Rational Design and Molecular Docking Studies of Novel Dual-Thionamide Antithyroid Agent with Enhanced Thyroid Peroxidase Inhibition Through Bidentate Heme Coordination

Rational Design and Molecular Docking Studies of Novel Dual-Thionamide Antithyroid Agent with Enhanced Thyroid Peroxidase Inhibition Through Bidentate Heme Coordination | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report Rational Design and Molecular Docking Studies of Novel Dual-Thionamide Antithyroid Agent with Enhanced Thyroid Peroxidase Inhibition Through Bidentate Heme Coordination Luis Jesuino de Oliveira Andrade, Gabriela Correia Matos de Oliveira, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7830056/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 Background: Hyperthyroidism management remains constrained by limited pharmacological innovation, with thionamide therapy exhibiting suboptimal remission rates and significant adverse effects. Thyroid peroxidase (TPO) inhibition through conventional monodentate heme coordination demonstrates transient efficacy, necessitating novel therapeutic approaches. Objective: To rationally design and computationally validate a dual-thionamide antithyroid agent with enhanced TPO inhibitory potency through bidentate heme coordination. Methods: Comprehensive computational workflow integrating de novo scaffold generation, quantum mechanical optimization (B3LYP/6-31G(d,p)), molecular docking (AutoDock Vina), 200 ns molecular dynamics simulations (GROMACS/AMBER99SB-ILDN), MM-PBSA binding free energy calculations, and structure-activity relationship analysis across 15 structural analogs was employed to design and characterize a novel antithyroid molecule designated Thiazolthiouracil . Results: Thiazolthiouracil exhibited superior binding affinity (-9.6 kcal/mol) compared to methimazole (-7.3 kcal/mol), propylthiouracil (-6.8 kcal/mol), and carbimazole (-7.5 kcal/mol), representing 32-41% enhancement (p<0.001). Bidentate Fe-S coordination geometry (Fe-S₁: 2.32 Å, Fe-S₂: 2.38 Å, angle: 98.7°) demonstrated 97.2% occupancy throughout MD simulations versus 68-71% for conventional agents. MM-PBSA calculations revealed ΔG_binding = -45.8±3.2 kcal/mol, 34-54% superior to clinical comparators. The mechanism involves dual-site heme occupation inducing catalytically incompetent low-spin Fe(III) configuration, extensive hydrogen bonding network stabilization, and 93.5% active site occlusion (SASA reduction: 12.3→0.8 Ų). Conclusion: Thiazolthiouracil represents a novel antithyroid molecule computationally validated with predicted superior and sustained TPO inhibition through persistent bidentate coordination, warranting experimental validation and clinical development. Bioinformatics Endocrinology & Metabolism Thyroid peroxidase inhibition Rational drug design Computational pharmacology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Hyperthyroidism represents a significant endocrine disorder characterized by excessive synthesis and secretion of thyroid hormones. 1 The pathophysiology underlying this condition centers on dysregulated thyroid hormone biosynthesis, wherein thyroid peroxidase (TPO) catalyzes the critical oxidation of iodide ions and their subsequent incorporation into tyrosine residues on thyroglobulin, ultimately generating triiodothyronine and thyroxine. 2 The most common etiologies include Graves' disease, where thyroid-stimulating immunoglobulins activate TSH receptors triggering autonomous hormone production, and toxic multinodular goiter, which results from somatic mutations in the TSH receptor leading to constitutive activation of the cAMP signaling pathway. 3 Beyond the classical symptoms of weight loss, palpitations, and heat intolerance, untreated hyperthyroidism carries substantial morbidity, including atrial fibrillation, osteoporotic fractures, and increased cardiovascular mortality, with particularly severe manifestations in thyroid storm. 4 Current therapeutic strategies for hyperthyroidism encompass three definitive approaches: thionamide pharmacotherapy, radioactive iodine (RAI) ablation, and surgical thyroidectomy, each carrying distinct risk-benefit profiles. 1 Antithyroid drugs function as competitive inhibitors of thyroid peroxidase, blocking hormone synthesis at the organification and coupling steps, though remission rates following discontinuation remain disappointingly modest at 20–30% in North American cohorts. 5 RAI therapy, while effective, is contraindicated during pregnancy and lactation, carries risks of worsening Graves' orbitopathy in patients with moderate-to-severe eye disease, and frequently results in permanent hypothyroidism requiring lifelong levothyroxine replacement. 6 Thyroidectomy offers definitive cure with near-zero recurrence rates but entails surgical risks including permanent hypoparathyroidism, recurrent laryngeal nerve injury, and perioperative complications, making it less desirable for patients with significant comorbidities. 7 The transient nature of thionamide efficacy, combined with these substantial limitations across all therapeutic modalities, creates a compelling need for safer, more effective pharmacological alternatives. For over eight decades, thionamides have remained the mainstay pharmacotherapy for hyperthyroidism, yet no structurally novel agents have been emerged since the introduction of methimazole and propylthiouracil in the 1940s. Despite significant advances in TPO enzymology and thionamide–heme interactions, therapeutic innovation markedly lagged behind that of other endocrine fields. Modern bioinformatics-driven approaches now enable the rational design of novel TPO-inhibiting drug scaffolds. This proof-of-concept computational study aims to report the rational design, in silico validation, and structural characterization of a novel antithyroid scaffold. While computational predictions are validated against experimental data for established thionamides, the designed molecule requires chemical synthesis and biochemical characterization to confirm predicted TPO inhibitory activity. METHOD This investigation employed a comprehensive computational drug design workflow integrating de novo molecular scaffold generation, structure-based virtual screening, molecular docking, and molecular dynamics simulations to rationally design and evaluate novel dual-thionamide antithyroid agents targeting TPO with enhanced bidentate heme coordination capabilities. Rational Drug Design and Scaffold Generation The molecular architecture of candidate compounds was systematically designed using ChemDraw Professional 21.0 (PerkinElmer, Waltham, MA, USA) for initial two-dimensional structure generation, followed by three-dimensional conformer optimization in Avogadro 1.2.0 with the Universal Force Field algorithm with energy minimization convergence criteria set at 10 -4 kcal/mol. The design strategy incorporated structural insights from crystallographic studies of TPO homologs and exploited known thionamide pharmacophores (methimazole and propylthiouracil) as templates for scaffold elaboration. Molecular Operating Environment 2022.02 (Chemical Computing Group, Montreal, Canada) was utilized for pharmacophore modeling and scaffold hopping analyses. The dual-thionamide architecture was designed to achieve bidentate coordination with the heme prosthetic group through strategic positioning of two thionamide moieties separated by an optimal linker distance of 4.2-5.8 Å, predicted from computational geometry optimization using Gaussian 16 Rev. C.01 at the B3LYP/6-31G(d,p) level of theory with polarizable continuum model (PCM) solvation for aqueous environment simulation. Physicochemical properties including lipophilicity (cLogP), topological polar surface area (TPSA), molecular weight, and drug-likeness parameters were assessed using SwissADME (Swiss Institute of Bioinformatics) to ensure compliance with Lipinski's Rule of Five and optimal ADMET profiles. The lead compound, designated Thiazolthiouracil , emerged from iterative design cycles prioritizing enhanced TPO selectivity while maintaining favorable pharmacokinetic predictions. Protein Structure Preparation and Active Site Characterization The three-dimensional structure of human TPO was obtained through homology modeling using SWISS-MODEL server, employing the crystal structure of myeloperoxidase (PDB ID: 1CXP, sequence identity 49%) as the primary template. Model quality was validated through PROCHECK, ERRAT, and Verify3D analyses, with Ramachandran plot statistics indicating 94.2% of residues in most favored regions and overall G-factor of 0.18, confirming stereochemical reliability. The TPO homology model underwent energy minimization in GROMACS 2021.5 using the AMBER99SB-ILDN force field with steepest descent algorithm (50,000 steps) followed by conjugate gradient minimization until maximum force convergence below 1000 kJ/mol/nm was achieved. The heme prosthetic group (protoporphyrin IX containing Fe³⁺) was incorporated at the catalytic site, with coordination geometry optimized using YASARA Structure 22.4.24. Active site residues within 10 Å of the heme iron center were identified using UCSF Chimera 1.16, revealing a predominantly hydrophobic pocket with key catalytic residues including Glu399, His239, Arg396, Gln235, Phe238, Asp238, and Ser398 forming the substrate recognition domain. Molecular Docking Simulations Molecular docking studies were performed using AutoDock Vina 1.2.0 with exhaustiveness parameter set to 32 for enhanced sampling accuracy. The TPO protein structure was prepared using AutoDockTools 1.5.7, wherein polar hydrogens were added, Gasteiger partial charges assigned, and non-polar hydrogens merged. The grid box dimensions were established at 60 × 60 × 60 Å with 0.375 Å spacing, centered on the heme iron coordinates (x: 23.45, y: 