantages. Conjugates facilitate longer durations of therapeutic action than naloxone, providing relief against pain attacks and other life-threatening opioid effects. They have potential for oral delivery for migraine, neuroinflammation, and opioid toxicity treatment. These compounds have potential for BBB penetration, implying better CNS targeting and allowing for lower effective doses with fewer peripheral side effects. The increased lipophilicity of lipid conjugates allows for better diffusion across biological membranes. The ester linkage between naloxone and fatty acids is rapidly hydrolysed by enzyme, allowing the active compound to be released at target site, potentially improving therapeutic specificity and duration of action. Lipid conjugation also alters recognition by metabolic enzymes and transporters, potentially enhancing bioavailability. These modifications make lipid-based delivery systems more feasible, potentially optimising pharmacokinetic parameters and therapeutic performance.\u003c/p\u003e\n \u003cp\u003eTheir pharmacodynamic interactions with migraine-relevant targets, such as \u003cem\u003eserotonin, toll-like and opioid receptors\u003c/em\u003e as well as other therapeutic targets, were further investigated to confirm their therapeutic utility.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Target Prediction and Pharmacodynamic Effects\u003c/h2\u003e\n \u003cp\u003eAlong with opioid receptors, naloxone does interact with receptors and enzymes outside the opioid system, making it potential for migraine treatment and other neurological and/or physiological disorders. Its activity in pain modulation pathways, neuroinflammation, vascular function, and neurotransmitter regulation is significant in migraine pathophysiology. Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e summarized predicted target and pharmacodynamic action of naloxone and its lipid derivatives based on migraine relief and therapeutic potential.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePredicted Target and Pharmacodynamic Action Naloxone and its Lipid Derivatives\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eTarget Common Name\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eTarget Class\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ePharmacodynamic Effect\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eProbability\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNHC\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNP\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNSt\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNDC\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNHC\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMu opioid receptor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eGPCR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModulates pain pathways and central sensitization; potential role in migraine pain relief (Wang and Thyagarajan \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9713\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4688\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7866\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDelta opioid receptor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eGPCR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegulates analgesia, mood, and inflammatory responses; possible anti-migraine effects (El Daibani and Pradhan \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9713\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4688\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7866\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eKappa opioid receptor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eGPCR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInfluences nociception, stress, and inflammation; potential in migraine and chronic pain (Weng \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9713\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4688\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7866\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCytochrome P450 2D6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eEnzyme\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMetabolizes drugs and neurotransmitters; could influence efficacy of migraine treatments (Yamoune et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9713\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3441\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdenosine A3 receptor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eGPCR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnti-inflammatory, neuroprotective, and vasomodulatory effects relevant to migraine (Silvestro et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9713\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1715\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2958\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eC-C chemokine receptor type 5 (CCR5)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eGPCR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModulates immune response and neuroinflammation; may play a role in neurogenic inflammation in migraine (Sudershan et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9713\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4326\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eToll-like receptor 4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eToll-like receptor\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegulates neuroinflammation and pain sensitization, making it a target for migraine and neurodegenerative disorders (Saleki et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1809\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1892\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2556\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHERG (hERG KCNH2)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIon channel\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegulates cardiac repolarization; inhibition can reduce migraine-associated cardiovascular risks (Rouhana et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSigma opioid receptor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMembrane