Computational Identification and Evaluation of Perlolyrine as a Promising AT1R Antagonist for Hypertension Therapy

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Bufarwa, Mustapha Belaidi, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7499142/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 The angiotensin II type 1 receptor (AT1R) is a key target for antihypertensive drug development. This study uses an integrative computational approach to identify perlolyrine (MOL002140) as a promising AT1R modulator. A comprehensive in silico workflow was used, which included pharmacophore modeling, molecular docking, ADMET profiling, DFT calculations, and molecular dynamics (MD) simulations. Strong binding affinity to AT1R (− 8.2 kcal/mol) was demonstrated by perlolyrine, which also formed stable interactions with important residues like TRP84, TYR87, ASP281, and ARG167. ADMET predictions showed a good safety profile and favorable pharmacokinetic properties. The electronic stability of the compound with a HOMO–LUMO energy gap of 3.95 eV was confirmed by DFT analysis. The AT1R–Perlolyrine complex was found to be stable, compact, and exhibit few conformational fluctuations in long-timescale MD simulations (200 ns). Consistent receptor–ligand dynamics were further shown by principal component analysis (PCA) and angular distribution studies, confirming the compound's potential as a potent AT1R antagonist. All of these results point to perlolyrine as a viable option for additional research and development in the treatment of hypertension. Computational Biology Bioinformatics Perlolyrine AT1R hypertension molecular dynamics DFT pharmacophore modeling in silico drug discovery Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Hypertension is characterized as a progressive cardiovascular condition caused by multiple and interconnected etiologies. As it advances, it could result in structural and functional cardiac and vascular abnormalities that harm the brain, kidneys, heart, vasculature, and other organs, causing early morbidity and death [ 1 , 2 ]. The World Health Organization (WHO) estimates that 7.5 million deaths, or 12.8% of all deaths, are attributed to high blood pressure [ 3 ]. The main role of RAAS is to manage BP and the water in your body. High blood pressure can result from lack of sodium chloride in the kidney tubules, a problem with blood pressure or activation of the nervous system that controls fight or flight reaction [ 4 ]. In to the system, renin is the enzyme that sets off the process by secreting angiotensinogen. It alters it, making it a decapeptide called angiotensin I (Ang I). The ACE converts Ang I into Ang II, an important octapeptide which is much more likely when substrates are adequately glycosylated [ 5 ]. Ang II controls many activities in the body by liganding to and activating the G-protein-coupled angiotensin II type 1 receptor (AT1R) found in the sarcolemma. When Ang II binds to AT1R, several tyrosine–histidine and phenylalanine–histidine interactions are observed. When intracellular kinases, like MAPKs, are introduced and G-protein psych settings are triggered, they cause signaling reactions to unfold. As well, beta arrestins regulate additional processes such as signaling, making receptors less sensitive and bringing receptors into the cell [ 6 ]. An overstimulation of Ang II or poor breakdown of AT1R caused by aberrant glycosylation may lead to high blood pressure [ 7 ]. The rational design of AT1 receptor antagonists is essential for the development of therapeutic drug that target cardiovascular diseases. Sartans, a class of drugs intended to stop Angiotensin II from attaching and activating on the AT1 receptor, have demonstrated notable therapeutic efficacy [ 8 ]. Traditionally, traditional Chinese medicine (TCM) has often been used to treat cardiovascular disorders which include components that may be therapeutically helpful. Danshen (Salvia miltiorrhiza) has potent anti-inflammatory, antioxidant and anti-thrombotic features, mainly due to tanshinones and salvianolic acids. It helps prevent atherosclerosis, soothes ischemic heart symptoms and promotes blood circulation in the heart by hindering oxidative stress and problems with the heart’s endothelial cells [ 9 ]. Since ginseng can ease inflammation and lower lipids, it helps treat both hypertension and hyperlipidemia. Moreover, it stimulates the body to make nitric oxide (NO) which relaxes the blood vessels [ 10 ]. Benefits of Schisandra chinensis, including protecting mitochondria and reducing oxidative stress, are useful to individuals coping with ischemic heart disease [ 11 ]. It has been observed that this herb can assist in treating ischemic heart disease as well as promote normal heart function. The major components in Chuanxiong are ligustilide and ferulic acid which help relax blood vessels and stop blood clots. For a long time, medicine has used it to remove blood blockages and encourage blood circulation [ 12 ]. This herb is recognized for assiting in blood circulation and making blood more fluid. It helps to control hypertension by changing how the blood vessels work and lessening the stiffness of the arteries [ 13 ]. Ginkgo biloba contains flavonoids and terpenoids which help the small blood vessels, lessen oxidative stress and improve how the endothelium functions. Ginkgo extract may both prevent ischemia and play a role in reducing arterial plaque development, clinical studies suggest [ 14 ]. Hawthorn's (Crataegus spp.) polyphenolic content improves cardiovascular health by lessening the signs of heart failure and hypertension [ 15 ]. The main ingredient in Stephania tetrandra, tetrandrine, has anti-inflammatory and vasodilatory qualities that help control calcium channels and lessen vascular remodeling [ 16 ]. Licorice contains glycyrrhizin, an anti-inflammatory and antioxidant substance. By reducing arterial stiffness and regulating lipid metabolism, it safeguards the heart [ 9 ]. Numerous cardioprotective advantages of astragalus include enhancing heart health and reducing inflammation [ 17 ]. While notoginseng's anticoagulant properties improve vascular health and reduce myocardial ischemia, cinnamon prevents cardiovascular disorders linked to metabolic syndrome by controlling blood pressure and glucose levels [ 18 , 19 ]. This study aimed to investigate the potential of natural compounds derived from specific herbs as AT1R modulators, taking into account the significance of the Ang II-AT1R axis in the pathophysiology of hypertension. Using FDA-approved AT1R antagonists as references, we assessed the bioactive compounds using computational techniques including virtual screening, molecular docking, ADMET profiling, density functional theory (DFT) calculations, molecular dynamics (MD) simulations, and post-MD analysis. Using MD simulations, thermochemical analysis, and molecular orbital analysis, we assessed their drug-like properties. By changing vascular function and reducing blood pressure, we believe that targeting AT1R with these natural compounds may benefit those who suffer from hypertension. Material and Methods Virtual Screening A set of 587 compounds derived from traditional Chinese medicinal herbs, such as Danshen, Ginseng, Schisandra chinensis, Chuanxiong, Angelica sinensis, Ginkgo biloba, Hawthorn, Stephania tetrandra, Licorice root, Astragalus membranaceus, Notoginseng, and Cinnamon, was subjected to a ligand-based virtual screening using LigandScout 3.1 software [ 20 ]. The compounds were retrieved from the TCM database [ 21 ] and filtered based on the following criteria: molecular weight (MW) ≤ 500 Da, LogP ≤ 5, hydrogen bond donors (HBD) ≤ 5, hydrogen bond acceptors (HBA) ≤ 10, oral bioavailability (OB) ≤ 10, Caco-2 permeability greater than − 5.15 cm/s, blood-brain barrier (BBB) permeability greater than 0.3, drug-likeness (DL) ≥ 0.18, fractional polar surface area (FASA) above 30%, and a half-life (HL) of more than 3 hours. The pharmacophore model was created using the 3D structures of Katerzia, Norliqva, Isoxsuprine, Lisinopril, Perindopril, Atorvastatin, Xarelto, Brilinta, and Amlodipine medications approved by the FDA for coronary artery disease (CAD). The espresso method was used to develop a ligand-based pharmacophore, and LigandScout's default parameters were used to ensure that the pharmacophore hypothesis was compatible. Two common benchmark criteria were used to determine which hits were the best. Hits were initially arranged according to pharmacophore fit scores, with preference given to those that were above a predetermined cutoff, frequently 0.7–1.0 or near 1. Second, pharmacophore feature matching was used to classify compounds as good hits if they demonstrated at least 70–80% alignment with the pharmacophore features, such as hydrogen bond acceptors (HBAs), aromatic rings (ARs), and hydrophobic zones (Hs). Receptor Ligand Preparation The three-dimensional (3D) structure of AT1R (PDB ID: 4ZUD) were retreived from the Protein Data Bank (PDB) [ 22 ]. The UCSF Chimera v1.17.1 software [ 23 ], was used to remove water molecules, crystallographic cofactors, and additional chains from the retrieved structure. After that, hydrogen atoms were incorporated into the protein structures, and their stability was maximized by minimizing energy. The PDB format was used to store the processed structure for later examination. The binding pocket of targeted protein was estimated by using BIOVIA Discovery Studio Software [ 24 ] for possible docking sites. PyRx software 0.8 [ 25 ] was used to prepare the top hit molecules in order to ensure their suitability for molecular docking studies. All ligands were first subjected to energy minimization in order to maximize their structural conformations. The reduced ligands were then transformed into the PDBQT format, which is the file type needed for docking. Molecular Docking Analysis To analyze the top-ranked compounds' binding affinities with the target proteins, molecular docking was carried out using PyRx software 0.8 . After docking, the binding modes were analyzed and interpreted using BIOVIA Discovery Studio and Chimera X software to investigate receptor-ligand interactions. Compounds with high binding affinities (-7.0 to -10.0 kcal/mol) were chosen for additional examination. Key chemical interactions that support the stability and specificity of ligand binding, such as hydrogen bonding, hydrophobic contacts, and π-π stacking, were identified using this post-docking analysis. ADMET and Physiochemical Analysis The ADME prediction was carried out by using the SWISS ADME [ 26 ] and ADMETLab [ 27 ] databases, which are openly available to assess the pharmacokinetics and drug-likeness of active compounds. Many properties were investigated, including the number of rotatable bonds, the molecular weight, and the donors and acceptors of hydrogen bonds. The toxicity and safety evaluation of chemicals were also conducted using the ProTox-II [ 28 ] web-based server. ProTox-II uses fragment-based methods, pharmacophore modeling, machine-learning algorithms, and molecular similarity analysis. The server generated 33 models with confidence scores that depicted the potential toxicity profile of the medication after receiving a 2D chemical structure as input. DFT Calculations The DFT/B3LYP method with multiple basis sets in the Gaussian 09 software was used to fully optimize the geometries of the chosen drug candidates [ 29 ]. The Gaussian output files were evaluated using the GaussView molecular visualization application [ 30 ]. Using HOMO–LUMO energy values based on the numbering scheme assigned to the compounds, DFT-derived quantum chemical parameters were calculated in the gas phase. Additionally, the excitation energy, oscillator strength, and effective charges of the coordinating groups of the optimized structures were determined. Molecular Dynamic Simulation The stability of the docked complexes was studied through the molecular dynamics (MD) Simulation analysis [ 31 ]. Top compounds identified through the molecular docking and ADME analysis were subjected to the MD analysis. The Desmond Module of Schrodinger explicit solvent MD package along with a fixed OPLS 2005 force field was used for the MD simulation [ 32 , 33 ]. The Protein Preparation Wizard was used to create a protein-ligand combination with a predetermined SPC (Simple Point Charge) water model and an orthorhombic box shape (10 Å × 10 Å × 10 Å). To neutralize it, a NaCL solution was introduced to the system. The isosmotic condition of the simulation box remains intact through the addition of 0.15 m NaCl. A specified equilibrium was achieved before simulation's production run. Than the