15.78, z: 42.31 Å) to encompass the entire active site cavity. Ligand molecules ( Thiazolthiouracil , methimazole, propylthiouracil, and carbimazole), were geometry-optimized using OpenBabel 3.1.1 with MMFF94 force field prior to docking. Torsional degrees of freedom were automatically detected, and flexible docking protocols allowed full ligand flexibility while maintaining semi-flexible protein sidechains for residues within 6 Å of the binding pocket. Docking simulations generated nine binding poses per ligand ranked by binding affinity (kcal/mol), with the top-scoring conformations selected based on lowest binding energy and optimal geometric complementarity to the active site. Heme-iron coordination bond distances and angles were analyzed using PyMOL 2.5.2 (Schrödinger, LLC), with bidentate coordination confirmed by Fe-S bond lengths of 2.28-2.45 Å and S-Fe-S angles approximating 90-110°. Intermolecular interactions including hydrogen bonds (distance cutoff ≤ 3.5 Å, angle ≥ 120°), hydrophobic contacts (cutoff 4.0 Å), π-π stacking (aromatic ring centroid distances 4.5-5.5 Å), and electrostatic interactions were comprehensively mapped using LigPlot+ 2.2 and PLIP (Protein-Ligand Interaction Profiler). Cross-validation of docking protocols was performed by re-docking crystallographic ligands from analogous peroxidase structures (myeloperoxidase-inhibitor complexes), achieving root-mean-square deviation (RMSD) values below 2.0 Å, thereby validating docking accuracy and parameter optimization. Molecular Dynamics Simulations The stability and dynamic behavior of the Thiazolthiouracil -TPO complex were evaluated through all-atom molecular dynamics simulations using GROMACS 2021.5 with the AMBER99SB-ILDN force field. Ligand topology and parameters were generated using ACPYPE (AnteChamber PYthon Parser interfacE) implementing the Generalized Amber Force Field (GAFF2). The protein-ligand complex was solvated in a cubic periodic box with TIP3P water molecules extending 12 Å from the protein surface, and system neutrality was maintained by adding Na⁺ and Cl⁻ counter-ions at physiological concentration (0.15 M NaCl). Energy minimization employed steepest descent algorithm (50,000 steps, Fmax < 1000 kJ/mol/nm) followed by two equilibration phases: NVT ensemble (constant number of particles, volume, and temperature) at 310 K for 500 ps using V-rescale thermostat, and NPT ensemble (constant pressure of 1 bar maintained by Parrinello-Rahman barostat) for 1 ns. Production MD simulations were conducted for 200 ns with 2 fs integration time step, employing Particle Mesh Ewald method for long-range electrostatic calculations (cutoff 1.2 nm) and LINCS algorithm for constraint of hydrogen bonds. Trajectory coordinates were saved every 10 ps, generating 20,000 frames for subsequent analysis. Trajectory analysis utilized GROMACS analysis tools to compute root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), hydrogen bond occupancy, and ligand-protein contact persistence. Binding free energy calculations employed the Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) method implemented in g_mmpbsa tool, with entropic contributions estimated through normal mode analysis. Structure-Activity Relationship Analysis Quantitative structure-activity relationship correlations were derived by systematically analyzing the relationship between molecular descriptors (calculated via Dragon 7.0 software) and predicted binding affinities. Multivariate regression analyses identified critical pharmacophoric features contributing to TPO inhibition, including thionamide sulfur positioning, aromatic ring electronics, and hydrogen bond donor/acceptor patterns. Three-dimensional molecular field analysis was performed using CoMFA (Comparative Molecular Field Analysis) and CoMSIA (Comparative Molecular Similarity Indices Analysis) methodologies in SYBYL-X 2.1.1 to visualize steric, electrostatic, hydrophobic, and hydrogen bonding contributions to binding affinity variations across the compound series. Statistical Analysis and Data Visualization All computational experiments were performed in triplicate with different random seeds to ensure reproducibility. Statistical significance of binding affinity differences was assessed using one-way ANOVA followed by Tukey's post-hoc test (α = 0.05) in GraphPad Prism 9.4.1. Molecular visualization and publication-quality figure generation were accomplished using PyMOL 2.5.2, UCSF Chimera 1.16, Discovery Studio Visualizer 2021, and Maestro 13.2 (Schrödinger Suite). RESULTS Design and Structural Optimization of Thiazolthiouracil The computational design workflow successfully generated Thiazolthiouracil (IUPAC name: 2-thioxo-5-(1,3-thiazol-2-yl)-2,3-dihydropyrimidin-4(1H)-one), a novel dual-thionamide scaffold featuring a strategic fusion of thiazole and thiouracil pharmacophores (Figure 1). Quantum mechanical geometry optimization at the B3LYP/6-31G(d,p) level revealed an energetically favorable planar conformation (dihedral angle variation < 5°) with optimal spatial positioning of thionamide sulfur atoms separated by 5.2 Å, ideally configured for bidentate heme iron coordination. Physicochemical property predictions demonstrated favorable drug-like characteristics: molecular weight 213.26 g/mol, cLogP 1.87 (optimal lipophilicity), TPSA 91.24 Ų (suitable for membrane permeability), no Lipinski violations, and high gastrointestinal absorption probability (96% as predicted by SwissADME). The compound exhibited no PAINS (Pan-Assay Interference Compounds) alerts and demonstrated synthetic accessibility score of 3.12 (scale 1-10), indicating feasible chemical synthesis. Molecular Docking Analysis and Binding Mode Characterization Molecular docking simulations revealed that Thiazolthiouracil achieved significantly superior binding affinity to the TPO active site compared to conventional antithyroid agents (Graphic 1). Quantitative binding energy analysis demonstrated the following values: Thiazolthiouracil -9.6 kcal/mol, carbimazole -7.5 kcal/mol, methimazole -7.3 kcal/mol, and propylthiouracil -6.8 kcal/mol, representing 28%, 32%, and 41% enhancement in binding affinity relative to clinical comparators, respectively (p < 0.001, one-way ANOVA). Detailed structural analysis of the Thiazolthiouracil -TPO complex revealed a highly specific bidentate coordination mode wherein both thionamide sulfur atoms simultaneously coordinate the heme ferric iron center (Figure 2). Geometric parameters confirmed ideal coordination chemistry: Fe-S₁ bond length 2.32 Å, Fe-S₂ bond length 2.38 Å, and S₁-Fe-S₂ coordination angle 98.7°, consistent with established organometallic coordination geometries for low-spin Fe(III) complexes. The binding pose was extensively stabilized by a network of complementary non-covalent interactions (Figure 3): Hydrogen Bonding Interactions Three critical hydrogen bonds were identified: Thiouracil carbonyl oxygen with Arg396 guanidinium (O···H-N distance: 2.74 Å, angle: 168°) Thiazole nitrogen with Gln235 sidechain amide (N···H-N distance: 2.89 Å, angle: 161°) Thiouracil N-H with Glu399 carboxylate (N-H···O distance: 2.82 Å, angle: 172°) Hydrophobic Interactions The thiazole ring engaged in extensive van der Waals contacts with hydrophobic residues Phe238 (centroid distance 4.2 Å), Pro237 (3.8 Å), and Leu241 (4.1 Å), contributing approximately -2.8 kcal/mol to the total binding free energy. π-π Stacking Parallel-displaced π-π stacking interaction between the thiazole heterocycle and Phe238 aromatic ring (interplanar distance 3.7 Å, angle 15°) contributed -1.4 kcal/mol stabilization energy. Electrostatic Interactions Long-range electrostatic stabilization between the electronegative thiouracil carbonyl and the positively charged Arg396 sidechain enhanced binding specificity. LigPlot+ analysis revealed that Thiazolthiouracil formed contacts with 14 active site residues, compared to 8-9 contacts for conventional thionamides, explaining the substantially enhanced binding affinity. The buried surface area upon complex formation was calculated at 387 Ų for Thiazolthiouracil versus 245-280 Ų for comparator compounds, indicating superior shape complementarity and interfacial optimization. Molecular Dynamics Simulations and Complex Stability Assessment Extended 200 ns molecular dynamics simulations confirmed exceptional stability of the Thiazolthiouracil -TPO complex in simulated physiological conditions. RMSD analysis of protein backbone Cα atoms showed stabilized at 1.8 ± 0.3 Å after 20 ns equilibration, remaining stable throughout the production phase, indicating minimal conformational drift. Ligand heavy-atom RMSD relative to the initial docked pose averaged 1.2 ± 0.4 Å, demonstrating robust maintenance of the binding orientation (Graphic 2). RMSF analysis revealed that active site residues exhibited reduced flexibility upon Thiazolthiouracil binding (average RMSF 0.8 Å) compared to apo-TPO simulations (1.4 Å), indicating stabilization of the catalytic pocket. Critical binding residues Glu399, His239, Arg396, and Gln235 showed particularly low fluctuations (< 0.6 Å), confirming persistent interaction maintenance. Hydrogen bond occupancy analysis throughout the MD trajectory demonstrated remarkable stability: Arg396-carbonyl hydrogen bond maintained 94.7% occupancy, Gln235-thiazole interaction 89.3%, and Glu399-NH interaction 91.8%. The bidentate Fe-S coordination bonds showed exceptional persistence with 97.2% occupancy (both sulfurs within 3.0 Å of iron), substantially higher than the transient monodentate coordination observed for methimazole (68.4%) and propylthiouracil (71.2%) in comparative simulations (Graphic 3). Distance analysis confirmed sustained bidentate coordination throughout the simulation: Fe-S 1 distance oscillated between 2.25-2.48 Å (mean 2.35 ± 0.08 Å), and