Search Results (104)

Carnitine plays an essential role in fatty acid metabolism, and its biosynthesis is tightly regulated by γ-butyrobetaine hydroxylase (BBOX), an Fe(II)/α-ketoglutarate-dependent dioxygenase. BBOX is the target of mildronate (THP), a clinically used drug for treating ischemic heart diseases. However, the detailed mechanisms of BBOX-catalyzed hydroxylation and the atypical oxidative rearrangement underlying THP inhibition remain elusive. In this study, we employed combined quantum mechanics/molecular mechanics (QM/MM) methods to systematically elucidate these mechanisms at the atomic level. Our calculations reveal that the hydroxylation of γBB proceeds via a classical three-step mechanism in the quintet state, with hydrogen atom abstraction as the rate-determining step. Remarkably, substitution of the C4 methylene group in γBB with an amino group in THP redirects the reaction pathway, as the lone pair electrons on the adjacent nitrogen atom render N-N bond cleavage kinetically favored over hydroxyl rebound, thereby blocking carnitine synthesis. Through systematic evaluation of possible rearrangement pathways, we rule out the previously proposed direct 1,2-H migration and suggest a revised mechanism featuring imine-mediated hydrogen transfer, hydroxyl rebound preceding C-C bond formation, and final radical coupling. This work provides a detailed atomic-level understanding of both the catalytic and inhibitory mechanisms of BBOX, revealing how substrate electronic effects dictate reaction outcomes. The elucidated mechanistic insights offer a theoretical foundation for understanding the catalytic versatility of the αKG-dependent dioxygenase family and provide valuable guidance for the rational design of novel BBOX inhibitors. Full article

Organic mixed ionic–electronic conductors (OMIECs) are pivotal for bioelectronics; however, the microscopic origins of doping-dependent charge transport remain elusive. In this study, we established a multi-scale computational framework to quantify the distinct intramolecular electronic coupling ($H_{ab}$) distributions in systems with 25% and 75% doping levels. Our protocol employs automated quantum chemical calculations to exhaustively identify intrinsic local minima, ensuring thermodynamically stable initial conformations. Subsequent Molecular Dynamics (MD) simulations characterize the equilibration timescales and counter-ion dispersion behaviors. The simulation results reveal that the 75% doped system exhibits significantly stronger counter-ion confinement and a distinct electrostatic landscape compared to the 25% system. Finally, hybrid QM/MM calculations integrated with Constrained Density Functional Theory (CDFT) were utilized to evaluate $H_{ab}$ within these specific environments. The computed coupling distributions show a clear correlation with local electrostatic fluctuations induced by differing counter-ion arrangements. These findings indicate that doping-induced environmental disorder is a critical factor modulating intramolecular transport efficiency, providing a theoretical basis for optimizing OMIEC performance through electrostatic engineering. Full article

The interaction between water and metallic interfaces is crucial in many fields, and accurate modeling requires good parametrizations using reference data. In classical molecular dynamics (MD), an important part of this interaction is described using the Lennard–Jones (LJ) potential. However, previously reported LJ parameters are not always optimal for capturing the metal/water interactions observed in ab initio descriptions such as density functional theory (DFT). Therefore, well-tailored LJ parameters are necessary to improve the description of water structuring metals in classical MD. The usual route for obtaining LJ parameters involves energetic analysis, where the energies of various structures are obtained via DFT calculations and then matched with the energies obtained using the LJ potentials by varying the sigma/epsilon parameters. Here, we show a different approach to fit LJ parameters for metal/water interactions, based on structural analysis. We report several classical MD simulations for gold/water, varying the sigma/epsilon parameters, comparing the resulting water structuring with that obtained using DFT. Additionally, we test these parameters in quantum mechanics/molecular mechanics (QM/MM) MD simulations, where electrostatic interactions are enabled. Our results demonstrate that the proposed approach can improve the LJ parameters reported in the literature and potentially develop parameters for more complex systems where the water structure above metallic surfaces plays a significant role. Finally, within this proposed approach, the water density profile obtained in hybrid QM/MM calculations, where water is treated as MM at a substantially reduced cost, closely matches the description it would have if treated as QM. Full article