modal system was submitted for simulation at 200ns steps with the OPLS_2005 force field. A temperature of 300 K was maintained using the Nosé-Hoover chain thermostat algorithm, while a pressure of 1.01325 bar with isotropic coupling was maintained using the Martyna-Tobias-Klein barostat method. All other parameters were maintained at their default values, with a Coulombic cutoff of 0.9 nm [ 34 ]. Finally, the results of the MD simulation were examined for solvent accessible surface area (SASA), radius of gyration (Rg), root mean square deviation (RMSD), and root mean square fluctuation (RMSF) etc at 200ns using the Simulation Interaction Diagram (SID) tool. MMGBSA binding free energy analysis The MM-GBSA method and the default settings of the Prime MM-GBSA module in Schrödinger software were used to calculate the binding free energies (ΔGBind) of the selected protein–ligand complexes. The analysis was conducted using the Glide pose viewer file, and the relative binding affinity of ligands to the receptor which was expressed in kcal/mol was calculated using MM-GBSA. Larger negative binding energies, which are estimates of the free binding energies, indicate a stronger binding affinity [ 35 , 36 ]. Results Pharmacophore Modelling To identify potential treatment options, a pharmacophore model was developed using the three-dimensional (3D) structures of FDA-approved drugs commonly used to treat heart disease. A pharmacophore describes a molecule's primary chemical properties that are essential to its biological activity. Three essential structural elements for successful ligand binding were identified by the model in this study: an aromatic ring, which is necessary to stabilize interactions with the target protein, as well as characteristics that have electron donor and acceptor characteristics (Fig. 1 ). The hits selection was refined using Pharmacophore Fit Score and Pharmacophore Feature Matching, two important evaluation techniques. Each compound's alignment with the pharmacophore model was gauged by its Fit Score; higher scores suggested a higher chance of binding successfully. Based on their agreement with the model, 149 of the 587 compounds that were examined were determined to be possible hits. Molecular Docking Analysis Out of 149 pharmacophore-screened candidates, the top 17 compounds with the angiotensin II type 1 receptor (AT1R) have docking scores summarized in (Table 1 ) due to their high binding affinities. The strength of anticipated interactions is indicated by binding energy values, which are represented in kcal/mol. Stronger binding is indicated by higher negative values. With a value of -10.6 kcal/mol, MOL004805 showed the highest binding by far, followed by MOL004810 (-9.5 kcal/mol), MOL004806, and MOL002776 (both − 9.4 kcal/mol). Even though a number of compounds showed higher docking scores, MOL002140, also known as perlolyrine, was selected as the last lead contender for additional in-depth examination because of its docking score of -8.2 kcal/mol. Based on a combination of binding affinity, excellent pharmacophore alignment, anticipated pharmacokinetic features, and potential for drug-likeness, Perlolyrine was chosen as a promising compound for further investigation in AT1R targeting. Table 1 Binding affinities (kcal/mol) of the top 17 pharmacophore-screened compounds docked with AT1R. Compounds AT1R MOL000098 -8.4 MOL000354 -8.4 MOL000379 -7 MOL000398 -7.4 MOL000433 -9 MOL000436 -7 MOL000500 -8.1 MOL001789 -7.5 MOL002135 -9.1 MOL002140 -8.2 MOL002311 -9.1 MOL002776 -9.4 MOL004805 -10.6 MOL004806 -9.4 MOL004808 -8.5 MOL004810 -9.5 MOL004811 -8.5 Perlolyrine interacts with several amino acid residues by utilizing a mix of water-mediated contacts, hydrophobic interactions, and hydrogen bonding. Remarkably, TRP84 and TYR87 interact with Perlolyrine's aromatic core to promote π-π stacking and hydrophobic stability. As a donor of hydrogen bonds, perlolyrine's hydroxyl (-OH) group interacts directly with ASP281, a crucial residue that may be essential for either receptor activation or inhibition. Water bridges containing residues such as ARG167, TYR35, and GLY22 facilitate additional hydrogen bonding and polar interactions, improving ligand anchoring inside the active site (Fig. 2 ). According to the interaction profile, perlolyrine engages residues frequently engaged in ligand recognition and signaling, forming a deep and stable binding within the receptor's ligand-binding cavity. Toxicity and Physicochemical Properties The ADMET profile of Perlolyrine (MOL002140) lends credence to its potential as an antihypertensive drug. Good oral bioavailability is essential for chronic management medications like antihypertensives, and it is indicated by its favorable physicochemical features, including a moderate molecular weight (266.110 g/mol), appropriate lipophilicity (logP = 2.384), and compliance with Lipinski, Pfizer, and Veber criteria (Table 2 ). Perlolyrine's blood-brain barrier (BBB) crossing capability might also help regulate key elements of blood pressure management if necessary. Its therapeutic importance is further supported by its interaction with the angiotensin II type 1 receptor (AT1R), a crucial target in blood pressure regulation. Because it is not carcinogenic, mutagenic, cardiotoxic, or cytotoxic, perlolyrine is especially useful for long-term use in the treatment of chronic conditions like hypertension. However, given that hypertension patients frequently need polypharmacy, its function as a substrate and inhibitor of several CYP enzymes particularly CYP3A4 and CYP2C9 highlights the significance of taking possible drug-drug interactions into account. Table 2 ADMET profile of Perlolyrine showing its favorable pharmacokinetic, metabolic, and safety properties for use as an antihypertensive agent. MOL002140 Molecular Weight (MW) 266.110 g/mol TPSA 57.430 Ų logS -3.970 logP 2.384 Lipinski Rule Yes Pfizer Rule Yes Veber Yes Caco-2 Permeability -4.858 Pgp-inhibitor No Pgp-substrate Yes BBB Penetration Yes CYP1A2 inhibitor Yes CYP1A2 substrate No CYP2C19 inhibitor Yes CYP2C19 substrate Yes CYP2C9 inhibitor Yes CYP2C9 substrate Yes CYP2D6 inhibitor No CYP2D6 substrate Yes CYP3A4 inhibitor Yes CYP3A4 substrate Yes Eye Corrosion No Genotoxic Carcinogenicity Rule No HBA 2 HBD 3 Molecular refractivity 83.28 Number of rotable bonds 2 Carcinogenicity No Mutagenicity No Cytotoxicity No Cardiotoxicity No In respect to recognized drug-likeness boundaries, the radar plot displays Perlolyrine's physicochemical and pharmacokinetic profile. The blue line displays the actual values of Perlolyrine's characteristics, the pink area displays the lower limitations, and the orange shaded area reflects the higher permitted limits. The majority of measures, including molecular weight, lipophilicity, solubility, and hydrogen bonding characteristics, show that perlolyrine falls well within the permitted range, demonstrating strong adherence to important drug-likeness requirements. Small variations in a few regions do not affect its overall drug-like capabilities and are still within a reasonable range. Density functional theory (DFT) calculations According to Density Functional Theory (DFT), Perlolyrine's (MOL002140) electronic properties and chemical reactivity were assessed. Important reactive areas of the molecule are revealed by the distribution of the frontier molecular orbitals, HOMO (Highest Occupied Molecular Orbital) and LUMO (Lowest Unoccupied Molecular Orbital), as seen in (Fig. 4 ). While the LUMO is delocalized throughout the molecule, emphasizing electron-accepting locations pertinent to its interaction with biological targets, the HOMO is primarily clustered around the indole ring, suggesting possible electron-donating sites. The calculated energy values of -0.85 eV for LUMO and − 4.80 eV for HOMO provide an energy gap of 3.95 eV, indicating that perlolyrine has favorable electronic stability and moderate reactivity, which are in good agreement with the characteristics of a drug-like molecule. A number of quantum descriptors were obtained. The softness (S) is 0.25 and the chemical hardness (η) is 1.97, indicating a balanced reactivity appropriate for molecular interactions. The molecule's propensity to attract electrons is shown by its electronegativity (χ) of 2.82, while its ability to absorb electrons upon binding is reflected by its electrophilicity index (ω) of 2.02. With a maximum electronic charge transfer (ΔNmax) of 1.43 and a chemical potential (Pi) of -2.82, perlolyrine is a good candidate for antihypertensive medication development due to its reasonable electronic stability and binding ability (Table 3 ). Table 3 Quantum chemical parameters derived from DFT calculations for Perlolyrine, indicating its electronic stability, reactivity, and interaction potential. Compound HOMO LUMO Eg ꭓ ɳ σ Pi S ω ΔN max MOL02140 -4.80 -0.85 3.95 2.82 1.97 0.51 -2.82 0.25 2.02 1.43 According to Density Functional Theory (DFT) calculations, the noncovalent interaction profile of perlolyrine (MOL002140) is shown in detail in Fig. 5 . The types and intensities of intramolecular and intermolecular interactions are quantitatively mapped in (Fig. 5 A), which is an RDG (Reduced Density Gradient) against sign(λ₂)ρ plot. The dense clustering of points in the green zone close to sign(λ₂)ρ = 0, which corresponds to low RDG values (~ 0.5 to 1.5), is a noticeable characteristic in this plot. This clearly shows that weak van der Waals interactions predominate across the molecule surface. Furthermore, the sharp blue spikes on the left side (sign(λ₂)ρ < 0, particularly close to -0.035) are suggestive of attractive interactions like hydrogen bonds or π–π stacking, indicating that certain atoms in the structure are engaged in directional, potentially biologically significant stabilizing interactions. On the other hand, red dots on the right (sign(λ₂)ρ > 0.02) indicate locations where the molecule undergoes internal strain or spatial crowding, and they also reflect steric repulsion or close interactions between electron-rich regions. A 3D NCI (Non-Covalent Interaction) isosurface projected onto the Perlolyrine molecular structure allows the spatial visualization of these interactions in (Fig. 5 B). The molecule exhibits broad green isosurfaces on both side chains and aromatic rings, indicating that dispersion (van der Waals) interactions are common and probably play a major role in the molecule's binding potential and conformational stability. Notably, the presence of hydrogen bonding donors and acceptors is confirmed by the direct correlation between the attractive contacts shown in the RDG plot and localized blue patches close to the nitrogen and oxygen atoms, such as those in the indole ring and side-chain substituents. The bioactive conformation of the molecule may be influenced by a small red patch in the central aromatic core, which indicates an area of steric repulsion that is probably caused by ring-ring crowding or torsional strain. These findings draw attention to the molecule's structural flexibility and reactivity, two crucial properties that support its potential as a helpful ligand in drug development, particularly with regard to antihypertensive activity. Molecular Dynamic Simulation The molecular dynamics (MD) simulation results shown in (Fig. 6 ) give a complete examination of Perlolyrine's structural stability, flexibility, and binding interactions with the angiotensin II type 1 receptor (AT1R), a critical target in hypertension treatment. Root Mean Square Deviation (RMSD) of the AT1R protein backbone (in blue) and the ligand (Perlolyrine, in red) over a 200 ns trajectory is displayed in (Fig. 6 A). Following an initial equilibration phase, the protein RMSD stabilizes at approximately 3.5 Å, suggesting a reasonably stable protein-ligand combination. Throughout the simulation, the ligand RMSD stays below 2.0 Å, indicating that perlolyrine binds to the AT1R binding site with strength and stability. The AT1R residues' RMSF (Root Mean Square Fluctuation), which gauges per-residue flexibility throughout the simulation, is shown in (Fig. 6 B). As is common for membrane proteins like AT1R, the majority of residues exhibit low to moderate variations (< 2 Å), with more flexibility seen at the terminal and loop regions. The idea of a well-anchored ligand is supported by the stable core areas that are engaged in ligand binding showing little fluctuation. The interaction proportion of particular AT1R residues with perlolyrine is shown in (Fig. 6 C), which shows how frequently each residue makes contact throughout the simulation. Residues like PHE115, TRP84, ARG167, and MET284 exhibit large interaction fractions, highlighting