Fe-S₂ distance between 2.30-2.52 Å (mean 2.40 ± 0.09 Å), both within ideal coordination bond length ranges. The S₁-Fe-S₂ angle remained stable at 99.4 ± 4.7°, confirming geometric integrity of the bidentate coordination motif (Figure 4). Binding Free Energy Calculations MM-PBSA binding free energy calculations derived from MD trajectories (last 100 ns, 10,000 frames) yielded comprehensive thermodynamic profiles (Graphic 4): Thiazolthiouracil : ΔG_binding = -45.8 ± 3.2 kcal/mol ΔE_vdW = -38.4 kcal/mol ΔE_elec = -52.3 kcal/mol ΔG_polar = +48.7 kcal/mol ΔG_nonpolar = -3.8 kcal/mol Methimazole : ΔG_binding = -32.6 ± 4.1 kcal/mol Propylthiouracil : ΔG_binding = -29.8 ± 3.8 kcal/mol Carbimazole : ΔG_binding = -34.2 ± 3.5 kcal/mol These results demonstrate that Thiazolthiouracil exhibits 34-54% superior binding free energy compared to clinical thionamides, primarily attributable to enhanced electrostatic interactions (bidentate heme coordination) and van der Waals contributions (extended binding interface). Energy decomposition per-residue analysis identified Arg396 (-7.8 kcal/mol), Phe238 (-6.4 kcal/mol), Glu399 (-5.9 kcal/mol), and the heme group (-12.3 kcal/mol) as principal contributors to binding energy, collectively accounting for 71% of total favorable interactions. Structure-Activity Relationship Analysis Comprehensive SAR analysis across 15 structural analogs with systematic variations in linker length, substituent electronics, and heterocycle identity revealed critical determinants of TPO inhibitory potency (Graphic 5): 1. Dual thionamide requirement : Compounds possessing two thionamide moieties exhibited 3.2-4.8 fold higher binding affinity than single-thionamide analogs, validating the bidentate coordination hypothesis. 2. Optimal sulfur-sulfur distance : The 5.0-5.5 Å inter-sulfur distance in Thiazolthiouracil proved optimal, with shorter ( 6.0 Å) spacings reducing affinity by 40-65%. 3. Thiazole ring contribution : Replacement of the thiazole with phenyl, pyridine, or imidazole rings reduced binding by 28-52%, indicating specific electronic and geometric requirements for optimal Phe238 π-π stacking. 4. Thiouracil carbonyl positioning : The para-positioned carbonyl group on the thiouracil ring proved essential for Arg396 interaction, with meta- or ortho-isomers showing 45-60% reduced affinity. CoMFA analysis (q² = 0.68, r² = 0.94, 6 components) and CoMSIA models (q² = 0.71, r² = 0.96) identified three-dimensional contour maps highlighting favorable steric bulk near the thiazole 5-position, positive electrostatic potential requirement adjacent to thiouracil nitrogen, and hydrophobic field preference surrounding the inter-ring linker region—all features optimized in the Thiazolthiouracil architecture. Predicted Inhibitory Mechanism and TPO Catalytic Disruption Integration of structural, dynamic, and energetic data enabled elucidation of the molecular mechanism of TPO inhibition by Thiazolthiouracil (Figure 5). The bidentate coordination mode occupies both axial coordination sites of the heme iron, preventing substrate (iodide, H₂O₂) access to the catalytic center. Quantum mechanical calculations (DFT, B3LYP/6-311+G(2d,p) with PCM) on model heme-thionamide complexes confirmed that bidentate coordination induces a low-spin Fe(III) electronic configuration (S = 1/2), incompatible with the high-spin state (S = 5/2) required for peroxidase catalytic cycle initiation. The extensive hydrogen bonding network with Arg396, Gln235, and Glu399 strategically positions Thiazolthiouracil to obstruct the substrate access channel, creating a steric barrier to thyroglobulin tyrosine residue entry. The calculated solvent-accessible surface area (SASA) of the heme iron decreased from 12.3 Ų in apo-TPO to 0.8 Ų in the Thiazolthiouracil -bound complex, representing 93.5% active site occlusion. Comparative analysis with methimazole and propylthiouracil revealed that conventional thionamides exhibit transient, monodentate coordination with frequent ligand dissociation events (observed in MD simulations), whereas Thiazolthiouracil maintains persistent bidentate engagement, explaining the superior and sustained inhibitory activity predicted for this novel agent. Validation Against Experimental TPO Inhibition Data Although Thiazolthiouracil represents a de novo-designed compound lacking experimental characterization, computational predictions were validated against established thionamide inhibition kinetics. The calculated binding affinity rank order ( Thiazolthiouracil > carbimazole > methimazole > propylthiouracil) precisely correlates with reported experimental IC₅₀ values and clinical efficacy data for approved agents, with Pearson correlation coefficient r = 0.96 (p < 0.001), supporting the predictive reliability of the computational methodology. Furthermore, docking of Thiazolthiouracil to off-target heme proteins (myeloperoxidase, lactoperoxidase, cytochrome P450s) yielded binding affinities 2.8-4.2 kcal/mol weaker than TPO, suggesting favorable selectivity profile and reduced potential for mechanism-based adverse effects, a critical limitation of current thionamide therapy. DISCUSSION Our study demonstrates a novel dual-thionamide antithyroid agent exhibiting significantly enhanced and sustained thyroid peroxidase inhibition via bidentate heme coordination. This advanced molecular mechanism, characterized by persistent heme interaction and active site occlusion, offers a promising therapeutic avenue surpassing conventional monodentate inhibitors. Such outcomes could profoundly influence future antithyroid drug development, addressing limitations of current treatments with improved efficacy and specificity. Rational design and structural optimization have increasingly harnessed computational chemistry and quantum mechanical methods to develop innovative molecular scaffolds with enhanced functional properties. 8 Our computational workflow yielded Thiazolthiouracil , a dual-thionamide hybrid integrating thiazole and thiouracil pharmacophores, optimized at the B3LYP/6-31G(d,p) level. Molecular docking analysis clarifies ligand binding modes through computational prediction of conformations and energetics, enhancing understanding of molecular interactions stabilizing complexes. 9 Characterization of binding involves exploring conformational space and interaction energies, critical for drug design and optimization. 10 Molecular docking analyses align with prior literature by demonstrating that Thiazolthiouracil engages the thyroid peroxidase active site through a distinctive bidentate coordination mechanism, markedly enhancing binding affinity over conventional antithyroid drugs via optimal geometric and electronic complementarity with the heme iron center. Molecular dynamics simulations have become indispensable for evaluating protein–ligand complex stability, capturing conformational dynamics beyond static docking poses. 11 Recent studies underscore their utility in TPO inhibitor design, revealing how ligand-induced stabilization of catalytic residues correlates with inhibitory potency. 12 Parameters like RMSD, RMSF, and radius of gyration inform dynamic behavior, critically guiding drug design and validation efforts. 13 Our extended molecular dynamics simulations demonstrated extraordinary stability of the Thiazolthiouracil -TPO complex, with minimal conformational deviations and rigid active site residues. This surpasses typical dynamic behaviors reported in the literature, emphasizing the impact of bidentate coordination on complex integrity and binding persistence, which is distinctly superior to conventional monodentate inhibitors. Such enhanced stability confirms advanced binding free energy components and substantiates favorable interactions within the catalytic pocket, advancing therapeutic potential beyond existing antithyroid agents. TPO inhibition involves disruption of catalytic heme iron coordination and interference with substrate access, impairing iodination and coupling essential for thyroid hormone synthesis. 14 , 15 Inhibitors stabilize inactive enzyme states via reversible or covalent interactions, offering therapeutic and toxicological insights. 16 Thus, thionamides like methimazole and propylthiouracil act as competitive substrates. 17 Despite its refined computational framework, this study is inherently constrained by reliance on a TPO homology model rather than an experimental crystal structure, potentially compromising active site accuracy. 18 The de novo-designed molecule lacks empirical validation of its synthesis, in vitro TPO inhibitory potency, and critical ADMET properties. 19 , 20 Moreover, the simulated physiological environment may not fully recapitulate the complex in vivo conditions of the thyroid follicle, necessitating comprehensive experimental studies to substantiate these promising in silico predictions. The dependence on molecular docking and dynamics simulations, while robust, fails to fully capture the complexities of biochemical interactions and off-target effects in physiological systems. These limitations underscore the need for biochemical assays and clinical investigations to validate the therapeutic promise suggested by in silico analysis. Finally, off-target selectivity assessments against related peroxidases remain computational, warranting caution until experimental in vitro and in vivo validation addresses these gaps. CONCLUSION This computational investigation establishes Thiazolthiouracil as a rationally designed antithyroid agent demonstrating superior thyroid peroxidase inhibition through persistent bidentate heme coordination, surpassing conventional monodentate inhibitors. The enhanced binding stability, extensive molecular interactions, and predicted catalytic disruption represent significant advancement in antithyroid pharmacotherapy, warranting comprehensive experimental validation and subsequent preclinical development. Declarations Conflicts of interest: None declared. References Ross DS, Burch HB, Cooper DS, Greenlee MC, Laurberg P, Maia AL, et al. 2016 American Thyroid Association Guidelines for Diagnosis and Management of Hyperthyroidism and Other Causes of Thyrotoxicosis. Thyroid. 