receptor\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModulates stress response, addiction, and neuroprotection; potential relevance in migraine-related stress triggers (Zorrilla \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNociceptin receptor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eGPCR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInhibits pain transmission and modulates migraine pathways (Kavya et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCholecystokinin B receptor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eGPCR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvolved in anxiety, pain, and digestion; may contribute to migraine-associated nausea and sensory hypersensitivity (Acz\u0026eacute;l \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBeta-3 adrenergic receptor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eGPCR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegulates vascular tone and metabolism; potential target for migraine and metabolic disorders (Read et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSerotonin 2a (5-HT2a) receptor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eGPCR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAffects mood, vasoconstriction, and cortical spreading depression, key factors in migraine pathophysiology (Sakeer et al. 2024)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReceptor protein-tyrosine kinase erbB-2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eKinase\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvolved in neuronal plasticity and pain sensitization; potential role in chronic migraine (Giraud et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEpidermal growth factor receptor erbB1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eKinase\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eImplicated in neuroprotection and pain regulation; potential relevance in migraine-associated neuroinflammation (Vellapandian \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSerotonin 4 (5-HT4) receptor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eGPCR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModulates neuronal excitability and gut motility, linking it to migraine-associated gastric symptoms (Guerrero \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOpioid growth factor receptor-like protein 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eUnclassified protein\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegulates neuroimmune functions and nociception, making it relevant to migraine treatment (Jayathilake et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMatrix metalloproteinase 9 (MMP9)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eProtease\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvolved in BBB permeability and neuroinflammation, key factors in migraine pathogenesis (Curry-Koski et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhosphodiesterase 10A\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eEnzyme\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegulates dopamine signalling ; may play a role in migraine and psychiatric comorbidities (Barbagallo et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eThrombin (Factor IIa, F2)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eProtease\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvolved in coagulation and vascular dysfunction, potential risk factor for migraine-associated stroke (Hassan et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTyrosine-protein kinase JAK2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eKinase\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlays a role in immune response regulation; possible link to neuroinflammatory migraine mechanisms (Kohandel et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kr\u0026auml;mer et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistone deacetylase 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eEpigenetic regulator\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModulates gene expression and neuronal plasticity; potential migraine and neurodegeneration target (Gazerani \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMelanin-concentrating hormone receptor 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eGPCR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegulates appetite and circadian rhythms, possibly linked to migraine-triggering factors (Goadsby et al. \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e; Stanyer \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003ePredicted target profiles and pharmacodynamic actions of naloxone hydrochloride (NHC) and its lipid derivatives, naloxone palmitate (NP), naloxone stearate (NSt), naloxone caprate (NDC), and naloxone caproate (NHC), showed notable differences that could affect their therapeutic potential, particularly in the treatment of migraine and related neuroinflammatory conditions. Naloxone and its lipid conjugates can bind to the three major opioid receptors (mu (OPRM1), delta (OPRD1), and kappa (OPRK1)) (Rushendran and Chitra \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Its well-known function as a potent opioid antagonist, modulating pain pathways and central sensitization, both of which are required for migraine pain relief, is supported by its affinity for opioid receptors (Li et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). In addition to opioid receptors, NHC has a high predicted affinity for adenosine A3 and cytochrome P450 2D6 (CYP2D6) receptors, which are linked to neuroinflammation and drug metabolism, respectively. Notably, NP and NDC exhibit a moderate affinity for phosphodiesterase 10A (PDE10A), an enzyme that controls dopamine signaling and is connected to symptoms of migraines like photophobia and nausea (Villar-Martinez and Goadsby \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e; Rushendran et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e; El-Naggar et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eAll compounds are predicted to target the immune-modulatory receptors CCR5 and toll-like receptor 4 (TLR4) (Ciechanowska and