their crucial involvement in ligand stability, especially through hydrogen bonding and hydrophobic interactions (shown by the color stacking). Interestingly, transmembrane domain residues play a major role, matching the known binding site design of GPCRs. The quantity and regularity of ligand-protein connections are shown in the time-resolved interaction contact map shown in (Fig. 6 D). The durability of the Perlolyrine–AT1R complex is further supported by the top graph, which displays the overall number of interactions over the course of the simulation and stays comparatively constant. Persistent binding hotspots that are crucial for ligand recognition and receptor modulation are highlighted by the bottom heatmap, which shows ongoing interactions with important residues like PHE115, TYR87, ARG167, and MET284. Additionally, there is very little variation in the radius of gyration (Rg) at 3.9 Å, suggesting that the protein's overall compactness is unaffected and that no substantial unfolding takes place during the simulation. The intra-molecular hydrogen bonds (intraHB) show intermittent formation, which is typical for receptor-ligand systems and reflects dynamic reorganization of hydrogen bonding interactions that stabilize the binding pocket and surrounding residues. The polar surface area (PSA), solvent-accessible surface area (SASA), and molecular surface area (MolSA) all exhibit steady trends devoid of sharp oscillations, suggesting that the solvation characteristics of the ligand and the protein's solvent exposure are constant over time (Fig. 6 E). Significantly, PSA varies at about 90 Ų, indicating that the complex's polar portions are still accessible and may help with interactions with nearby ions or water molecules, which is essential for bioactivity in physiological settings. By examining the protein's secondary structural elements (%SSE) during the course of the simulation shown in (Fig. 6 F). With α-helices and β-strands (colored cyan and red, respectively) being well-preserved, the plot shows that the overall percentage of secondary structure stays impressively consistent. This structural preservation demonstrates that the binding of perlolyrine does not cause AT1R to undergo substantial conformational instability, which is essential for maintaining the receptor's functional integrity. These findings collectively provide more evidence that perlolyrine and AT1R form a stable, compact complex that preserves the structural characteristics and solvent dynamics of the receptor. Its prospective use as a stable and selective antihypertensive drug that targets AT1R depends on these characteristics. During the simulation, the polar plots and accompanying histograms of angular distributions shown in (Fig. 6 G) most likely depict side chain torsion angles or the vector orientations of important residues or the ligand itself. A bimodal angular distribution peaking close to ± 180° is seen in the blue polar plot and histogram, suggesting a toggling or conformational flipping between two dominant states. This implies that certain atoms or vectors in the Perlolyrine–AT1R complex take on two different orientations during the simulation, which could be a reflection of conformational changes in the binding pocket or rotational freedom. The green histogram indicates considerable flexibility and conformational variability, possibly in a loop region or solvent-exposed part of the receptor, as it shows a wider and more irregular distribution along the full angular range. A highly stable dihedral or vector alignment is indicated by the red angular distribution's narrowness and high centralization around 0°, which most likely reflects a limited interaction inside the binding site that doesn't change over time. Together, these graphs show that the binding interface is both flexible and stable, with certain parts of the complex undergoing dynamic reorientation while others retain stiff, stable structures. The key motions in the conformational space are captured in the 3D Principal Component Analysis (PCA) plot of the protein-ligand complex over the simulation trajectory, which is displayed in (Fig. 6 H). The variation explained by each component is confirmed by the diagonal plots (PC1 vs. PC1, etc.). The complex traverses several conformational states instead of staying in a single dominant conformation, as shown by the off-diagonal projections, which show clear clustering patterns, especially in PC1 vs. PC2 and PC2 vs. PC3 plots. The dispersion between PC1 and PC2 indicates that the AT1R structure undergoes significant global motions as a result of perlolyrine binding. The presence of several dense clusters throughout time suggests transitions between metastable states, and the color gradients (from light to dark orange/brown) most likely indicate the simulation duration. This result implies that AT1R dynamics are modulated by perlolyrine binding in a manner that may be functionally important, influencing either receptor inhibition or activation. Together, these findings demonstrate that Perlolyrine interacts with AT1R in a variety of stiff and flexible ways, with both structural stability and dynamic sampling of alternate conformations confirmed by angular and PCA data. Perlolyrine's significance as a possible small-molecule modulator may be supported by these dynamics, which may be essential to comprehending how it affects AT1R activity in the setting of hypertension. Molecular Mechanics Generalized Born Surface Area The Molecular Mechanics Generalized Born Surface Area (MM-GBSA) indicates a highly favorable and stable association between the ligand and the protein. The total binding free energy (ΔG Bind) is -162.52 kcal/mol, which is significantly negative. With a value of -155.92 kcal/mol, the van der Waals interactions (ΔG Bind vdW) provide a significant contribution to the energetic contributions, emphasizing the significance of close-contact forces and hydrophobic interactions in ligand binding. Additionally, electrostatic (Coulomb) interactions play a positive role; ΔG Bind Coulomb = -48.89 kcal/mol indicates that Perlolyrine and charged residues in the AT1R binding pocket have a strong electrostatic complementarity. Conversely, the solvation energy (ΔG Bind Solv GB) shows a high positive value of + 116.11 kcal/mol, which represents the energetic cost of desolvating the receptor and the ligand during complex formation. The electrostatic and van der Waals contributions are so high that the overall binding is still very advantageous in spite of this penalty. The tiny positive contributions of 6.17 kcal/mol and 1 kcal/mol, respectively, from the covalent interaction term (ΔG Bind Covalent) and another unidentified component (labeled "1") suggest that they play insignificant or marginally destabilizing roles in the total binding energetics (Fig. 7 ). Discussion Hypertension is a complex cardiovascular condition that contributes significantly to morbidity and mortality worldwide. The renin-angiotensin system (RAS) is essential to its pathogenesis, especially the angiotensin II type 1 receptor (AT1R), a G protein-coupled receptor (GPCR) that mediates the pro-inflammatory, pro-fibrotic, and vasoconstrictive effects of angiotensin II [ 37 ]. Chronic AT1R overactivation worsens hypertension pathophysiology by increasing systemic vascular resistance, aldosterone production, and progressive cardiac and renal remodeling [ 38 ]. As a result, AT1R is now a well-established target in antihypertensive medication, with a number of ARBs (angiotensin receptor blockers), including valsartan and losartan, effectively lowering cardiovascular events by selectively inhibiting AT1R [ 39 ]. A β-carboline alkaloid called perlolyrine is identified in our work as a new AT1R regulator with encouraging antihypertensive potential. Perlolyrine has demonstrated pharmacological actions related to the pathophysiology of hypertension, despite the fact that it has not yet been extensively investigated in the context of cardiovascular diseases. Notably, it has been observed that β-carbolines, such as Perlolyrine, have neuroprotective, anti-inflammatory, and antioxidant characteristics that mechanistically interact with AT1R signaling pathways [ 40 , 41 ]. Specifically, oxidative stress and inflammation, which are downstream effects of AT1R activation, are necessary for the vascular damage brought on by hypertension [ 42 ]. The finding that perlolyrine is a stable AT1R binder adds to its previously documented bioactivities and creates new avenues for research into its possible repurposing as a cardiovascular treatment. The study's molecular docking analyses reveal that perlolyrine interacts closely with the AT1R transmembrane pocket through π–π stacking, hydrogen bonding, and polar interactions involving residues such as TRP84, TYR87, ARG167, and ASP281. Studies on AT1R-7 receptor activation and ligand recognition frequently include these acids [ 43 ]. Despite not having the lowest docking score of any of the compounds evaluated, perlolyrine was a strong candidate for additional research due to its appealing pharmacokinetic profile, chemical stability, and binding energy balance. Because of its ADMET profile, perlolyrine is a more practical choice for long-term antihypertensive treatment. Although more research is required to fully understand its dual role, its predicted ability to penetrate the blood-brain barrier (BBB) may be significant in regulating central sympathetic outflow, which is known to contribute to hypertension. It lacks signs of mutagenicity and carcinogenicity, has adequate lipophilicity and solubility, and satisfies important drug-likeness requirements [ 44 ]. Furthermore, the molecule's role as a moderate CYP3A4 and CYP2C9 substrate and inhibitor highlights the importance of researching drug-drug interactions, particularly in hypertensive patients who frequently experience polypharmacy [ 45 ]. According to our DFT-based molecular orbital and noncovalent interaction (NCI) study on chemical reactivity, perlolyrine has a favorable HOMO-LUMO gap (3.95 eV) and participates in significant hydrogen bonding and van der Waals interactions. In GPCR–ligand complexes, these electrical characteristics have been connected to improved binding stability and affinity [ 46 ]. Perlolyrine's structure includes specific nucleophilic and electrophilic regions that aid in its dynamic and specific binding to AT1R target sites. MD modeling provided additional confirmation of perlolyrine's long-term structural compatibility with AT1R. The complex exhibited persistent protein-ligand interactions, a tight radius of gyration, and a constant root mean square deviation (RMSD) over 200 ns. These results are in line with earlier simulation-based studies that demonstrated the importance of contact persistence and conformational stability in potent AT1R antagonists [ 47 ]. Since PCA found metastable states, it is possible that perlolyrine keeps AT1R in an inactive conformation. This is consistent with the expected antagonistic effect seen in existing ARBs [ 48 ]. Furthermore, secondary structure conservation and stable surface area characteristics (SASA, PSA, and MolSA) show that no significant conformational changes have taken place and that the physiological architecture of the receptor is maintained during modulation. The MM-GBSA analysis showed that perlolyrine bound to the AT1R receptor with a total binding free energy (ΔG Bind) of -162.52 kcal/mol, which is a strong and energetically advantageous binding. Significant van der Waals interactions (–155.92 kcal/mol) and Coulombic contributions (–48.89 kcal/mol) are the main drivers of this stability, surpassing the desolvation penalty (ΔG Bind Solv GB: +116.11 kcal/mol). These findings support the idea that ligand stability and affinity in the AT1R binding pocket are mostly dependent on hydrophobic and electrostatic forces.The binding appears to be non-covalent and selective based on the small contribution from covalent interactions (+ 6.17 kcal/mol) and other factors. These results validate that perlolyrine can stably occupy and regulate the AT1R receptor, supporting the molecular dynamics findings. Interestingly, because perlolyrine is a natural β-carboline, it belongs to a class of chemicals that have been historically associated with neuroactivity and MAO inhibition [ 49 ]. Although this increases the possibility of off-target effects, it also offers chances for dual-purpose cardiovascular–neurological uses where central and peripheral pathways meet, like in hypertensive encephalopathy or stress-induced hypertension [ 50 ]. This study links perlolyrine's established bioactivities with new cardiovascular uses