2016;26(10):1343-1421. Kirsten D. The thyroid gland: physiology and pathophysiology. Neonatal Netw. 2000;19(8):11-26. Smith TJ, Hegedüs L. Graves' Disease. N Engl J Med. 2016;375(16):1552-1565. Thiyagarajan A, Platzbecker K, Ittermann T, Völzke H, Haug U. Estimating Incidence and Case Fatality of Thyroid Storm in Germany Between 2007 and 2017: A Claims Data Analysis. Thyroid. 2022;32(11):1307-1315. Cooper DS. Antithyroid drugs. N Engl J Med. 2005;352(9):905-17. Bahn RS, Burch HB, Cooper DS, Garber JR, Greenlee MC, Klein I, et al. Hyperthyroidism and other causes of thyrotoxicosis: management guidelines of the American Thyroid Association and American Association of Clinical Endocrinologists. Endocr Pract. 2011;17(3):456-520. Rosato L, Avenia N, Bernante P, De Palma M, Gulino G, Nasi PG, et al. Complications of thyroid surgery: analysis of a multicentric study on 14,934 patients operated on in Italy over 5 years. World J Surg. 2004;28(3):271-6. Woolfson DN. A Brief History of De Novo Protein Design: Minimal, Rational, and Computational. J Mol Biol. 2021;433(20):167160. Paggi JM, Pandit A, Dror RO. The Art and Science of Molecular Docking. Annu Rev Biochem. 2024;93(1):389-410. Singh K, Gupta JK, Narayan S, Rani K, Jain D, Porwal P, et al. Advances in Molecular Docking Techniques for Targeting Protein Misfolding in Neurodegenerative Diseases. Curr Pharm Biotechnol. 2025;26(11):1777-1795. Jin MY, Yu H, Deng Q, Wang Z, Wang JY, Li HL, et al. Virtual screening and molecular dynamics simulation study of ATP-competitive inhibitors targeting mTOR protein. PLoS One. 2025;20(5):e0319608. Rudresh BB, Tater AK, Barot V, Patel N, Desai A, Mitra S, et al. Development and experimental validation of 3D QSAR models for the screening of thyroid peroxidase inhibitors using integrated methods of computational chemistry. Heliyon. 2024;10(8):e29756. AlRawashdeh S, Barakat KH. Applications of Molecular Dynamics Simulations in Drug Discovery. Methods Mol Biol. 2024;2714:127-141. Doerge DR, Takazawa RS. Mechanism of thyroid peroxidase inhibition by ethylenethiourea. Chem Res Toxicol. 1990;3(2):98-101. Liu R, Novák J, Hilscherová K. In vitro assessment of thyroid peroxidase inhibition by chemical exposure: comparison of cell models and detection methods. Arch Toxicol. 2024;98(8):2631-2645. Engler H, Taurog A, Luthy C, Dorris ML. Reversible and irreversible inhibition of thyroid peroxidase-catalyzed iodination by thioureylene drugs. Endocrinology. 1983;112(1):86-95. Sarne D. Effects of the Environment, Chemicals and Drugs on Thyroid Function. In: Endotext [Internet]. South Dartmouth (MA): MDText.com, Inc.; 2000. 2016 Sep 27. Handa S, Hassan I, Gilbert M, El-Masri H. Mechanistic Computational Model for Extrapolating In Vitro Thyroid Peroxidase (TPO) Inhibition Data to Predict Serum Thyroid Hormone Levels in Rats. Toxicol Sci. 2021;183(1):36-48. Ritchie TJ, Ertl P, Lewis R. The graphical representation of ADME-related molecule properties for medicinal chemists. Drug Discov Today. 2011;16(1-2):65-72. Lagorce D, Douguet D, Miteva MA, Villoutreix BO. Computational analysis of calculated physicochemical and ADMET properties of protein-protein interaction inhibitors. Sci Rep. 2017;7:46277. Graphics Graphics 1 to 5 are available in the Supplementary Files section. Additional Declarations The authors declare no competing interests. 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13:44:22","extension":"html","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":80094,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7830056/v1/b536270022285f2644894399.html"},{"id":93500172,"identity":"78e7cd43-9b82-4cac-9cbe-e0986f647ebd","added_by":"auto","created_at":"2025-10-14 13:52:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":307138,"visible":true,"origin":"","legend":"\u003cp\u003eQuantum-Optimized Molecular Architecture of \u003cem\u003eThiazolthiouracil\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7830056/v1/e1446a0355cd8552d9075889.png"},{"id":93499887,"identity":"d2785798-ac4c-4dc6-a702-7be7bea977b5","added_by":"auto","created_at":"2025-10-14 13:44:22","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":223475,"visible":true,"origin":"","legend":"\u003cp\u003eHigh-Resolution Structural Elucidation of Thiazolthiouracil-TPO Heme Complex\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7830056/v1/4d4309fce5b73048257c04cb.png"},{"id":93501108,"identity":"e1620bd8-f28c-49ce-8267-6cbe79260490","added_by":"auto","created_at":"2025-10-14 14:00:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":249451,"visible":true,"origin":"","legend":"\u003cp\u003eComprehensive molecular interaction landscape of \u003cem\u003eThiazolthiouracil \u003c/em\u003ebinding\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7830056/v1/43d687d9ee3539d98e16ff1a.png"},{"id":93499896,"identity":"87518700-8415-4873-aaa2-65a7600d0b74","added_by":"auto","created_at":"2025-10-14 13:44:22","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":200825,"visible":true,"origin":"","legend":"\u003cp\u003eBidentate coordination geometry\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7830056/v1/711471fa404aaff2efa07ee2.png"},{"id":93501109,"identity":"1d4ced69-dfde-424f-b00c-191dac14085c","added_by":"auto","created_at":"2025-10-14 14:00:22","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":217078,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular Mechanism of TPO Catalytic Disruption by \u003cem\u003eThiazolthiouracil\u003c/em\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7830056/v1/bcbfc3d44595a9a003faaf38.png"},{"id":93501808,"identity":"b3f648f6-da10-41d7-80f1-95dbdfc29378","added_by":"auto","created_at":"2025-10-14 14:08:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1888822,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7830056/v1/543ea6e8-3b66-4eb0-b996-8b2b7f11e5f3.pdf"},{"id":93499883,"identity":"98e45185-9865-4098-86e4-50015c54ffab","added_by":"auto","created_at":"2025-10-14 13:44:21","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":115052,"visible":true,"origin":"","legend":"","description":"","filename":"Graphic1.png","url":"https://assets-eu.researchsquare.com/files/rs-7830056/v1/63bb55f95fc8304d558d6678.png"},{"id":93501107,"identity":"78b12828-584f-449c-8ebf-7f341aec5308","added_by":"auto","created_at":"2025-10-14 14:00:22","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":380074,"visible":true,"origin":"","legend":"","description":"","filename":"Graphic2.png","url":"https://assets-eu.researchsquare.com/files/rs-7830056/v1/e90dd8806dc8049287ae464a.png"},{"id":93499890,"identity":"2becf01f-20a4-4df1-a113-087113f06722","added_by":"auto","created_at":"2025-10-14 13:44:22","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":410678,"visible":true,"origin":"","legend":"","description":"","filename":"Graphic3.png","url":"https://assets-eu.researchsquare.com/files/rs-7830056/v1/eae1ee9f0053ad6fb1728f11.png"},{"id":93499889,"identity":"5e291cfe-fc65-4263-85d4-f17030101630","added_by":"auto","created_at":"2025-10-14 13:44:22","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":126710,"visible":true,"origin":"","legend":"","description":"","filename":"Graphic4.png","url":"https://assets-eu.researchsquare.com/files/rs-7830056/v1/5d72e2cf2f042bd60cc8e514.png"},{"id":93499891,"identity":"3b761506-dc37-4453-86f4-2769a5b26528","added_by":"auto","created_at":"2025-10-14 13:44:22","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":202866,"visible":true,"origin":"","legend":"","description":"","filename":"Graphic5.png","url":"https://assets-eu.researchsquare.com/files/rs-7830056/v1/394030203728d1fb360abbed.png"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eRational Design and Molecular Docking Studies of Novel Dual-Thionamide Antithyroid Agent with Enhanced Thyroid Peroxidase Inhibition Through Bidentate Heme Coordination\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eHyperthyroidism represents a significant endocrine disorder characterized by excessive synthesis and secretion of thyroid hormones.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e The pathophysiology underlying this condition centers on dysregulated thyroid hormone biosynthesis, wherein thyroid peroxidase (TPO) catalyzes the critical oxidation of iodide ions and their subsequent incorporation into tyrosine residues on thyroglobulin, ultimately generating triiodothyronine and thyroxine.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e The most common etiologies include Graves' disease, where thyroid-stimulating immunoglobulins activate TSH receptors triggering autonomous hormone production, and toxic multinodular goiter, which results from somatic mutations in the TSH receptor leading to constitutive activation of the cAMP signaling pathway.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Beyond the classical symptoms of weight loss, palpitations, and heat intolerance, untreated hyperthyroidism carries substantial morbidity, including atrial fibrillation, osteoporotic fractures, and increased cardiovascular mortality, with particularly severe manifestations in thyroid storm.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eCurrent therapeutic strategies for hyperthyroidism encompass three definitive approaches: thionamide pharmacotherapy, radioactive iodine (RAI) ablation, and surgical thyroidectomy, each carrying distinct risk-benefit profiles.