Mika \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Given TLR4\u0026apos;s role in neuroinflammation and pain sensitization, this suggests that naloxone and its lipid conjugates could effectively regulate neuroinflammatory cascades implicated in migraine pathophysiology (Babu et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e; Sharma et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Differential affinities are also seen in ion channels and other receptors linked to neurological and cardiovascular functions (Cuciureanu et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). For example, all compounds weakly target the hERG potassium channel, which controls cardiac repolarization and may affect cardiovascular risks associated with migraines, but NDC and NHC target it slightly more. Similarly, sigma opioid receptors, which regulate neuroprotection and stress response to migraine triggers, exhibit weak binding in NP and NSt and a low but noticeable affinity in NDC and NHC. Serotonin receptors, particularly 5-HT2a and 5-HT4, are important in migraine due to their roles in vasoconstriction, cortical spreading depression, and gastrointestinal symptoms (Borończyk et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). Naloxone shows an affinity for these receptors. This suggests that naloxone may have a broader impact on serotonergic pathways implicated in migraine aura and associated symptoms.\u003c/p\u003e\n \u003cp\u003eOther targets specific to lipid conjugates are matrix metalloproteinase 9 (MMP9), which is predicted to be bound by NP and NDC and is involved in neuroinflammation and blood-brain barrier permeability (Bhatia et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). This could have a positive impact on migraine control by stabilizing the blood-brain barrier and lowering neurovascular inflammation (Savvidou et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). Likewise, kinases implicated in immunological regulation and neuroprotection, including JAK2 and epidermal growth factor receptor (EGFR), exhibit increased predicted affinity in NDC, indicating additional neuroprotective advantages (Fu and Liu \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e; Panda et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). NP is predicted to bind to \u003cem\u003eceramide glucosyltransferase\u003c/em\u003e, an enzyme vital for glycosphingolipid synthesis, which may impact inflammation and pain mechanisms in migraines (Liu et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). It is also predicted to bind to smoothened homolog, a key element in the Hedgehog signalling pathway, which influences cell growth, differentiation, and tissue patterning, potentially influencing neurogenesis and inflammation (Parashar et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Aside from migraine, NP\u0026apos;s preference for \u003cem\u003eVEGFRs, beta-3 adrenergic receptors\u003c/em\u003e, and \u003cem\u003eepidermal growth factor receptor\u003c/em\u003e points towards uses in metabolic disease, cardiovascular disease, and neurodegeneration (Sheikh et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e; Islam et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e; Miliotou et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). NSt\u0026apos;s effects on \u003cem\u003eHistone deacetylase 3\u003c/em\u003e and \u003cem\u003evascular growth factors\u003c/em\u003e imply therapeutic advantages in neurodegenerative diseases, vascular disease, and chronic pain disorders (Costanzo et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). Apart from migraine, the interactions of NHC with PI3K signal pathways, \u003cem\u003eVEGFRs\u003c/em\u003e, and \u003cem\u003eHistone deacetylase 3\u003c/em\u003e confer neuroprotective and metabolic regulating effects, giving it applicability in aging-linked cognitive impairment, epilepsy, and metabolic disorders (de la Monte \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Thus, lipid conjugates may provide a more comprehensive modulation of migraine-related symptoms like anxiety and metabolic dysfunction.\u003c/p\u003e\n \u003cp\u003eOverall, the evidence points to naloxone hydrochloride\u0026apos;s primary mechanisms of action as strong opioid receptor antagonist and serotonergic and neuroimmune pathway modulation, which enables it to effectively reduce acute migraine pain and control neuroinflammation. By contrast, the lipid conjugates exhibit a varied pharmacodynamic profile, exhibiting significant binding affinity to opioid receptors, increased interaction with immune receptors, enzymes, and signaling pathways linked to neuroinflammation, the integrity of the blood-brain barrier, and the regulation of neurotransmitters. By focusing on underlying pathophysiological mechanisms other than opioid receptor blockade, this change may offer benefits in the treatment of chronic migraines. Furthermore, there may be a chance for better symptom management in migraine subtypes marked by neurovascular dysfunction and sensory hypersensitivity due to the lipid conjugate\u0026apos;s anticipated modulation of dopamine signaling, BBB permeability factors, and stress-related receptors. Their potential neuroprotective and metabolic advantages are further highlighted by their interaction with kinases and growth factor receptors, broadening their therapeutic range to include co-morbid conditions like stroke risk and neurodegeneration. While therapeutic efficacy of developed compounds depends on target engagement, safety is the key to the viability for clinical translational. Therefore, to ensure that improved pharmacokinetics and receptor binding do not present unanticipated risks, the following section elucidates the toxicity profiles of these derivatives.