in addition to presenting it as a viable AT1R antagonist. It bolsters the idea that naturally occurring alkaloids can function as potent GPCR target modulators, providing multi-targeted treatment approaches for complicated chronic conditions like hypertension. Conclusion A stable, bioactive, and pharmacologically promising AT1R modulator, perlolyrine has been discovered using extensive pharmacophore modeling, molecular docking, ADMET screening, DFT computations, and MD simulation. Its function as an antagonist with possible antihypertensive effects is supported by its structural flexibility and capacity to consistently create contacts with important AT1R residues. To support its therapeutic potential for the treatment of hypertension, these computational results call for additional experimental validation, such as in vitro binding tests and in vivo efficacy investigations. Declarations Conflict of Interest Authors declare no conflict of interest. Statement on the Use of Artificial Intelligence AI-based tools (Grammarly and QuillBot) were used solely for language editing, grammar correction, and rephrasing to improve clarity. No AI tools were used for data analysis, figure generation, or interpretation of results. The authors take full responsibility for the content of this manuscript. Funding Note: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Authors Contribution Iqra Azhar : Data collection, Formal analysis, Review, and writing of the initial draft. Imran Ali Khan : Formal analysis, Review, and writing of the initial draft. Saleh M. Bufarwa : Material and Methods, and Review and writing of the initial draft. Mustapha Belaidi : Formal analysis. Sadia Zahid : Conceptualization, investigation, and supervision. Bushra Shakoor : Formal Analysis. Aneeqa Batool : Review and writing of the final version of the manuscript. Huma Fatima : Materials and Methods. Ayesha Farooq : Review and writing of the final version of the manuscript. Aqsa Nazir : Review and writing of the final version of the manuscript. All authors reviewed the final version of the manuscript and approved it for publication. Acknowledgment The authors would like to acknowledge the support and resources provided by the Department of Biotechnology, University of Okara. Data Availability Statement All computational data generated or analyzed during this study are available from the corresponding author upon reasonable request. References Giles TD et al (2005) Expanding the Definition and Classification of Hypertension. J Clin Hypertens 7(9):505–512 Giles TD et al (2009) Definition and classification of hypertension: an update. J Clin Hypertens (Greenwich) 11(11):611–614 Organization WH (2009) Global health risks: mortality and burden of disease attributable to selected major risks. World Health Organization Weir MR, Dzau VJ (1999) The renin-angiotensin-aldosterone system: a specific target for hypertension management. Am J Hypertens 12(S9):205S–213S Yan Y et al (2019) Structural basis for the specificity of renin-mediated angiotensinogen cleavage. 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J Ginseng Res 36(1):16–26 Hou YZ et al (2004) Protective effect of Ligusticum chuanxiong and Angelica sinensis on endothelial cell damage induced by hydrogen peroxide. Life Sci 75(14):1775–1786 Zhi X et al (2024) Therapeutic potential of Angelica sinensis in addressing organ fibrosis: A comprehensive review. Biomed Pharmacother 173:116429 Mahadevan S, Park Y (2008) Multifaceted therapeutic benefits of Ginkgo biloba L.: chemistry, efficacy, safety, and uses. J Food Sci 73(1):R14–R19 Tassell MC et al (2010) Hawthorn (Crataegus spp.) in the treatment of cardiovascular disease. Pharmacogn Rev 4(7):32–41 Kang HS et al (1996) Anti-inflammatory effects of Stephania tetrandra S. Moore on interleukin-6 production and experimental inflammatory disease models. Mediators Inflamm 5(4):280–291 Adesso S et al (2018) Astragalus membranaceus Extract Attenuates Inflammation and Oxidative Stress in Intestinal Epithelial Cells via NF-κB Activation and Nrf2 Response. 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Nutrients, 11(4) Spindola HM et al (2012) The antinociceptive activity of harmicine on chemical-induced neurogenic and inflammatory pain models in mice. Pharmacol Biochem Behav 102(1):133–138 Grobe AC et al (2006) Increased oxidative stress in lambs with increased pulmonary blood flow and pulmonary hypertension: role of NADPH oxidase and endothelial NO synthase. Am J Physiol Lung Cell Mol Physiol 290(6):L1069–L1077 Zhang H et al (2015) Structure of the Angiotensin receptor revealed by serial femtosecond crystallography. Cell 161(4):833–844 Dampney RA (2015) Central mechanisms regulating coordinated cardiovascular and respiratory function during stress and arousal. Am J Physiol Regul Integr Comp Physiol 309(5):R429–R443 Nebert DW, Russell DW (2002) Clinical importance of the cytochromes P450. Lancet 360(9340):1155–1162 Parr RG, Weitao Y (1995) Density-Functional Theory of Atoms and Molecules. Oxford University Press Kellici TF et al (2019) The dynamic properties of angiotensin II type 1 receptor inverse agonists in solution and in the receptor site. Arab J Chem 12(8):5062–5078 Wingler LM et al (2019) Angiotensin Analogs with Divergent Bias Stabilize Distinct Receptor Conformations. Cell 176(3):468–478e11 Berlowitz I, Egger K, Cumming P (2022) Monoamine Oxidase Inhibition by Plant-Derived β-Carbolines; Implications for the Psychopharmacology of Tobacco and Ayahuasca. Front Pharmacol 13:886408 Esler M, Lambert E, Schlaich M (2010) Point: Chronic activation of the sympathetic nervous system is the dominant contributor to systemic hypertension. J Appl Physiol (1985), 109(6): p. 1996-8; discussion 2016. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7499142","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":508000775,"identity":"a5fa8581-56b2-4aa7-8f06-d8a5930f3fff","order_by":0,"name":"Adeeba Riaz","email":"","orcid":"","institution":"Faculty of Life Sciences, Department of Biotechnology, University of Okara, Okara, 53600, Punjab, Pakistan","correspondingAuthor":false,"prefix":"","firstName":"Adeeba","middleName":"","lastName":"Riaz","suffix":""},{"id":508000776,"identity":"54f380e7-7d1b-439b-b260-b85f754e9aa0","order_by":1,"name":"Iqra Azhar","email":"","orcid":"","institution":"Faculty of Life Sciences, Department of Biotechnology, University of Okara, Okara, 53600, Punjab, Pakistan","correspondingAuthor":false,"prefix":"","firstName":"Iqra","middleName":"","lastName":"Azhar","suffix":""},{"id":508000777,"identity":"9463f5ab-c55f-406f-8fd6-8c6ade918e53","order_by":2,"name":"Imran Ali Khan","email":"","orcid":"","institution":"Medical Genomic Research Department, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, Ministry of National Guard-Health Affairs, Riyadh-11481, Saudi Arabia","correspondingAuthor":false,"prefix":"","firstName":"Imran","middleName":"Ali","lastName":"Khan","suffix":""},{"id":508000778,"identity":"c3f2feb1-024a-4217-a54c-ac1c5ac2a28c","order_by":3,"name":"Salah W. 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(A) AT1R, (B) Perlolyrine.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7499142/v1/4de457f4aa9aad9305e607e0.png"},{"id":90478299,"identity":"2a5b7a65-28ac-484d-8d35-cc4d24d70236","added_by":"auto","created_at":"2025-09-03 07:24:52","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":130027,"visible":true,"origin":"","legend":"\u003cp\u003eRadar plot comparing Perlolyrine’s physicochemical properties (blue) against the lower (pink) and upper (orange) acceptable limits for drug-likeness assessment.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7499142/v1/75675f2749afd849268f3620.png"},{"id":90478303,"identity":"96e350a9-06c2-4fac-9dbb-766fe58596b2","added_by":"auto","created_at":"2025-09-03 07:24:56","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":174124,"visible":true,"origin":"","legend":"\u003cp\u003eHOMO-LUMO orbital distribution and energy gap (Eg) of Perlolyrine (MOL002140) illustrating electronic transitions and chemical reactivity based on DFT analysis.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7499142/v1/972c539717e09fe1793bacbc.jpg"},{"id":90478305,"identity":"cfdb9484-d307-471c-95e3-042b419d9007","added_by":"auto","created_at":"2025-09-03 07:24:57","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":543739,"visible":true,"origin":"","legend":"\u003cp\u003eRDG plot and NCI isosurface of Perlolyrine showing key noncovalent interactions, including hydrogen bonding, van der Waals forces, and steric repulsion based on DFT analysis.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7499142/v1/e67386120c50a78bd46d0d0f.png"},{"id":90478236,"identity":"94348e8a-f9ce-4d3f-9d41-42faf067997d","added_by":"auto","created_at":"2025-09-03 07:24:50","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":777856,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular dynamics (MD) analysis of the Perlolyrine–AT1R complex over 200 ns. (A) RMSD plots of protein backbone and ligand showing structural stability. (B) RMSF plot indicating residue-level flexibility. (C) Interaction fraction of key residues involved in ligand binding. (D) Contact timeline showing stability and persistence of ligand-protein interactions. (E) Time evolution of structural and surface properties: RMSD, radius of gyration (Rg), intramolecular hydrogen bonds (intraHB), molecular surface area (MolSA), solvent-accessible surface area (SASA), and polar surface area (PSA). (F) Secondary structure elements (%SSE) and residue-wise structural distribution showing maintained protein architecture throughout the simulation. Angular distribution plots (G) reveal distinct torsional behaviors, with both flexible and rigid orientations observed during the simulation. Principal component analysis (H) shows conformational clustering, indicating dynamic sampling of multiple metastable states in the ligand receptor complex.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7499142/v1/cc92021234c5d0bb39a6448a.png"},{"id":90478296,"identity":"06aff5ce-ef79-48be-8501-4f1bb2ce643f","added_by":"auto","created_at":"2025-09-03 07:24:51","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":52244,"visible":true,"origin":"","legend":"\u003cp\u003eMM-GBSA analysis of Perlolyrine–AT1R complex. The binding free energy components are represented in distinct colors: total ΔG Bind (green), Coulomb energy (light blue), covalent energy (yellow), solvation energy using GB model (dark green), and van der Waals energy (dark blue). The total binding energy reflects strong ligand-receptor affinity, driven primarily by van der Waals and electrostatic interactions.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7499142/v1/a74eb1ec7884c15dff8f8f93.png"},{"id":90478545,"identity":"8dec0fac-f380-4932-bf24-4742572cf30b","added_by":"auto","created_at":"2025-09-03 07:33:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2606266,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7499142/v1/c533088d-99dd-4796-9fb4-71781d212991.