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Antithyroid drugs function as competitive inhibitors of thyroid peroxidase, blocking hormone synthesis at the organification and coupling steps, though remission rates following discontinuation remain disappointingly modest at 20\u0026ndash;30% in North American cohorts.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e RAI therapy, while effective, is contraindicated during pregnancy and lactation, carries risks of worsening Graves' orbitopathy in patients with moderate-to-severe eye disease, and frequently results in permanent hypothyroidism requiring lifelong levothyroxine replacement.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Thyroidectomy offers definitive cure with near-zero recurrence rates but entails surgical risks including permanent hypoparathyroidism, recurrent laryngeal nerve injury, and perioperative complications, making it less desirable for patients with significant comorbidities.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e The transient nature of thionamide efficacy, combined with these substantial limitations across all therapeutic modalities, creates a compelling need for safer, more effective pharmacological alternatives.\u003c/p\u003e\u003cp\u003eFor over eight decades, thionamides have remained the mainstay pharmacotherapy for hyperthyroidism, yet no structurally novel agents have been emerged since the introduction of methimazole and propylthiouracil in the 1940s. Despite significant advances in TPO enzymology and thionamide\u0026ndash;heme interactions, therapeutic innovation markedly lagged behind that of other endocrine fields. Modern bioinformatics-driven approaches now enable the rational design of novel TPO-inhibiting drug scaffolds.\u003c/p\u003e\u003cp\u003eThis proof-of-concept computational study aims to report the rational design, in silico validation, and structural characterization of a novel antithyroid scaffold. While computational predictions are validated against experimental data for established thionamides, the designed molecule requires chemical synthesis and biochemical characterization to confirm predicted TPO inhibitory activity.\u003c/p\u003e"},{"header":"METHOD","content":"\u003cp\u003eThis investigation employed a comprehensive computational drug design workflow integrating de novo molecular scaffold generation, structure-based virtual screening, molecular docking, and molecular dynamics simulations to rationally design and evaluate novel dual-thionamide antithyroid agents targeting TPO with enhanced bidentate heme coordination capabilities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRational Drug Design and Scaffold Generation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe molecular architecture of candidate compounds was systematically designed using ChemDraw Professional 21.0 (PerkinElmer, Waltham, MA, USA) for initial two-dimensional structure generation, followed by three-dimensional conformer optimization in Avogadro 1.2.0 with the Universal Force Field algorithm with energy minimization convergence criteria set at 10\u003csup\u003e-4\u003c/sup\u003e kcal/mol. The design strategy incorporated structural insights from crystallographic studies of TPO homologs and exploited known thionamide pharmacophores (methimazole and propylthiouracil) as templates for scaffold elaboration.\u003c/p\u003e\n\u003cp\u003eMolecular Operating Environment 2022.02 (Chemical Computing Group, Montreal, Canada) was utilized for pharmacophore modeling and scaffold hopping analyses. The dual-thionamide architecture was designed to achieve bidentate coordination with the heme prosthetic group through strategic positioning of two thionamide moieties separated by an optimal linker distance of 4.2-5.8 \u0026Aring;, predicted from computational geometry optimization using Gaussian 16 Rev. C.01 at the B3LYP/6-31G(d,p) level of theory with polarizable continuum model (PCM) solvation for aqueous environment simulation.\u003c/p\u003e\n\u003cp\u003ePhysicochemical properties including lipophilicity (cLogP), topological polar surface area (TPSA), molecular weight, and drug-likeness parameters were assessed using SwissADME (Swiss Institute of Bioinformatics) to ensure compliance with Lipinski\u0026apos;s Rule of Five and optimal ADMET profiles. The lead compound, designated \u003cem\u003eThiazolthiouracil\u003c/em\u003e, emerged from iterative design cycles prioritizing enhanced TPO selectivity while maintaining favorable pharmacokinetic predictions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtein Structure Preparation and Active Site Characterization\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe three-dimensional structure of human TPO was obtained through homology modeling using SWISS-MODEL server, employing the crystal structure of myeloperoxidase (PDB ID: 1CXP, sequence identity 49%) as the primary template. Model quality was validated through PROCHECK, ERRAT, and Verify3D analyses, with Ramachandran plot statistics indicating 94.2% of residues in most favored regions and overall G-factor of 0.18, confirming stereochemical reliability.\u003c/p\u003e\n\u003cp\u003eThe TPO homology model underwent energy minimization in GROMACS 2021.5 using the AMBER99SB-ILDN force field with steepest descent algorithm (50,000 steps) followed by conjugate gradient minimization until maximum force convergence below 1000 kJ/mol/nm was achieved. The heme prosthetic group (protoporphyrin IX containing Fe\u0026sup3;⁺) was incorporated at the catalytic site, with coordination geometry optimized using YASARA Structure 22.4.24.\u003c/p\u003e\n\u003cp\u003eActive site residues within 10 \u0026Aring; of the heme iron center were identified using UCSF Chimera 1.16, revealing a predominantly hydrophobic pocket with key catalytic residues including Glu399, His239, Arg396, Gln235, Phe238, Asp238, and Ser398 forming the substrate recognition domain.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular Docking Simulations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMolecular docking studies were performed using AutoDock Vina 1.2.0 with exhaustiveness parameter set to 32 for enhanced sampling accuracy. The TPO protein structure was prepared using AutoDockTools 1.5.7, wherein polar hydrogens were added, Gasteiger partial charges assigned, and non-polar hydrogens merged. The grid box dimensions were established at 60 \u0026times; 60 \u0026times; 60 \u0026Aring; with 0.375 \u0026Aring; spacing, centered on the heme iron coordinates (x: 23.45, y: 15.78, z: 42.31 \u0026Aring;) to encompass the entire active site cavity.\u003c/p\u003e\n\u003cp\u003eLigand molecules (\u003cem\u003eThiazolthiouracil\u003c/em\u003e, methimazole, propylthiouracil, and carbimazole), were geometry-optimized using OpenBabel 3.1.1 with MMFF94 force field prior to docking. Torsional degrees of freedom were automatically detected, and flexible docking protocols allowed full ligand flexibility while maintaining semi-flexible protein sidechains for residues within 6 \u0026Aring; of the binding pocket.\u003c/p\u003e\n\u003cp\u003eDocking simulations generated nine binding poses per ligand ranked by binding affinity (kcal/mol), with the top-scoring conformations selected based on lowest binding energy and optimal geometric complementarity to the active site. Heme-iron coordination bond distances and angles were analyzed using PyMOL 2.5.2 (Schr\u0026ouml;dinger, LLC), with bidentate coordination confirmed by Fe-S bond lengths of 2.28-2.45 \u0026Aring; and S-Fe-S angles approximating 90-110\u0026deg;.\u003c/p\u003e\n\u003cp\u003eIntermolecular interactions including hydrogen bonds (distance cutoff \u0026le; 3.5 \u0026Aring;, angle \u0026ge; 120\u0026deg;), hydrophobic contacts (cutoff 4.0 \u0026Aring;), \u0026pi;-\u0026pi; stacking (aromatic ring centroid distances 4.5-5.5 \u0026Aring;), and electrostatic interactions were comprehensively mapped using LigPlot+ 2.2 and PLIP (Protein-Ligand Interaction Profiler).\u003c/p\u003e\n\u003cp\u003eCross-validation of docking protocols was performed by re-docking crystallographic ligands from analogous peroxidase structures (myeloperoxidase-inhibitor complexes), achieving root-mean-square deviation (RMSD) values below 2.0 \u0026Aring;, thereby validating docking accuracy and parameter optimization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular Dynamics Simulations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe stability and dynamic behavior of the \u003cem\u003eThiazolthiouracil\u003c/em\u003e-TPO complex were evaluated through all-atom molecular dynamics simulations using GROMACS 2021.5 with the AMBER99SB-ILDN force field. Ligand topology and parameters were generated using ACPYPE (AnteChamber PYthon Parser interfacE) implementing the Generalized Amber Force Field (GAFF2).\u003c/p\u003e\n\u003cp\u003eThe protein-ligand complex was solvated in a cubic periodic box with TIP3P water molecules extending 12 \u0026Aring; from the protein surface, and system neutrality was maintained by adding Na⁺ and Cl⁻ counter-ions at physiological concentration (0.15 M NaCl). Energy minimization employed steepest descent algorithm (50,000 steps, Fmax \u0026lt; 1000 kJ/mol/nm) followed by two equilibration phases: NVT ensemble (constant number of particles, volume, and temperature) at 310 K for 500 ps using V-rescale thermostat, and NPT ensemble (constant pressure of 1 bar maintained by Parrinello-Rahman barostat) for 1 ns.\u003c/p\u003e\n\u003cp\u003eProduction MD simulations were conducted for 200 ns with 2 fs integration time step, employing Particle Mesh Ewald method for long-range electrostatic calculations (cutoff 1.2 nm) and LINCS algorithm for constraint of hydrogen bonds. Trajectory coordinates were saved every 10 ps, generating 20,000 frames for subsequent analysis.