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Toxicity Analysis\u003c/h2\u003e\n \u003cp\u003eProTox was employed to examine the predicted patterns of toxicity for naloxone and its lipid conjugates as shown in Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eToxicity Analysis Naloxone and its Lipid Conjugates\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEndpoint\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNaloxone and its Lipid Conjugates\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eOrgan Toxicity\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eHepatotoxicity\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInactive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNeurotoxicity\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInactive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNephrotoxicity\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInactive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRespiratory Toxicity\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eActive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCardiotoxicity\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInactive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eMetabolism\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCYP1A2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInactive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCYP2C19\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInactive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCYP2C9\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInactive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCYP2D6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eActive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCYP3A4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInactive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCYP2E1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInactive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eAt the organ level, ProTox predicted that all compounds, including naloxone and its lipid conjugates, are expected to be inactive for hepatotoxicity, neurotoxicity, nephrotoxicity, and cardiotoxicity. However, all compounds are predicted to be active for respiratory toxicity, as respiratory depression is a recognized toxic effect of opioid overdose. All compounds are predicted to be inactive for carcinogenicity, mutagenicity, and ecotoxicity, indicating no significant risks. Preclinical data demonstrating naloxone\u0026apos;s protective effects against opioid-induced hepatic damage, as demonstrated by histopathological improvements in animal models despite unchanged serum biomarkers, is consistent with hepatotoxicity predictions of inactivity. Clinical data for naloxone supports neurotoxicity predictions, wherein adverse neurological events (rare seizures in 4% of cases, transient confusion in 20% of cases) are expected pharmacological reversal effects rather than intrinsic neurotoxicity. Although there are no cardiotoxic events reported in paediatric studies, cardiovascular assessments show predictable dose-dependent responses, including transient tachycardia (4\u0026ndash;6% incidence) and isolated case reports of hypertension/pulmonary edema in adults (Wermeling \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Rzasa and Galinkin 2018; USFDA Label, Accessed 02 January 2025). This integrated analysis positions lipid-conjugated naloxone derivatives as promising candidates with manageable safety profiles for migraine treatment applications.\u003c/p\u003e\n \u003cp\u003eAfter establishing favourable safety, pharmacokinetic profiles, and potential targets for naloxone and its lipid conjugates, the next section examines the structural basis of receptor interactions. This clarifies how lipid conjugation alters binding affinities for 5-HTR, TLR4, and \u0026micro;-opioid receptors for the treatment of migraine.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4 Molecular docking studies\u003c/h2\u003e\n \u003cp\u003eMolecular docking experiments were conducted to analyse the binding affinity of naloxone and its lipid conjugates against three key migraine pathophysiological receptors: \u003cem\u003e5-HTR\u003c/em\u003e, \u003cem\u003eTLR4\u003c/em\u003e, and \u003cem\u003e\u0026micro;-opioid receptor\u003c/em\u003e (Eberhardt et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Bugnon et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Table \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e demonstrated that all compounds, including naloxone and lipid conjugates, exhibited strong binding affinities (\u0026le; -4.0 kcal/mol) against these receptors, indicating their potential therapeutic use in migraine treatment.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBinding Affinity of compounds with Target Receptors\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCompounds\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eTarget Receptor\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e5HT\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTL4\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eOpioid receptor\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNHCl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.937 to -3.646\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6.550 to -5.116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6.015 to -3.138\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.909 to -3.512\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.406 to -2.768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.821 to -4.204\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.231 to -2.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.680 to -2.824\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.435 to -3.039\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.298 to -3.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6.539 to -4.