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eComputational Identification and Evaluation of Perlolyrine as a Promising AT1R Antagonist for Hypertension Therapy\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHypertension is characterized as a progressive cardiovascular condition caused by multiple and interconnected etiologies. As it advances, it could result in structural and functional cardiac and vascular abnormalities that harm the brain, kidneys, heart, vasculature, and other organs, causing early morbidity and death [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The World Health Organization (WHO) estimates that 7.5\u0026nbsp;million deaths, or 12.8% of all deaths, are attributed to high blood pressure [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe main role of RAAS is to manage BP and the water in your body. High blood pressure can result from lack of sodium chloride in the kidney tubules, a problem with blood pressure or activation of the nervous system that controls fight or flight reaction [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In to the system, renin is the enzyme that sets off the process by secreting angiotensinogen. It alters it, making it a decapeptide called angiotensin I (Ang I). The ACE converts Ang I into Ang II, an important octapeptide which is much more likely when substrates are adequately glycosylated [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAng II controls many activities in the body by liganding to and activating the G-protein-coupled angiotensin II type 1 receptor (AT1R) found in the sarcolemma. When Ang II binds to AT1R, several tyrosine\u0026ndash;histidine and phenylalanine\u0026ndash;histidine interactions are observed. When intracellular kinases, like MAPKs, are introduced and G-protein psych settings are triggered, they cause signaling reactions to unfold. As well, beta arrestins regulate additional processes such as signaling, making receptors less sensitive and bringing receptors into the cell [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. An overstimulation of Ang II or poor breakdown of AT1R caused by aberrant glycosylation may lead to high blood pressure [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The rational design of AT1 receptor antagonists is essential for the development of therapeutic drug that target cardiovascular diseases. Sartans, a class of drugs intended to stop Angiotensin II from attaching and activating on the AT1 receptor, have demonstrated notable therapeutic efficacy [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTraditionally, traditional Chinese medicine (TCM) has often been used to treat cardiovascular disorders which include components that may be therapeutically helpful. Danshen (Salvia miltiorrhiza) has potent anti-inflammatory, antioxidant and anti-thrombotic features, mainly due to tanshinones and salvianolic acids. It helps prevent atherosclerosis, soothes ischemic heart symptoms and promotes blood circulation in the heart by hindering oxidative stress and problems with the heart\u0026rsquo;s endothelial cells [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSince ginseng can ease inflammation and lower lipids, it helps treat both hypertension and hyperlipidemia. Moreover, it stimulates the body to make nitric oxide (NO) which relaxes the blood vessels [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Benefits of Schisandra chinensis, including protecting mitochondria and reducing oxidative stress, are useful to individuals coping with ischemic heart disease [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. It has been observed that this herb can assist in treating ischemic heart disease as well as promote normal heart function. The major components in Chuanxiong are ligustilide and ferulic acid which help relax blood vessels and stop blood clots. For a long time, medicine has used it to remove blood blockages and encourage blood circulation [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis herb is recognized for assiting in blood circulation and making blood more fluid. It helps to control hypertension by changing how the blood vessels work and lessening the stiffness of the arteries [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Ginkgo biloba contains flavonoids and terpenoids which help the small blood vessels, lessen oxidative stress and improve how the endothelium functions. Ginkgo extract may both prevent ischemia and play a role in reducing arterial plaque development, clinical studies suggest [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHawthorn's (Crataegus spp.) polyphenolic content improves cardiovascular health by lessening the signs of heart failure and hypertension [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The main ingredient in Stephania tetrandra, tetrandrine, has anti-inflammatory and vasodilatory qualities that help control calcium channels and lessen vascular remodeling [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eLicorice contains glycyrrhizin, an anti-inflammatory and antioxidant substance. By reducing arterial stiffness and regulating lipid metabolism, it safeguards the heart [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Numerous cardioprotective advantages of astragalus include enhancing heart health and reducing inflammation [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWhile notoginseng's anticoagulant properties improve vascular health and reduce myocardial ischemia, cinnamon prevents cardiovascular disorders linked to metabolic syndrome by controlling blood pressure and glucose levels [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study aimed to investigate the potential of natural compounds derived from specific herbs as AT1R modulators, taking into account the significance of the Ang II-AT1R axis in the pathophysiology of hypertension. Using FDA-approved AT1R antagonists as references, we assessed the bioactive compounds using computational techniques including virtual screening, molecular docking, ADMET profiling, density functional theory (DFT) calculations, molecular dynamics (MD) simulations, and post-MD analysis. Using MD simulations, thermochemical analysis, and molecular orbital analysis, we assessed their drug-like properties. By changing vascular function and reducing blood pressure, we believe that targeting AT1R with these natural compounds may benefit those who suffer from hypertension.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eVirtual Screening\u003c/h2\u003e\u003cp\u003eA set of 587 compounds derived from traditional Chinese medicinal herbs, such as Danshen, Ginseng, Schisandra chinensis, Chuanxiong, Angelica sinensis, Ginkgo biloba, Hawthorn, Stephania tetrandra, Licorice root, Astragalus membranaceus, Notoginseng, and Cinnamon, was subjected to a ligand-based virtual screening using \u003cem\u003eLigandScout 3.1 software\u003c/em\u003e [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The compounds were retrieved from the TCM database [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and filtered based on the following criteria: molecular weight (MW)\u0026thinsp;\u0026le;\u0026thinsp;500 Da, LogP\u0026thinsp;\u0026le;\u0026thinsp;5, hydrogen bond donors (HBD)\u0026thinsp;\u0026le;\u0026thinsp;5, hydrogen bond acceptors (HBA)\u0026thinsp;\u0026le;\u0026thinsp;10, oral bioavailability (OB)\u0026thinsp;\u0026le;\u0026thinsp;10, Caco-2 permeability greater than \u0026minus;\u0026thinsp;5.15 cm/s, blood-brain barrier (BBB) permeability greater than 0.3, drug-likeness (DL)\u0026thinsp;\u0026ge;\u0026thinsp;0.18, fractional polar surface area (FASA) above 30%, and a half-life (HL) of more than 3 hours. The pharmacophore model was created using the 3D structures of Katerzia, Norliqva, Isoxsuprine, Lisinopril, Perindopril, Atorvastatin, Xarelto, Brilinta, and Amlodipine medications approved by the FDA for coronary artery disease (CAD). The espresso method was used to develop a ligand-based pharmacophore, and LigandScout's default parameters were used to ensure that the pharmacophore hypothesis was compatible. Two common benchmark criteria were used to determine which hits were the best. Hits were initially arranged according to pharmacophore fit scores, with preference given to those that were above a predetermined cutoff, frequently 0.7\u0026ndash;1.0 or near 1. Second, pharmacophore feature matching was used to classify compounds as good hits if they demonstrated at least 70\u0026ndash;80% alignment with the pharmacophore features, such as hydrogen bond acceptors (HBAs), aromatic rings (ARs), and hydrophobic zones (Hs).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eReceptor Ligand Preparation\u003c/h3\u003e\n\u003cp\u003eThe three-dimensional (3D) structure of AT1R (PDB ID: 4ZUD) were retreived from the Protein Data Bank (PDB) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The \u003cem\u003eUCSF Chimera v1.17.1 software\u003c/em\u003e [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], was used to remove water molecules, crystallographic cofactors, and additional chains from the retrieved structure. After that, hydrogen atoms were incorporated into the protein structures, and their stability was maximized by minimizing energy. The PDB format was used to store the processed structure for later examination. The binding pocket of targeted protein was estimated by using \u003cem\u003eBIOVIA Discovery Studio Software\u003c/em\u003e [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] for possible docking sites. \u003cem\u003ePyRx software 0.8\u003c/em\u003e [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] was used to prepare the top hit molecules in order to ensure their suitability for molecular docking studies. All ligands were first subjected to energy minimization in order to maximize their structural conformations. The reduced ligands were then transformed into the PDBQT format, which is the file type needed for docking.\u003c/p\u003e\n\u003ch3\u003eMolecular Docking Analysis\u003c/h3\u003e\n\u003cp\u003eTo analyze the top-ranked compounds' binding affinities with the target proteins, molecular docking was carried out using \u003cem\u003ePyRx software 0.8\u003c/em\u003e. After docking, the binding modes were analyzed and interpreted using \u003cem\u003eBIOVIA Discovery Studio\u003c/em\u003e and \u003cem\u003eChimera X software\u003c/em\u003e to investigate receptor-ligand interactions. Compounds with high binding affinities (-7.0 to -10.0 kcal/mol) were chosen for additional examination. Key chemical interactions that support the stability and specificity of ligand binding, such as hydrogen bonding, hydrophobic contacts, and π-π stacking, were identified using this post-docking analysis.\u003c/p\u003e\n\u003ch3\u003eADMET and Physiochemical Analysis\u003c/h3\u003e\n\u003cp\u003eThe ADME prediction was carried out by using the SWISS ADME [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] and ADMETLab [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] databases, which are openly available to assess the pharmacokinetics and drug-likeness of active compounds. Many properties were investigated, including the number of rotatable bonds, the molecular weight, and the donors and acceptors of hydrogen bonds. The toxicity and safety evaluation of chemicals were also conducted using the ProTox-II [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] web-based server. ProTox-II uses fragment-based methods, pharmacophore modeling, machine-learning algorithms, and molecular similarity analysis. The server generated 33 models with confidence scores that depicted the potential toxicity profile of the medication after receiving a 2D chemical structure as input.\u003c/p\u003e\n\u003ch3\u003eDFT Calculations\u003c/h3\u003e\n\u003cp\u003eThe DFT/B3LYP method with multiple basis sets in the Gaussian 09 software was used to fully optimize the geometries of the chosen drug candidates [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The Gaussian output files were evaluated using the GaussView molecular visualization application [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Using HOMO\u0026ndash;LUMO energy values based on the numbering scheme assigned to the compounds, DFT-derived quantum chemical parameters were calculated in the gas phase. Additionally, the excitation energy, oscillator strength, and effective charges of the coordinating groups of the optimized structures were determined.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eMolecular Dynamic Simulation\u003c/h2\u003e\u003cp\u003eThe stability of the docked complexes was studied through the molecular dynamics (MD) Simulation analysis [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Top compounds identified through the molecular docking and ADME analysis were subjected to the MD analysis. The Desmond Module of Schrodinger explicit solvent MD package along with a fixed OPLS 2005 force field was used for the MD simulation [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The Protein Preparation Wizard was used to create a protein-ligand combination with a predetermined SPC (Simple Point Charge) water model and an orthorhombic box shape (10 \u0026Aring; \u0026times; 10 \u0026Aring; \u0026times; 10 \u0026Aring;). To neutralize it, a NaCL solution was introduced to the system. The isosmotic condition of the simulation box remains intact through the addition of 0.15 m NaCl. A specified equilibrium was achieved before simulation's production run. Than the modal system was submitted for simulation at 200ns steps with the OPLS_2005 force field. A temperature of 300 K was maintained using the Nos\u0026eacute;-Hoover chain thermostat algorithm, while a pressure of 1.01325 bar with isotropic coupling was maintained using the Martyna-Tobias-Klein barostat method. All other parameters were maintained at their default values, with a Coulombic cutoff of 0.9 nm [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Finally, the results of the MD simulation were examined for solvent accessible surface area (SASA), radius of gyration (Rg), root mean square deviation (RMSD), and root mean square fluctuation (RMSF) etc at 200ns using the Simulation Interaction Diagram (SID) tool.