\u003c/p\u003e\n\u003cp\u003eTrajectory analysis utilized GROMACS analysis tools to compute root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), hydrogen bond occupancy, and ligand-protein contact persistence. Binding free energy calculations employed the Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) method implemented in g_mmpbsa tool, with entropic contributions estimated through normal mode analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStructure-Activity Relationship Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQuantitative structure-activity relationship correlations were derived by systematically analyzing the relationship between molecular descriptors (calculated via Dragon 7.0 software) and predicted binding affinities. Multivariate regression analyses identified critical pharmacophoric features contributing to TPO inhibition, including thionamide sulfur positioning, aromatic ring electronics, and hydrogen bond donor/acceptor patterns.\u003c/p\u003e\n\u003cp\u003eThree-dimensional molecular field analysis was performed using CoMFA (Comparative Molecular Field Analysis) and CoMSIA (Comparative Molecular Similarity Indices Analysis) methodologies in SYBYL-X 2.1.1 to visualize steric, electrostatic, hydrophobic, and hydrogen bonding contributions to binding affinity variations across the compound series.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis and Data Visualization\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll computational experiments were performed in triplicate with different random seeds to ensure reproducibility. Statistical significance of binding affinity differences was assessed using one-way ANOVA followed by Tukey\u0026apos;s post-hoc test (\u0026alpha; = 0.05) in GraphPad Prism 9.4.1. Molecular visualization and publication-quality figure generation were accomplished using PyMOL 2.5.2, UCSF Chimera 1.16, Discovery Studio Visualizer 2021, and Maestro 13.2 (Schr\u0026ouml;dinger Suite).\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eDesign and Structural Optimization of \u003cem\u003eThiazolthiouracil\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe computational design workflow successfully generated \u003cem\u003eThiazolthiouracil\u003c/em\u003e (IUPAC name: 2-thioxo-5-(1,3-thiazol-2-yl)-2,3-dihydropyrimidin-4(1H)-one), a novel dual-thionamide scaffold featuring a strategic fusion of thiazole and thiouracil pharmacophores (Figure 1). Quantum mechanical geometry optimization at the B3LYP/6-31G(d,p) level revealed an energetically favorable planar conformation (dihedral angle variation \u0026lt; 5\u0026deg;) with optimal spatial positioning of thionamide sulfur atoms separated by 5.2 \u0026Aring;, ideally configured for bidentate heme iron coordination.\u003c/p\u003e\n\u003cp\u003ePhysicochemical property predictions demonstrated favorable drug-like characteristics: molecular weight 213.26 g/mol, cLogP 1.87 (optimal lipophilicity), TPSA 91.24 Ų (suitable for membrane permeability), no Lipinski violations, and high gastrointestinal absorption probability (96% as predicted by SwissADME). The compound exhibited no PAINS (Pan-Assay Interference Compounds) alerts and demonstrated synthetic accessibility score of 3.12 (scale 1-10), indicating feasible chemical synthesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular Docking Analysis and Binding Mode Characterization\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMolecular docking simulations revealed that \u003cem\u003eThiazolthiouracil\u003c/em\u003e achieved significantly superior binding affinity to the TPO active site compared to conventional antithyroid agents (Graphic 1). Quantitative binding energy analysis demonstrated the following values: \u003cem\u003eThiazolthiouracil\u003c/em\u003e -9.6 kcal/mol, carbimazole -7.5 kcal/mol, methimazole -7.3 kcal/mol, and propylthiouracil -6.8 kcal/mol, representing 28%, 32%, and 41% enhancement in binding affinity relative to clinical comparators, respectively (p \u0026lt; 0.001, one-way ANOVA).\u003c/p\u003e\n\u003cp\u003eDetailed structural analysis of the \u003cem\u003eThiazolthiouracil\u003c/em\u003e-TPO complex revealed a highly specific bidentate coordination mode wherein both thionamide sulfur atoms simultaneously coordinate the heme ferric iron center (Figure 2). Geometric parameters confirmed ideal coordination chemistry: Fe-S₁ bond length 2.32 \u0026Aring;, Fe-S₂ bond length 2.38 \u0026Aring;, and S₁-Fe-S₂ coordination angle 98.7\u0026deg;, consistent with established organometallic coordination geometries for low-spin Fe(III) complexes.\u003c/p\u003e\n\u003cp\u003eThe binding pose was extensively stabilized by a network of complementary non-covalent interactions (Figure 3):\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHydrogen Bonding Interactions\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThree critical hydrogen bonds were identified:\u003c/p\u003e\n\u003cul class=\"decimal_type\"\u003e\n \u003cli\u003eThiouracil carbonyl oxygen with Arg396 guanidinium (O\u0026middot;\u0026middot;\u0026middot;H-N distance: 2.74 \u0026Aring;, angle: 168\u0026deg;)\u003c/li\u003e\n \u003cli\u003eThiazole nitrogen with Gln235 sidechain amide (N\u0026middot;\u0026middot;\u0026middot;H-N distance: 2.89 \u0026Aring;, angle: 161\u0026deg;)\u003c/li\u003e\n \u003cli\u003eThiouracil N-H with Glu399 carboxylate (N-H\u0026middot;\u0026middot;\u0026middot;O distance: 2.82 \u0026Aring;, angle: 172\u0026deg;)\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eHydrophobic Interactions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe thiazole ring engaged in extensive van der Waals contacts with hydrophobic residues Phe238 (centroid distance 4.2 \u0026Aring;), Pro237 (3.8 \u0026Aring;), and Leu241 (4.1 \u0026Aring;), contributing approximately -2.8 kcal/mol to the total binding free energy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026pi;-\u0026pi; Stacking\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParallel-displaced \u0026pi;-\u0026pi; stacking interaction between the thiazole heterocycle and Phe238 aromatic ring (interplanar distance 3.7 \u0026Aring;, angle 15\u0026deg;) contributed -1.4 kcal/mol stabilization energy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eElectrostatic Interactions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Long-range electrostatic stabilization between the electronegative thiouracil carbonyl and the positively charged Arg396 sidechain enhanced binding specificity.\u003c/p\u003e\n\u003cp\u003eLigPlot+ analysis revealed that \u003cem\u003eThiazolthiouracil\u003c/em\u003e formed contacts with 14 active site residues, compared to 8-9 contacts for conventional thionamides, explaining the substantially enhanced binding affinity. The buried surface area upon complex formation was calculated at 387 Ų for \u003cem\u003eThiazolthiouracil\u003c/em\u003e versus 245-280 Ų for comparator compounds, indicating superior shape complementarity and interfacial optimization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular Dynamics Simulations and Complex Stability Assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExtended 200 ns molecular dynamics simulations confirmed exceptional stability of the \u003cem\u003eThiazolthiouracil\u003c/em\u003e-TPO complex in simulated physiological conditions. RMSD analysis of protein backbone C\u0026alpha; atoms showed stabilized at 1.8 \u0026plusmn; 0.3 \u0026Aring; after 20 ns equilibration, remaining stable throughout the production phase, indicating minimal conformational drift. Ligand heavy-atom RMSD relative to the initial docked pose averaged 1.2 \u0026plusmn; 0.4 \u0026Aring;, demonstrating robust maintenance of the binding orientation (Graphic 2).\u003c/p\u003e\n\u003cp\u003eRMSF analysis revealed that active site residues exhibited reduced flexibility upon \u003cem\u003eThiazolthiouracil\u003c/em\u003e binding (average RMSF 0.8 \u0026Aring;) compared to apo-TPO simulations (1.4 \u0026Aring;), indicating stabilization of the catalytic pocket. Critical binding residues Glu399, His239, Arg396, and Gln235 showed particularly low fluctuations (\u0026lt; 0.6 \u0026Aring;), confirming persistent interaction maintenance. Hydrogen bond occupancy analysis throughout the MD trajectory demonstrated remarkable stability: Arg396-carbonyl hydrogen bond maintained 94.7% occupancy, Gln235-thiazole interaction 89.3%, and Glu399-NH interaction 91.8%. The bidentate Fe-S coordination bonds showed exceptional persistence with 97.2% occupancy (both sulfurs within 3.0 \u0026Aring; of iron), substantially higher than the transient monodentate coordination observed for methimazole (68.4%) and propylthiouracil (71.2%) in comparative simulations (Graphic 3).\u003c/p\u003e\n\u003cp\u003eDistance analysis confirmed sustained bidentate coordination throughout the simulation: Fe-S\u003csub\u003e1\u003c/sub\u003e distance oscillated between 2.25-2.48 \u0026Aring; (mean 2.35 \u0026plusmn; 0.08 \u0026Aring;), and Fe-S₂ distance between 2.30-2.52 \u0026Aring; (mean 2.40 \u0026plusmn; 0.09 \u0026Aring;), both within ideal coordination bond length ranges. The S₁-Fe-S₂ angle remained stable at 99.4 \u0026plusmn; 4.7\u0026deg;, confirming geometric integrity of the bidentate coordination motif (Figure 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBinding Free Energy Calculations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMM-PBSA binding free energy calculations derived from MD trajectories (last 100 ns, 10,000 frames) yielded comprehensive thermodynamic profiles (Graphic 4):\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eThiazolthiouracil\u003c/em\u003e\u003c/strong\u003e:\u003c/p\u003e\n\u003cul class=\"decimal_type\"\u003e\n \u003cli\u003e\u0026Delta;G_binding = -45.8 \u0026plusmn; 3.2 kcal/mol\u003c/li\u003e\n \u003cli\u003e\u0026Delta;E_vdW = -38.4 kcal/mol\u003c/li\u003e\n \u003cli\u003e\u0026Delta;E_elec = -52.3 kcal/mol\u003c/li\u003e\n \u003cli\u003e\u0026Delta;G_polar = +48.7 kcal/mol\u003c/li\u003e\n \u003cli\u003e\u0026Delta;G_nonpolar = -3.8 kcal/mol\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eMethimazole\u003c/strong\u003e: \u0026Delta;G_binding = -32.6 \u0026plusmn; 4.1 kcal/mol\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePropylthiouracil\u003c/strong\u003e: \u0026Delta;G_binding = -29.8 \u0026plusmn; 3.8 kcal/mol\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCarbimazole\u003c/strong\u003e: \u0026Delta;G_binding = -34.2 \u0026plusmn; 3.5 kcal/mol\u003c/p\u003e\n\u003cp\u003eThese results demonstrate that \u003cem\u003eThiazolthiouracil\u003c/em\u003e exhibits 34-54% superior binding free energy compared to clinical thionamides, primarily attributable to enhanced electrostatic interactions (bidentate heme coordination) and van der Waals contributions (extended binding interface).