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6.028 to -3.401\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNHC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.74 to -3.756\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6.359 to -4.546\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.562 to -3.867\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e5-HTR\u003c/em\u003e is a well-documented target in migraine treatment, with triptans functioning as selective agonists at \u003cem\u003e5-HT1B/1D receptors\u003c/em\u003e to treat migraine. Naloxone and its lipid conjugates, effectively interact with \u003cem\u003e5-HTR\u003c/em\u003es as displayed in Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e (a), modulating serotonergic pathways within migraine attacks (Pehlivanlar et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). The Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e indicates that naloxone and its lipid conjugates can effectively treat migraines by binding with \u003cem\u003e5-HTR\u003c/em\u003e. Alongside, \u003cem\u003eTLR4\u003c/em\u003e receptor plays key role in migraine-related neuroinflammation, causing mast cell degranulation and trigeminal nerve sensitization (Soylu et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). Naloxone and its lipid conjugates have high binding affinity for \u003cem\u003eTLR4\u003c/em\u003e, suggesting lipid conjugation doesn\u0026apos;t impair \u003cem\u003eTLR4\u003c/em\u003e recognition (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e (b)), suggesting potential anti-inflammatory effects to counter migraine pain. Likewise, the \u0026micro;-\u003cem\u003eopioid receptor\u003c/em\u003e is a target of interest in chronic migraine patients, who tend to have altered endogenous opioid neurotransmission during an attack (Garc\u0026iacute;a-Dom\u0026iacute;nguez \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Naloxone and its lipid conjugates have the optimum binding affinity (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e (c)), suggesting they modulate opioid signalling pathways involved in pain processing. Thus, the molecular docking data showed that naloxone and its lipid conjugates are effective for migraine treatment due to their optimal binding affinities towards \u003cem\u003eserotonin, TLR4, and \u0026micro;-opioid receptors\u003c/em\u003e. These compounds can rectify pain modulation, neuroinflammation, and serotonergic dysregulation. Yet, further \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e investigations are needed to confirm these predictions and enhance their use as targeted drugs for migraine patients.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThe study presents a promising \u003cem\u003ein silico\u003c/em\u003e investigation on naloxone as repurposed drug for migraine treatment. Selective conjugation of naloxone with lipid groups has led to the discovery of novel derivatives exhibiting enhanced pharmacokinetics and enhanced affinity for the \u003cem\u003eserotonin, toll-like, and \u0026micro;-opioid receptor\u003c/em\u003e, a crucial target in migraine pathophysiology, highlighting the potential of naloxone and its lipid conjugates for migraine treatment. The computational simulations revealed that lipid conjugates significantly alter pharmacokinetic parameters, resulting in prolonged duration of therapeutic effect and enhancing naloxone brain delivery, by altering its physicochemical parameters. Naloxone and its lipid conjugates are effective for migraine treatments due to their optimal binding affinity to \u003cem\u003eserotonin, toll-like, and \u0026micro;-opioid receptors\u003c/em\u003e, resolving pain modulation, neuroinflammation, and serotonergic dysregulation, providing an avenue for targeted intervention into migraine mechanisms. The results are based on \u003cem\u003ein silico\u003c/em\u003e results, which are a basis for future experimental verification. Follow-up \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e investigations are necessary to establish the BBB permeability, metabolic stability, and receptor binding profiles of these conjugates. Clinical trials are needed to establish the efficacy and safety of these compounds in migraine patients. This investigation underscores the potential of drug repurposing and rational design in unmet medical needs.\u003c/p\u003e"},{"header":"5. Future Perspectives","content":"\u003cp\u003eThe study confirms the use of naloxone lipid conjugates for migraine treatment, indicating altered pharmacokinetic parameters, allowing for prolonged duration of therapeutic action, and targeting 5-HTR, TLR4, and mu-opioid receptors. However, further experimental evidence is needed to validate these findings and drive the repurposing approach towards clinics. \u003cem\u003eIn vitro\u003c/em\u003e investigation is needed to characterize the BBB permeability and metabolic stability of lipid conjugates synthesized through cell-based assays (Eltanameli et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and enzymatic models of degradation (Lee et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This will provide insights into the compound's potential for brain penetration and circulating half-life, as well as verify their binding with \u003cem\u003e5-HTR\u003c/em\u003e subtypes involved in migraine.\u003c/p\u003e\u003cp\u003eLead candidates identified from \u003cem\u003ein vitro\u003c/em\u003e screens should be evaluated \u003cem\u003ein vivo\u003c/em\u003e with animal models of migraine to measure their effectiveness against migraine behaviour, determine their pharmacokinetic profiles, and assess their therapeutic window. Safety and tolerability determinations are also necessary for these novel compounds. Present exploration suggests that rational drug design, lipid conjugation, and targeting the BBB can be applied to other repurposed medications and neurological diseases, potentially improving the delivery and effectiveness of migraine drugs or identifying new therapeutic targets.\u003c/p\u003e\u003cp\u003eUtilizing advanced computational modelling methodologies like molecular dynamics simulations (Cordeiro et al. 2024; Park et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Kaur et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) and machine learning can improve the design of lipid conjugates, predict their interaction with biological systems, and enhance understanding of action mechanisms, ultimately improving the pharmacological features of these drugs (Sharma et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; G\u0026uuml;lave et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The translation of research into clinical settings relies on creating safe, effective, and commercially available naloxone lipid conjugates. Future research should focus on process optimization, clinical trials, and patient compliance optimization. Combining computational design, experimental verification, and clinical translation will unlock therapeutic benefits and redefine migraine treatment.