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eMMGBSA binding free energy analysis\u003c/h3\u003e\n\u003cp\u003eThe MM-GBSA method and the default settings of the Prime MM-GBSA module in Schr\u0026ouml;dinger software were used to calculate the binding free energies (ΔGBind) of the selected protein\u0026ndash;ligand complexes. The analysis was conducted using the Glide pose viewer file, and the relative binding affinity of ligands to the receptor which was expressed in kcal/mol was calculated using MM-GBSA. Larger negative binding energies, which are estimates of the free binding energies, indicate a stronger binding affinity [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003ePharmacophore Modelling\u003c/h2\u003e\u003cp\u003eTo identify potential treatment options, a pharmacophore model was developed using the three-dimensional (3D) structures of FDA-approved drugs commonly used to treat heart disease. A pharmacophore describes a molecule's primary chemical properties that are essential to its biological activity. Three essential structural elements for successful ligand binding were identified by the model in this study: an aromatic ring, which is necessary to stabilize interactions with the target protein, as well as characteristics that have electron donor and acceptor characteristics (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The hits selection was refined using Pharmacophore Fit Score and Pharmacophore Feature Matching, two important evaluation techniques. Each compound's alignment with the pharmacophore model was gauged by its Fit Score; higher scores suggested a higher chance of binding successfully. Based on their agreement with the model, 149 of the 587 compounds that were examined were determined to be possible hits.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eMolecular Docking Analysis\u003c/h2\u003e\u003cp\u003eOut of 149 pharmacophore-screened candidates, the top 17 compounds with the angiotensin II type 1 receptor (AT1R) have docking scores summarized in (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) due to their high binding affinities. The strength of anticipated interactions is indicated by binding energy values, which are represented in kcal/mol. Stronger binding is indicated by higher negative values. With a value of -10.6 kcal/mol, MOL004805 showed the highest binding by far, followed by MOL004810 (-9.5 kcal/mol), MOL004806, and MOL002776 (both \u0026minus;\u0026thinsp;9.4 kcal/mol). Even though a number of compounds showed higher docking scores, MOL002140, also known as perlolyrine, was selected as the last lead contender for additional in-depth examination because of its docking score of -8.2 kcal/mol. Based on a combination of binding affinity, excellent pharmacophore alignment, anticipated pharmacokinetic features, and potential for drug-likeness, Perlolyrine was chosen as a promising compound for further investigation in AT1R targeting.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBinding affinities (kcal/mol) of the top 17 pharmacophore-screened compounds docked with AT1R.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCompounds\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAT1R\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMOL000098\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-8.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMOL000354\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-8.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMOL000379\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMOL000398\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-7.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMOL000433\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMOL000436\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMOL000500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-8.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMOL001789\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-7.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMOL002135\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-9.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMOL002140\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-8.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMOL002311\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-9.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMOL002776\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-9.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMOL004805\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-10.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMOL004806\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-9.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMOL004808\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-8.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMOL004810\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-9.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMOL004811\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-8.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ePerlolyrine interacts with several amino acid residues by utilizing a mix of water-mediated contacts, hydrophobic interactions, and hydrogen bonding. Remarkably, TRP84 and TYR87 interact with Perlolyrine's aromatic core to promote π-π stacking and hydrophobic stability. As a donor of hydrogen bonds, perlolyrine's hydroxyl (-OH) group interacts directly with ASP281, a crucial residue that may be essential for either receptor activation or inhibition. Water bridges containing residues such as ARG167, TYR35, and GLY22 facilitate additional hydrogen bonding and polar interactions, improving ligand anchoring inside the active site (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to the interaction profile, perlolyrine engages residues frequently engaged in ligand recognition and signaling, forming a deep and stable binding within the receptor's ligand-binding cavity.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eToxicity and Physicochemical Properties\u003c/h2\u003e\u003cp\u003eThe ADMET profile of Perlolyrine (MOL002140) lends credence to its potential as an antihypertensive drug. Good oral bioavailability is essential for chronic management medications like antihypertensives, and it is indicated by its favorable physicochemical features, including a moderate molecular weight (266.110 g/mol), appropriate lipophilicity (logP\u0026thinsp;=\u0026thinsp;2.384), and compliance with Lipinski, Pfizer, and Veber criteria (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Perlolyrine's blood-brain barrier (BBB) crossing capability might also help regulate key elements of blood pressure management if necessary.\u003c/p\u003e\u003cp\u003eIts therapeutic importance is further supported by its interaction with the angiotensin II type 1 receptor (AT1R), a crucial target in blood pressure regulation. Because it is not carcinogenic, mutagenic, cardiotoxic, or cytotoxic, perlolyrine is especially useful for long-term use in the treatment of chronic conditions like hypertension. However, given that hypertension patients frequently need polypharmacy, its function as a substrate and inhibitor of several CYP enzymes particularly CYP3A4 and CYP2C9 highlights the significance of taking possible drug-drug interactions into account.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eADMET profile of Perlolyrine showing its favorable pharmacokinetic, metabolic, and safety properties for use as an antihypertensive agent.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMOL002140\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMolecular Weight (MW)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e266.110 g/mol\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTPSA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e57.430 \u0026Aring;\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003elogS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-3.970\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003elogP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.384\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLipinski Rule\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePfizer Rule\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVeber\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCaco-2 Permeability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-4.858\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePgp-inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePgp-substrate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBBB Penetration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCYP1A2 inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCYP1A2 substrate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCYP2C19 inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCYP2C19 substrate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCYP2C9 inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCYP2C9 substrate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCYP2D6 inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCYP2D6 substrate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCYP3A4 inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCYP3A4 substrate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEye Corrosion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGenotoxic Carcinogenicity Rule\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHBA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHBD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMolecular refractivity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e83.28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of rotable bonds\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCarcinogenicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMutagenicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCytotoxicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCardiotoxicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn respect to recognized drug-likeness boundaries, the radar plot displays Perlolyrine's physicochemical and pharmacokinetic profile. The blue line displays the actual values of Perlolyrine's characteristics, the pink area displays the lower limitations, and the orange shaded area reflects the higher permitted limits. The majority of measures, including molecular weight, lipophilicity, solubility, and hydrogen bonding characteristics, show that perlolyrine falls well within the permitted range, demonstrating strong adherence to important drug-likeness requirements. Small variations in a few regions do not affect its overall drug-like capabilities and are still within a reasonable range.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eDensity functional theory (DFT) calculations\u003c/h2\u003e\u003cp\u003eAccording to Density Functional Theory (DFT), Perlolyrine's (MOL002140) electronic properties and chemical reactivity were assessed. Important reactive areas of the molecule are revealed by the distribution of the frontier molecular orbitals, HOMO (Highest Occupied Molecular Orbital) and LUMO (Lowest Unoccupied Molecular Orbital), as seen in (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). While the LUMO is delocalized throughout the molecule, emphasizing electron-accepting locations pertinent to its interaction with biological targets, the HOMO is primarily clustered around the indole ring, suggesting possible electron-donating sites. The calculated energy values of -0.85 eV for LUMO and \u0026minus;\u0026thinsp;4.80 eV for HOMO provide an energy gap of 3.95 eV, indicating that perlolyrine has favorable electronic stability and moderate reactivity, which are in good agreement with the characteristics of a drug-like molecule.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eA number of quantum descriptors were obtained. The softness (S) is 0.25 and the chemical hardness (η) is 1.97, indicating a balanced reactivity appropriate for molecular interactions. The molecule's propensity to attract electrons is shown by its electronegativity (χ) of 2.82, while its ability to absorb electrons upon binding is reflected by its electrophilicity index (ω) of 2.02. With a maximum electronic charge transfer (ΔNmax) of 1.43 and a chemical potential (Pi) of -2.82, perlolyrine is a good candidate for antihypertensive medication development due to its reasonable electronic stability and binding ability (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eQuantum chemical parameters derived from DFT calculations for Perlolyrine, indicating its electronic stability, reactivity, and interaction potential.