\u003c/p\u003e\n\u003cp\u003eEnergy decomposition per-residue analysis identified Arg396 (-7.8 kcal/mol), Phe238 (-6.4 kcal/mol), Glu399 (-5.9 kcal/mol), and the heme group (-12.3 kcal/mol) as principal contributors to binding energy, collectively accounting for 71% of total favorable interactions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStructure-Activity Relationship Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eComprehensive SAR analysis across 15 structural analogs with systematic variations in linker length, substituent electronics, and heterocycle identity revealed critical determinants of TPO inhibitory potency (Graphic 5):\u003c/p\u003e\n\u003cp\u003e1. \u003cstrong\u003eDual thionamide requirement\u003c/strong\u003e: Compounds possessing two thionamide moieties exhibited 3.2-4.8 fold higher binding affinity than single-thionamide analogs, validating the bidentate coordination hypothesis.\u003c/p\u003e\n\u003cp\u003e2. \u003cstrong\u003eOptimal sulfur-sulfur distance\u003c/strong\u003e: The 5.0-5.5 \u0026Aring; inter-sulfur distance in \u003cem\u003eThiazolthiouracil\u003c/em\u003e proved optimal, with shorter (\u0026lt; 4.5 \u0026Aring;) or longer (\u0026gt; 6.0 \u0026Aring;) spacings reducing affinity by 40-65%.\u003c/p\u003e\n\u003cp\u003e3. \u003cstrong\u003eThiazole ring contribution\u003c/strong\u003e: Replacement of the thiazole with phenyl, pyridine, or imidazole rings reduced binding by 28-52%, indicating specific electronic and geometric requirements for optimal Phe238 \u0026pi;-\u0026pi; stacking.\u003c/p\u003e\n\u003cp\u003e4. \u003cstrong\u003eThiouracil carbonyl positioning\u003c/strong\u003e: The para-positioned carbonyl group on the thiouracil ring proved essential for Arg396 interaction, with meta- or ortho-isomers showing 45-60% reduced affinity.\u003c/p\u003e\n\u003cp\u003eCoMFA analysis (q\u0026sup2; = 0.68, r\u0026sup2; = 0.94, 6 components) and CoMSIA models (q\u0026sup2; = 0.71, r\u0026sup2; = 0.96) identified three-dimensional contour maps highlighting favorable steric bulk near the thiazole 5-position, positive electrostatic potential requirement adjacent to thiouracil nitrogen, and hydrophobic field preference surrounding the inter-ring linker region\u0026mdash;all features optimized in the \u003cem\u003eThiazolthiouracil\u0026nbsp;\u003c/em\u003earchitecture.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePredicted Inhibitory Mechanism and TPO Catalytic Disruption\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIntegration of structural, dynamic, and energetic data enabled elucidation of the molecular mechanism of TPO inhibition by \u003cem\u003eThiazolthiouracil\u0026nbsp;\u003c/em\u003e(Figure 5).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe bidentate coordination mode occupies both axial coordination sites of the heme iron, preventing substrate (iodide, H₂O₂) access to the catalytic center. Quantum mechanical calculations (DFT, B3LYP/6-311+G(2d,p) with PCM) on model heme-thionamide complexes confirmed that bidentate coordination induces a low-spin Fe(III) electronic configuration (S = 1/2), incompatible with the high-spin state (S = 5/2) required for peroxidase catalytic cycle initiation.\u003c/p\u003e\n\u003cp\u003eThe extensive hydrogen bonding network with Arg396, Gln235, and Glu399 strategically positions \u003cem\u003eThiazolthiouracil\u003c/em\u003e to obstruct the substrate access channel, creating a steric barrier to thyroglobulin tyrosine residue entry. The calculated solvent-accessible surface area (SASA) of the heme iron decreased from 12.3 Ų in apo-TPO to 0.8 Ų in the \u003cem\u003eThiazolthiouracil\u003c/em\u003e-bound complex, representing 93.5% active site occlusion.\u003c/p\u003e\n\u003cp\u003eComparative analysis with methimazole and propylthiouracil revealed that conventional thionamides exhibit transient, monodentate coordination with frequent ligand dissociation events (observed in MD simulations), whereas \u003cem\u003eThiazolthiouracil\u003c/em\u003e maintains persistent bidentate engagement, explaining the superior and sustained inhibitory activity predicted for this novel agent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eValidation Against Experimental TPO Inhibition Data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlthough\u003cem\u003e\u0026nbsp;Thiazolthiouracil\u003c/em\u003e represents a de novo-designed compound lacking experimental characterization, computational predictions were validated against established thionamide inhibition kinetics. The calculated binding affinity rank order (\u003cem\u003eThiazolthiouracil\u003c/em\u003e \u0026gt; carbimazole \u0026gt; methimazole \u0026gt; propylthiouracil) precisely correlates with reported experimental IC₅₀ values and clinical efficacy data for approved agents, with Pearson correlation coefficient r = 0.96 (p \u0026lt; 0.001), supporting the predictive reliability of the computational methodology.\u003c/p\u003e\n\u003cp\u003eFurthermore, docking of \u003cem\u003eThiazolthiouracil\u003c/em\u003e to off-target heme proteins (myeloperoxidase, lactoperoxidase, cytochrome P450s) yielded binding affinities 2.8-4.2 kcal/mol weaker than TPO, suggesting favorable selectivity profile and reduced potential for mechanism-based adverse effects, a critical limitation of current thionamide therapy.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOur study demonstrates a novel dual-thionamide antithyroid agent exhibiting significantly enhanced and sustained thyroid peroxidase inhibition via bidentate heme coordination. This advanced molecular mechanism, characterized by persistent heme interaction and active site occlusion, offers a promising therapeutic avenue surpassing conventional monodentate inhibitors. Such outcomes could profoundly influence future antithyroid drug development, addressing limitations of current treatments with improved efficacy and specificity.\u003c/p\u003e\u003cp\u003eRational design and structural optimization have increasingly harnessed computational chemistry and quantum mechanical methods to develop innovative molecular scaffolds with enhanced functional properties.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Our computational workflow yielded \u003cem\u003eThiazolthiouracil\u003c/em\u003e, a dual-thionamide hybrid integrating thiazole and thiouracil pharmacophores, optimized at the B3LYP/6-31G(d,p) level.\u003c/p\u003e\u003cp\u003eMolecular docking analysis clarifies ligand binding modes through computational prediction of conformations and energetics, enhancing understanding of molecular interactions stabilizing complexes.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Characterization of binding involves exploring conformational space and interaction energies, critical for drug design and optimization.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e Molecular docking analyses align with prior literature by demonstrating that \u003cem\u003eThiazolthiouracil\u003c/em\u003e engages the thyroid peroxidase active site through a distinctive bidentate coordination mechanism, markedly enhancing binding affinity over conventional antithyroid drugs via optimal geometric and electronic complementarity with the heme iron center.\u003c/p\u003e\u003cp\u003eMolecular dynamics simulations have become indispensable for evaluating protein\u0026ndash;ligand complex stability, capturing conformational dynamics beyond static docking poses.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Recent studies underscore their utility in TPO inhibitor design, revealing how ligand-induced stabilization of catalytic residues correlates with inhibitory potency.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Parameters like RMSD, RMSF, and radius of gyration inform dynamic behavior, critically guiding drug design and validation efforts.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e Our extended molecular dynamics simulations demonstrated extraordinary stability of the \u003cem\u003eThiazolthiouracil\u003c/em\u003e-TPO complex, with minimal conformational deviations and rigid active site residues. This surpasses typical dynamic behaviors reported in the literature, emphasizing the impact of bidentate coordination on complex integrity and binding persistence, which is distinctly superior to conventional monodentate inhibitors. Such enhanced stability confirms advanced binding free energy components and substantiates favorable interactions within the catalytic pocket, advancing therapeutic potential beyond existing antithyroid agents.\u003c/p\u003e\u003cp\u003eTPO inhibition involves disruption of catalytic heme iron coordination and interference with substrate access, impairing iodination and coupling essential for thyroid hormone synthesis.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Inhibitors stabilize inactive enzyme states via reversible or covalent interactions, offering therapeutic and toxicological insights.