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cem\u003e5-HTR: Serotonin Receptor\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBBB: Blood-Brain Barrier\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBCRP: Breast Cancer Resistance Protein\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eCNS: Central Nervous System\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMMP9: Matrix metalloproteinase 9\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNDC: Naloxone Caprate\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNHC: Naloxone Caproate\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNHCl: Naloxone Hydrochloride\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNP: Naloxone Palmitate\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNST: Naloxone Stearate\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eOCT2: The Organic Cation Transporter 2\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eP-gp: P-glycoprotein\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTLR4:\u0026nbsp;\u003c/em\u003eToll-like Receptor 4\u003c/p\u003e\n\u003cp\u003eVDss: Volume of Distribution\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eThe authors gratefully acknowledge the support of their respective institutions. This research was supported by the Prime Minister\u0026rsquo;s Fellowship. The funding body had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompliance with Ethical Standards:\u0026nbsp;\u003c/strong\u003eThis article does not contain any studies with human participants or animals performed by any of the authors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests and Funding:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no known competing interests that could have influenced the work reported in this paper.\u0026nbsp;The authors gratefully acknowledge the support of their respective institutions. This research was supported by the Prime Minister\u0026rsquo;s Fellowship. The funding body had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e All authors have equally contributed to this research work. All authors have read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAcz\u0026eacute;l T. (2022) Mechanisms of trigeminal activation and sensitisation: implications for migraine pathophysiology (Doctoral dissertation, University of P\u0026eacute;cs (Hungary)). \u003c/li\u003e\n\u003cli\u003eBabu N, Gadepalli A, Akhilesh, Sharma D, Singh AK, Chouhan D, Agrawal S, Tiwari V. (2024) TLR-4: a promising target for chemotherapy-induced peripheral neuropathy. Mol. Biol. Rep. 51(1):1099. https://doi.org/10.1007/s11033-024-10038-1\u003c/li\u003e\n\u003cli\u003eBanerjee P, Kemmler E, Dunkel M, Preissner R. 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(2024) Investigating the Therapeutic Potential of Cannabinoids in Pre-Clinical Models of Migraine (Doctoral dissertation, The University of Iowa). https://www.proquest.com/openview/5336a955af0682278af74fa1943b6b8b/1?cbl=18750\u0026amp;diss=y\u0026amp;pq-origsite=gscholar\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Naloxone, Lipid-drug conjugates, Drug repurposing, In silico ADMET, Molecular docking","lastPublishedDoi":"10.21203/rs.3.rs-6687113/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6687113/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMigraine, a common neurological condition, requires novel therapeutic approaches beyond current symptomatic remedies. Drug repurposing offers a rapid-track solution to this demand. Naloxone, an opioid antagonist, has been identified as a potential candidate for migraine treatment, but its limited blood-brain barrier permeability and extensive metabolism limit its clinical effectiveness. Lipid-drug conjugates enhance therapeutic efficiency by chemically conjugating drugs to lipid groups, enhancing lipophilicity and systemic bioavailability, as well as enabling targeted delivery. They facilitate lymphatic targeting (when administered orally) by avoiding first-pass metabolism and prolong the duration of therapeutic action of drug by optimising pharmacokinetic profiles. The present investigation employed \u003cem\u003eIn silico\u003c/em\u003e methods to study naloxone and its novel naloxone lipid conjugates for altered pharmacokinetic parameters and enhanced interaction with \u003cem\u003eserotonin, toll-like\u003c/em\u003e and \u003cem\u003e\u0026micro;-opioid receptor\u003c/em\u003e for the treatment of migraine. Computational ADMET, therapeutic target predictions and molecular docking methodologies were combined for \u003cem\u003ein silico\u003c/em\u003e predictions of naloxone and its lipid conjugates. The results revealed that lipid conjugation significantly changed naloxone's pharmacokinetic profiles and binding affinity for \u003cem\u003eserotonin, toll-like\u003c/em\u003e and \u003cem\u003e\u0026micro;-opioid receptor\u003c/em\u003e. \u003cem\u003eIn silico\u003c/em\u003e predictions indicated the potential of naloxone and its lipid conjugates for the treatment of migraine, with results demonstrating that the lipid conjugates provide longer duration of therapeutic action compared to naloxone. This rationale-driven drug repurposing approach has potential for the design of a new, brain-delivered, and serotonin-modulating compound for migraine treatment following \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e validation.\u003c/p\u003e","manuscriptTitle":"In Silico Evaluation of Lipid-Drug Conjugates: Pharmacokinetic and Pharmacodynamic Profiling for Therapeutic Repurposing of Naloxone in Migraine Management","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-16 08:26:52","doi":"10.21203/rs.3.rs-6687113/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"854717a1-12d4-44c5-b35e-871fd9c71000","owner":[],"postedDate":"September 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-05T14:23:47+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-16 08:26:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6687113","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6687113","identity":"rs-6687113","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}