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"11\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCompound\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHOMO\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLUMO\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEg\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eꭓ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eɳ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eσ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003ePi\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eω\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eΔN\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMOL02140\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-4.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-2.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e2.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAccording to Density Functional Theory (DFT) calculations, the noncovalent interaction profile of perlolyrine (MOL002140) is shown in detail in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The types and intensities of intramolecular and intermolecular interactions are quantitatively mapped in (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), which is an RDG (Reduced Density Gradient) against sign(λ₂)ρ plot. The dense clustering of points in the green zone close to sign(λ₂)ρ\u0026thinsp;=\u0026thinsp;0, which corresponds to low RDG values (~\u0026thinsp;0.5 to 1.5), is a noticeable characteristic in this plot. This clearly shows that weak van der Waals interactions predominate across the molecule surface. Furthermore, the sharp blue spikes on the left side (sign(λ₂)ρ\u0026thinsp;\u0026lt;\u0026thinsp;0, particularly close to -0.035) are suggestive of attractive interactions like hydrogen bonds or π\u0026ndash;π stacking, indicating that certain atoms in the structure are engaged in directional, potentially biologically significant stabilizing interactions. On the other hand, red dots on the right (sign(λ₂)ρ\u0026thinsp;\u0026gt;\u0026thinsp;0.02) indicate locations where the molecule undergoes internal strain or spatial crowding, and they also reflect steric repulsion or close interactions between electron-rich regions.\u003c/p\u003e\u003cp\u003eA 3D NCI (Non-Covalent Interaction) isosurface projected onto the Perlolyrine molecular structure allows the spatial visualization of these interactions in (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). The molecule exhibits broad green isosurfaces on both side chains and aromatic rings, indicating that dispersion (van der Waals) interactions are common and probably play a major role in the molecule's binding potential and conformational stability. Notably, the presence of hydrogen bonding donors and acceptors is confirmed by the direct correlation between the attractive contacts shown in the RDG plot and localized blue patches close to the nitrogen and oxygen atoms, such as those in the indole ring and side-chain substituents. The bioactive conformation of the molecule may be influenced by a small red patch in the central aromatic core, which indicates an area of steric repulsion that is probably caused by ring-ring crowding or torsional strain. These findings draw attention to the molecule's structural flexibility and reactivity, two crucial properties that support its potential as a helpful ligand in drug development, particularly with regard to antihypertensive activity.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eMolecular Dynamic Simulation\u003c/h2\u003e\u003cp\u003eThe molecular dynamics (MD) simulation results shown in (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) give a complete examination of Perlolyrine's structural stability, flexibility, and binding interactions with the angiotensin II type 1 receptor (AT1R), a critical target in hypertension treatment. Root Mean Square Deviation (RMSD) of the AT1R protein backbone (in blue) and the ligand (Perlolyrine, in red) over a 200 ns trajectory is displayed in (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Following an initial equilibration phase, the protein RMSD stabilizes at approximately 3.5 \u0026Aring;, suggesting a reasonably stable protein-ligand combination. Throughout the simulation, the ligand RMSD stays below 2.0 \u0026Aring;, indicating that perlolyrine binds to the AT1R binding site with strength and stability.\u003c/p\u003e\u003cp\u003eThe AT1R residues' RMSF (Root Mean Square Fluctuation), which gauges per-residue flexibility throughout the simulation, is shown in (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). As is common for membrane proteins like AT1R, the majority of residues exhibit low to moderate variations (\u0026lt;\u0026thinsp;2 \u0026Aring;), with more flexibility seen at the terminal and loop regions. The idea of a well-anchored ligand is supported by the stable core areas that are engaged in ligand binding showing little fluctuation.\u003c/p\u003e\u003cp\u003eThe interaction proportion of particular AT1R residues with perlolyrine is shown in (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC), which shows how frequently each residue makes contact throughout the simulation. Residues like PHE115, TRP84, ARG167, and MET284 exhibit large interaction fractions, highlighting their crucial involvement in ligand stability, especially through hydrogen bonding and hydrophobic interactions (shown by the color stacking). Interestingly, transmembrane domain residues play a major role, matching the known binding site design of GPCRs.\u003c/p\u003e\u003cp\u003eThe quantity and regularity of ligand-protein connections are shown in the time-resolved interaction contact map shown in (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). The durability of the Perlolyrine\u0026ndash;AT1R complex is further supported by the top graph, which displays the overall number of interactions over the course of the simulation and stays comparatively constant. Persistent binding hotspots that are crucial for ligand recognition and receptor modulation are highlighted by the bottom heatmap, which shows ongoing interactions with important residues like PHE115, TYR87, ARG167, and MET284.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAdditionally, there is very little variation in the radius of gyration (Rg) at 3.9 \u0026Aring;, suggesting that the protein's overall compactness is unaffected and that no substantial unfolding takes place during the simulation. The intra-molecular hydrogen bonds (intraHB) show intermittent formation, which is typical for receptor-ligand systems and reflects dynamic reorganization of hydrogen bonding interactions that stabilize the binding pocket and surrounding residues. The polar surface area (PSA), solvent-accessible surface area (SASA), and molecular surface area (MolSA) all exhibit steady trends devoid of sharp oscillations, suggesting that the solvation characteristics of the ligand and the protein's solvent exposure are constant over time (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). Significantly, PSA varies at about 90 \u0026Aring;\u0026sup2;, indicating that the complex's polar portions are still accessible and may help with interactions with nearby ions or water molecules, which is essential for bioactivity in physiological settings.\u003c/p\u003e\u003cp\u003eBy examining the protein's secondary structural elements (%SSE) during the course of the simulation shown in (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). With α-helices and β-strands (colored cyan and red, respectively) being well-preserved, the plot shows that the overall percentage of secondary structure stays impressively consistent. This structural preservation demonstrates that the binding of perlolyrine does not cause AT1R to undergo substantial conformational instability, which is essential for maintaining the receptor's functional integrity. These findings collectively provide more evidence that perlolyrine and AT1R form a stable, compact complex that preserves the structural characteristics and solvent dynamics of the receptor. Its prospective use as a stable and selective antihypertensive drug that targets AT1R depends on these characteristics.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eDuring the simulation, the polar plots and accompanying histograms of angular distributions shown in (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG) most likely depict side chain torsion angles or the vector orientations of important residues or the ligand itself. A bimodal angular distribution peaking close to \u0026plusmn;\u0026thinsp;180\u0026deg; is seen in the blue polar plot and histogram, suggesting a toggling or conformational flipping between two dominant states. This implies that certain atoms or vectors in the Perlolyrine\u0026ndash;AT1R complex take on two different orientations during the simulation, which could be a reflection of conformational changes in the binding pocket or rotational freedom.\u003c/p\u003e\u003cp\u003eThe green histogram indicates considerable flexibility and conformational variability, possibly in a loop region or solvent-exposed part of the receptor, as it shows a wider and more irregular distribution along the full angular range. A highly stable dihedral or vector alignment is indicated by the red angular distribution's narrowness and high centralization around 0\u0026deg;, which most likely reflects a limited interaction inside the binding site that doesn't change over time. Together, these graphs show that the binding interface is both flexible and stable, with certain parts of the complex undergoing dynamic reorientation while others retain stiff, stable structures.\u003c/p\u003e\u003cp\u003eThe key motions in the conformational space are captured in the 3D Principal Component Analysis (PCA) plot of the protein-ligand complex over the simulation trajectory, which is displayed in (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eH). The variation explained by each component is confirmed by the diagonal plots (PC1 vs. PC1, etc.). The complex traverses several conformational states instead of staying in a single dominant conformation, as shown by the off-diagonal projections, which show clear clustering patterns, especially in PC1 vs. PC2 and PC2 vs. PC3 plots. The dispersion between PC1 and PC2 indicates that the AT1R structure undergoes significant global motions as a result of perlolyrine binding.\u003c/p\u003e\u003cp\u003eThe presence of several dense clusters throughout time suggests transitions between metastable states, and the color gradients (from light to dark orange/brown) most likely indicate the simulation duration. This result implies that AT1R dynamics are modulated by perlolyrine binding in a manner that may be functionally important, influencing either receptor inhibition or activation.\u003c/p\u003e\u003cp\u003eTogether, these findings demonstrate that Perlolyrine interacts with AT1R in a variety of stiff and flexible ways, with both structural stability and dynamic sampling of alternate conformations confirmed by angular and PCA data. Perlolyrine's significance as a possible small-molecule modulator may be supported by these dynamics, which may be essential to comprehending how it affects AT1R activity in the setting of hypertension.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eMolecular Mechanics Generalized Born Surface Area\u003c/h2\u003e\u003cp\u003eThe Molecular Mechanics Generalized Born Surface Area (MM-GBSA) indicates a highly favorable and stable association between the ligand and the protein. The total binding free energy (ΔG Bind) is -162.52 kcal/mol, which is significantly negative. With a value of -155.92 kcal/mol, the van der Waals interactions (ΔG Bind vdW) provide a significant contribution to the energetic contributions, emphasizing the significance of close-contact forces and hydrophobic interactions in ligand binding. Additionally, electrostatic (Coulomb) interactions play a positive role; ΔG Bind Coulomb = -48.89 kcal/mol indicates that Perlolyrine and charged residues in the AT1R binding pocket have a strong electrostatic complementarity. Conversely, the solvation energy (ΔG Bind Solv GB) shows a high positive value of +\u0026thinsp;116.11 kcal/mol, which represents the energetic cost of desolvating the receptor and the ligand during complex formation.