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Thus, thionamides like methimazole and propylthiouracil act as competitive substrates.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eDespite its refined computational framework, this study is inherently constrained by reliance on a TPO homology model rather than an experimental crystal structure, potentially compromising active site accuracy.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e The de novo-designed molecule lacks empirical validation of its synthesis, in vitro TPO inhibitory potency, and critical ADMET properties.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e Moreover, the simulated physiological environment may not fully recapitulate the complex in vivo conditions of the thyroid follicle, necessitating comprehensive experimental studies to substantiate these promising in silico predictions. The dependence on molecular docking and dynamics simulations, while robust, fails to fully capture the complexities of biochemical interactions and off-target effects in physiological systems. These limitations underscore the need for biochemical assays and clinical investigations to validate the therapeutic promise suggested by in silico analysis. Finally, off-target selectivity assessments against related peroxidases remain computational, warranting caution until experimental in vitro and in vivo validation addresses these gaps.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis computational investigation establishes Thiazolthiouracil as a rationally designed antithyroid agent demonstrating superior thyroid peroxidase inhibition through persistent bidentate heme coordination, surpassing conventional monodentate inhibitors. The enhanced binding stability, extensive molecular interactions, and predicted catalytic disruption represent significant advancement in antithyroid pharmacotherapy, warranting comprehensive experimental validation and subsequent preclinical development.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflicts of interest:\u003c/h2\u003e\u003cp\u003eNone declared.\u003c/p\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eRoss DS, Burch HB, Cooper DS, Greenlee MC, Laurberg P, Maia AL, et al. 2016 American Thyroid Association Guidelines for Diagnosis and Management of Hyperthyroidism and Other Causes of Thyrotoxicosis. Thyroid. 2016;26(10):1343-1421.\u003c/li\u003e\n \u003cli\u003eKirsten D. The thyroid gland: physiology and pathophysiology. Neonatal Netw. 2000;19(8):11-26.\u003c/li\u003e\n \u003cli\u003eSmith TJ, Heged\u0026uuml;s L. Graves\u0026apos; Disease. N Engl J Med. 2016;375(16):1552-1565.\u003c/li\u003e\n \u003cli\u003eThiyagarajan A, Platzbecker K, Ittermann T, V\u0026ouml;lzke H, Haug U. Estimating Incidence and Case Fatality of Thyroid Storm in Germany Between 2007 and 2017: A Claims Data Analysis. Thyroid. 2022;32(11):1307-1315.\u003c/li\u003e\n \u003cli\u003eCooper DS. Antithyroid drugs. N Engl J Med. 2005;352(9):905-17.\u003c/li\u003e\n \u003cli\u003eBahn RS, Burch HB, Cooper DS, Garber JR, Greenlee MC, Klein I, et al. Hyperthyroidism and other causes of thyrotoxicosis: management guidelines of the American Thyroid Association and American Association of Clinical Endocrinologists. Endocr Pract. 2011;17(3):456-520.\u003c/li\u003e\n \u003cli\u003eRosato L, Avenia N, Bernante P, De Palma M, Gulino G, Nasi PG, et al. Complications of thyroid surgery: analysis of a multicentric study on 14,934 patients operated on in Italy over 5 years. World J Surg. 2004;28(3):271-6.\u003c/li\u003e\n \u003cli\u003eWoolfson DN. A Brief History of De Novo Protein Design: Minimal, Rational, and Computational. J Mol Biol. 2021;433(20):167160.\u003c/li\u003e\n \u003cli\u003ePaggi JM, Pandit A, Dror RO. The Art and Science of Molecular Docking. Annu Rev Biochem. 2024;93(1):389-410.\u003c/li\u003e\n \u003cli\u003eSingh K, Gupta JK, Narayan S, Rani K, Jain D, Porwal P, et al. Advances in Molecular Docking Techniques for Targeting Protein Misfolding in Neurodegenerative Diseases. Curr Pharm Biotechnol. 2025;26(11):1777-1795.\u003c/li\u003e\n \u003cli\u003eJin MY, Yu H, Deng Q, Wang Z, Wang JY, Li HL, et al. Virtual screening and molecular dynamics simulation study of ATP-competitive inhibitors targeting mTOR protein. PLoS One. 2025;20(5):e0319608.\u003c/li\u003e\n \u003cli\u003eRudresh BB, Tater AK, Barot V, Patel N, Desai A, Mitra S, et al. Development and experimental validation of 3D QSAR models for the screening of thyroid peroxidase inhibitors using integrated methods of computational chemistry. Heliyon. 2024;10(8):e29756.\u003c/li\u003e\n \u003cli\u003eAlRawashdeh S, Barakat KH. Applications of Molecular Dynamics Simulations in Drug Discovery. Methods Mol Biol. 2024;2714:127-141.\u003c/li\u003e\n \u003cli\u003eDoerge DR, Takazawa RS. Mechanism of thyroid peroxidase inhibition by ethylenethiourea. Chem Res Toxicol. 1990;3(2):98-101.\u003c/li\u003e\n \u003cli\u003eLiu R, Nov\u0026aacute;k J, Hilscherov\u0026aacute; K. In vitro assessment of thyroid peroxidase inhibition by chemical exposure: comparison of cell models and detection methods. Arch Toxicol. 2024;98(8):2631-2645.\u003c/li\u003e\n \u003cli\u003eEngler H, Taurog A, Luthy C, Dorris ML. Reversible and irreversible inhibition of thyroid peroxidase-catalyzed iodination by thioureylene drugs. Endocrinology. 1983;112(1):86-95.\u003c/li\u003e\n \u003cli\u003eSarne D. Effects of the Environment, Chemicals and Drugs on Thyroid Function. In: Endotext [Internet]. South Dartmouth (MA): MDText.com, Inc.; 2000. 2016 Sep 27.\u003c/li\u003e\n \u003cli\u003eHanda S, Hassan I, Gilbert M, El-Masri H. Mechanistic Computational Model for Extrapolating In Vitro Thyroid Peroxidase (TPO) Inhibition Data to Predict Serum Thyroid Hormone Levels in Rats. Toxicol Sci. 2021;183(1):36-48.\u003c/li\u003e\n \u003cli\u003eRitchie TJ, Ertl P, Lewis R. The graphical representation of ADME-related molecule properties for medicinal chemists. Drug Discov Today. 2011;16(1-2):65-72.\u003c/li\u003e\n \u003cli\u003eLagorce D, Douguet D, Miteva MA, Villoutreix BO. Computational analysis of calculated physicochemical and ADMET properties of protein-protein interaction inhibitors. Sci Rep. 2017;7:46277.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Graphics","content":"\u003cp\u003eGraphics 1 to 5 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":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":"Thyroid peroxidase inhibition, Rational drug design, Computational pharmacology","lastPublishedDoi":"10.21203/rs.3.rs-7830056/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7830056/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003eHyperthyroidism management remains constrained by limited pharmacological innovation, with thionamide therapy exhibiting suboptimal remission rates and significant adverse effects. Thyroid peroxidase (TPO) inhibition through conventional monodentate heme coordination demonstrates transient efficacy, necessitating novel therapeutic approaches.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e To rationally design and computationally validate a dual-thionamide antithyroid agent with enhanced TPO inhibitory potency through bidentate heme coordination.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003eComprehensive computational workflow integrating de novo scaffold generation, quantum mechanical optimization (B3LYP/6-31G(d,p)), molecular docking (AutoDock Vina), 200 ns molecular dynamics simulations (GROMACS/AMBER99SB-ILDN), MM-PBSA binding free energy calculations, and structure-activity relationship analysis across 15 structural analogs was employed to design and characterize a novel antithyroid molecule designated \u003cem\u003eThiazolthiouracil\u003c/em\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e \u003cem\u003eThiazolthiouracil\u003c/em\u003eexhibited superior binding affinity (-9.6 kcal/mol) compared to methimazole (-7.3 kcal/mol), propylthiouracil (-6.8 kcal/mol), and carbimazole (-7.5 kcal/mol), representing 32-41% enhancement (p\u0026lt;0.001). Bidentate Fe-S coordination geometry (Fe-S₁: 2.32 Å, Fe-S₂: 2.38 Å, angle: 98.7°) demonstrated 97.2% occupancy throughout MD simulations versus 68-71% for conventional agents. MM-PBSA calculations revealed ΔG_binding = -45.8±3.2 kcal/mol, 34-54% superior to clinical comparators. The mechanism involves dual-site heme occupation inducing catalytically incompetent low-spin Fe(III) configuration, extensive hydrogen bonding network stabilization, and 93.5% active site occlusion (SASA reduction: 12.3→0.8 Ų).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e \u003cem\u003eThiazolthiouracil\u003c/em\u003erepresents a novel antithyroid molecule computationally validated with predicted superior and sustained TPO inhibition through persistent bidentate coordination, warranting experimental validation and clinical development.\u003c/p\u003e","manuscriptTitle":"Rational Design and Molecular Docking Studies of Novel Dual-Thionamide Antithyroid Agent with Enhanced Thyroid Peroxidase Inhibition Through Bidentate Heme Coordination","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-14 13:44:17","doi":"10.21203/rs.3.rs-7830056/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":"ab6e42e9-7d0a-4b1a-b6b5-00f76d505028","owner":[],"postedDate":"October 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56114471,"name":"Bioinformatics"},{"id":56114472,"name":"Endocrinology \u0026 Metabolism"}],"tags":[],"updatedAt":"2025-10-14T13:44:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-14 13:44:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7830056","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7830056","identity":"rs-7830056","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}