\u003c/p\u003e\u003cp\u003eThe electrostatic and van der Waals contributions are so high that the overall binding is still very advantageous in spite of this penalty. The tiny positive contributions of 6.17 kcal/mol and 1 kcal/mol, respectively, from the covalent interaction term (ΔG Bind Covalent) and another unidentified component (labeled \"1\") suggest that they play insignificant or marginally destabilizing roles in the total binding energetics (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eHypertension is a complex cardiovascular condition that contributes significantly to morbidity and mortality worldwide. The renin-angiotensin system (RAS) is essential to its pathogenesis, especially the angiotensin II type 1 receptor (AT1R), a G protein-coupled receptor (GPCR) that mediates the pro-inflammatory, pro-fibrotic, and vasoconstrictive effects of angiotensin II [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Chronic AT1R overactivation worsens hypertension pathophysiology by increasing systemic vascular resistance, aldosterone production, and progressive cardiac and renal remodeling [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. As a result, AT1R is now a well-established target in antihypertensive medication, with a number of ARBs (angiotensin receptor blockers), including valsartan and losartan, effectively lowering cardiovascular events by selectively inhibiting AT1R [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA β-carboline alkaloid called perlolyrine is identified in our work as a new AT1R regulator with encouraging antihypertensive potential. Perlolyrine has demonstrated pharmacological actions related to the pathophysiology of hypertension, despite the fact that it has not yet been extensively investigated in the context of cardiovascular diseases. Notably, it has been observed that β-carbolines, such as Perlolyrine, have neuroprotective, anti-inflammatory, and antioxidant characteristics that mechanistically interact with AT1R signaling pathways [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Specifically, oxidative stress and inflammation, which are downstream effects of AT1R activation, are necessary for the vascular damage brought on by hypertension [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The finding that perlolyrine is a stable AT1R binder adds to its previously documented bioactivities and creates new avenues for research into its possible repurposing as a cardiovascular treatment.\u003c/p\u003e\u003cp\u003eThe study's molecular docking analyses reveal that perlolyrine interacts closely with the AT1R transmembrane pocket through π\u0026ndash;π stacking, hydrogen bonding, and polar interactions involving residues such as TRP84, TYR87, ARG167, and ASP281. Studies on AT1R-7 receptor activation and ligand recognition frequently include these acids [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Despite not having the lowest docking score of any of the compounds evaluated, perlolyrine was a strong candidate for additional research due to its appealing pharmacokinetic profile, chemical stability, and binding energy balance.\u003c/p\u003e\u003cp\u003eBecause of its ADMET profile, perlolyrine is a more practical choice for long-term antihypertensive treatment. Although more research is required to fully understand its dual role, its predicted ability to penetrate the blood-brain barrier (BBB) may be significant in regulating central sympathetic outflow, which is known to contribute to hypertension. It lacks signs of mutagenicity and carcinogenicity, has adequate lipophilicity and solubility, and satisfies important drug-likeness requirements [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Furthermore, the molecule's role as a moderate CYP3A4 and CYP2C9 substrate and inhibitor highlights the importance of researching drug-drug interactions, particularly in hypertensive patients who frequently experience polypharmacy [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAccording to our DFT-based molecular orbital and noncovalent interaction (NCI) study on chemical reactivity, perlolyrine has a favorable HOMO-LUMO gap (3.95 eV) and participates in significant hydrogen bonding and van der Waals interactions. In GPCR\u0026ndash;ligand complexes, these electrical characteristics have been connected to improved binding stability and affinity [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Perlolyrine's structure includes specific nucleophilic and electrophilic regions that aid in its dynamic and specific binding to AT1R target sites. MD modeling provided additional confirmation of perlolyrine's long-term structural compatibility with AT1R. The complex exhibited persistent protein-ligand interactions, a tight radius of gyration, and a constant root mean square deviation (RMSD) over 200 ns. These results are in line with earlier simulation-based studies that demonstrated the importance of contact persistence and conformational stability in potent AT1R antagonists [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Since PCA found metastable states, it is possible that perlolyrine keeps AT1R in an inactive conformation. This is consistent with the expected antagonistic effect seen in existing ARBs [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Furthermore, secondary structure conservation and stable surface area characteristics (SASA, PSA, and MolSA) show that no significant conformational changes have taken place and that the physiological architecture of the receptor is maintained during modulation.\u003c/p\u003e\u003cp\u003eThe MM-GBSA analysis showed that perlolyrine bound to the AT1R receptor with a total binding free energy (ΔG Bind) of -162.52 kcal/mol, which is a strong and energetically advantageous binding. Significant van der Waals interactions (\u0026ndash;155.92 kcal/mol) and Coulombic contributions (\u0026ndash;48.89 kcal/mol) are the main drivers of this stability, surpassing the desolvation penalty (ΔG Bind Solv GB: +116.11 kcal/mol). These findings support the idea that ligand stability and affinity in the AT1R binding pocket are mostly dependent on hydrophobic and electrostatic forces.The binding appears to be non-covalent and selective based on the small contribution from covalent interactions (+\u0026thinsp;6.17 kcal/mol) and other factors. These results validate that perlolyrine can stably occupy and regulate the AT1R receptor, supporting the molecular dynamics findings.\u003c/p\u003e\u003cp\u003eInterestingly, because perlolyrine is a natural β-carboline, it belongs to a class of chemicals that have been historically associated with neuroactivity and MAO inhibition [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Although this increases the possibility of off-target effects, it also offers chances for dual-purpose cardiovascular\u0026ndash;neurological uses where central and peripheral pathways meet, like in hypertensive encephalopathy or stress-induced hypertension [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. This study links perlolyrine's established bioactivities with new cardiovascular uses in addition to presenting it as a viable AT1R antagonist. It bolsters the idea that naturally occurring alkaloids can function as potent GPCR target modulators, providing multi-targeted treatment approaches for complicated chronic conditions like hypertension.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eA stable, bioactive, and pharmacologically promising AT1R modulator, perlolyrine has been discovered using extensive pharmacophore modeling, molecular docking, ADMET screening, DFT computations, and MD simulation. Its function as an antagonist with possible antihypertensive effects is supported by its structural flexibility and capacity to consistently create contacts with important AT1R residues. To support its therapeutic potential for the treatment of hypertension, these computational results call for additional experimental validation, such as in vitro binding tests and in vivo efficacy investigations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflict of Interest\u003c/h2\u003e\u003cp\u003eAuthors declare no conflict of interest.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eStatement on the Use of Artificial Intelligence\u003c/h2\u003e\u003cp\u003eAI-based tools (Grammarly and QuillBot) were used solely for language editing, grammar correction, and rephrasing to improve clarity. No AI tools were used for data analysis, figure generation, or interpretation of results. The authors take full responsibility for the content of this manuscript.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eNote:\u003c/p\u003e\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthors Contribution\u003c/h2\u003e\u003cp\u003e\u003cb\u003eIqra Azhar\u003c/b\u003e: Data collection, Formal analysis, Review, and writing of the initial draft. \u003cb\u003eImran Ali Khan\u003c/b\u003e: Formal analysis, Review, and writing of the initial draft. \u003cb\u003eSaleh M. Bufarwa\u003c/b\u003e: Material and Methods, and Review and writing of the initial draft. \u003cb\u003eMustapha Belaidi\u003c/b\u003e: Formal analysis. \u003cb\u003eSadia Zahid\u003c/b\u003e: Conceptualization, investigation, and supervision. \u003cb\u003eBushra Shakoor\u003c/b\u003e: Formal Analysis. \u003cb\u003eAneeqa Batool\u003c/b\u003e: Review and writing of the final version of the manuscript. \u003cb\u003eHuma Fatima\u003c/b\u003e: Materials and Methods. \u003cb\u003eAyesha Farooq\u003c/b\u003e: Review and writing of the final version of the manuscript. \u003cb\u003eAqsa Nazir\u003c/b\u003e: Review and writing of the final version of the manuscript. All authors reviewed the final version of the manuscript and approved it for publication.\u003c/p\u003e\u003ch2\u003eAcknowledgment\u003c/h2\u003e\u003cp\u003eThe authors would like to acknowledge the support and resources provided by the Department of Biotechnology, University of Okara.\u003c/p\u003e\u003ch2\u003eData Availability Statement\u003c/h2\u003e\u003cp\u003eAll computational data generated or analyzed during this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGiles TD et al (2005) Expanding the Definition and Classification of Hypertension. J Clin Hypertens 7(9):505\u0026ndash;512\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGiles TD et al (2009) Definition and classification of hypertension: an update. 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J Appl Physiol (1985), 109(6): p. 1996-8; discussion 2016.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Okara","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"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":"Perlolyrine, AT1R, hypertension, molecular dynamics, DFT, pharmacophore modeling, in silico drug discovery","lastPublishedDoi":"10.21203/rs.3.rs-7499142/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7499142/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe angiotensin II type 1 receptor (AT1R) is a key target for antihypertensive drug development. This study uses an integrative computational approach to identify perlolyrine (MOL002140) as a promising AT1R modulator. A comprehensive in silico workflow was used, which included pharmacophore modeling, molecular docking, ADMET profiling, DFT calculations, and molecular dynamics (MD) simulations. Strong binding affinity to AT1R (\u0026minus;\u0026thinsp;8.2 kcal/mol) was demonstrated by perlolyrine, which also formed stable interactions with important residues like TRP84, TYR87, ASP281, and ARG167. ADMET predictions showed a good safety profile and favorable pharmacokinetic properties. The electronic stability of the compound with a HOMO\u0026ndash;LUMO energy gap of 3.95 eV was confirmed by DFT analysis. The AT1R\u0026ndash;Perlolyrine complex was found to be stable, compact, and exhibit few conformational fluctuations in long-timescale MD simulations (200 ns). Consistent receptor\u0026ndash;ligand dynamics were further shown by principal component analysis (PCA) and angular distribution studies, confirming the compound's potential as a potent AT1R antagonist. All of these results point to perlolyrine as a viable option for additional research and development in the treatment of hypertension.\u003c/p\u003e","manuscriptTitle":"Computational Identification and Evaluation of Perlolyrine as a Promising AT1R Antagonist for Hypertension Therapy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-03 07:23:51","doi":"10.21203/rs.3.rs-7499142/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":"aedd3c61-746f-4e0a-8e71-f8fc676a0d78","owner":[],"postedDate":"September 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":53953476,"name":"Computational Biology"},{"id":53953477,"name":"Bioinformatics"}],"tags":[],"updatedAt":"2025-09-03T07:23:51+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-03 07:23:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7499142","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7499142","identity":"rs-7499142","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}