Two structurally tunable (propyl-3-ol)triphenyltin(IV) (Ph₃SnL₁) and (butyl-4-ol)triphenyltin(IV) (Ph₃SnL₂) compounds were investigated at the human serum transferrin (Tf) molecular interface to resolve how ligand architecture and protein metallation modulate organotin(IV) biocompound stability and lobe-selective binding. Steady-state fluorescence spectroscopy revealed efficient quenching of native Tf emission (λ_ex = 280 nm, 296–310 K, pH 7.4) without significant spectral displacement, indicating the predominant formation of non-fluorescent ground-state complexes. Calculated bimolecular quenching constants (K_q ~10¹² M⁻¹ s⁻¹) exceeded the diffusion-controlled aqueous limit, ruling out a collisional dynamic quenching mechanism and confirming static complexation as the principal origin of fluorescence suppression. Double-log binding analysis revealed moderate affinity (K_a ~10²–10³ M⁻¹) and an approximately single dominant binding event per protein (n ≈ 0.65–0.90). Temperature-dependent van’t Hoff evaluation yielded positive ΔH° and ΔS° values, supporting a spontaneous, entropy-favored association process largely governed by hydrophobic and dispersion-type contributions, consistent with lipophilic organotin(IV) scaffold accommodation. Iron (Fe³⁺) loading of Tf markedly enhanced ligand engagement, especially for Ph₃SnL₁, evidencing that metallation-induced lobe closure reshapes pocket accessibility and local polarity relevant for organotin(IV) binding presentation rather than simply strengthening empirical docking scores. Molecular docking localized the most stable Ph₃SnL₂ poses in the sterically confined, rigid C-lobe, while Ph₃SnL₁ preferentially penetrated the more adaptive N-lobe. ONIOM QM/MM refinement of docking poses confirmed strong interfacial stabilization (ΔE_int ≈ –38 to –62 kcal mol⁻¹) and clarified charge–packing interplay without invoking frontier orbital analysis. The results map multiscale structure–interaction relationships defining lobe preference and complex stability at the transferrin interface. Full article

The zoonotic potential of bat coronaviruses, especially HKU5, is a significant issue because of their capacity to utilize human angiotensin-converting enzyme 2 (ACE2) as a receptor for cellular entry. This study offers structural insights into the binding kinetics of HKU5 (Bat Merbecovirus HKU5) receptor-binding domain (RBD) spike protein with human ACE2 through a multiscale computational method. This study employed structural modeling, 300-nanosecond (ns) molecular dynamics (MD) simulations, alanine-scanning mutagenesis, and computational peptide design to investigate ACE2 recognition by the HKU5 RBD and its interactions with peptides. The root mean square deviation (RMSD) investigation of HKU5–ACE2 complexes indicated that HKU5 exhibited greater flexibility than SARS-CoV-2, with RMSD values reaching a maximum of 1.2 nm. Free energy analysis, Molecular Mechanics/Generalized Born Surface Area (MM/GBSA), indicated a more robust binding affinity of HKU5 to ACE2 (ΔG_Total = −21.61 kcal/mol) in contrast to SARS-CoV-2 (ΔG_Total = −5.82 kcal/mol), implying that HKU5 binding with ACE2 had higher efficiency. Additionally, a peptide was designed from the ACE2 interface, resulting in the development of 380 single-site mutants by mutational alterations. The four most promising mutant peptides were selected for 300-nanosecond (ns) MD simulations, subsequently undergoing quantum chemical calculations (DFT) to evaluate their electronic characteristics. MM/GBSA of −37.83 kcal/mol indicated that mutant-1 exhibits the most favorable binding with HKU5, hence potentially inhibiting ACE2 interaction. Mutant-1 formed hydrogen bonds involving Glu74, Ser202, Ser204, and Asn152 residues of HKU5. Finally, QM/MM calculations on the peptide–HKU5 complexes showed the most favorable ΔE_interaction of −170.47 (Hartree) for mutant-1 peptide. These findings offer a thorough comprehension of receptor-binding dynamics and are crucial for evaluating the zoonotic risk associated with HKU5-CoV and guiding the design of receptor-targeted antiviral treatments. Full article

Human carboxylesterases (CES) are enzymes that play a central role in the metabolism and biotransformation of diverse endogenous substances and xenobiotics. The two most relevant isoforms, CES1 and CES2, are crucial in clinical pharmacotherapy as they catalyze the hydrolysis of numerous approved drugs and prodrugs. Elucidating the structural basis of CES isoform substrate specificity is essential not only for understanding and anticipating the biological fate of administered drugs, but also for designing prodrugs with optimized site-specific bioactivation. Additionally, this knowledge is also important for the design of biomedically useful molecules such as subtype-targeted CES inhibitors and fluorescent probes. In this context, both experimental and computational methodologies have been used to explore the mechanistic and thermodynamic properties of CES-mediated catalysis. Experimental designs commonly employ recombinant CES or human tissue microsomes as enzyme sources, utilizing quantification methods such as spectrophotometry (UV and fluorescence) and mass spectrometry. Computational approaches fall into two categories: (1) modeling substrate: CES recognition and affinity (molecular docking, molecular dynamics simulation, and free-energy binding calculations), and (2) modeling substrate: CES reaction coordinates (hybrid QM/MM simulations). While experimental and theoretical approaches are highly synergistic in studying the catalytic properties of CES subtypes, they represent distinct technical and scientific fields. This review aims to provide an integrated discussion of the key concepts and the interplay between the most commonly used wet-lab and dry-lab strategies for investigating CES catalytic activity. We hope this report will serve as a concise resource for researchers exploring CES isoform specificity, enabling them to effectively utilize both experimental and computational methods. Full article

An important microbial enzymatic pathway in the gut is choline/phosphatidylcholine degradation in which intestinal microbes utilize dietary choline to produce TMA via the choline utilization cluster polypeptide C (CutC) enzyme, a member of the glycyl radical enzyme family. Our goal in this theoretical work was to study the reaction mechanism and elucidate how the enzyme environment (steric and electronic) modulates the reaction path. Dissecting the effect of the enzyme environment on the reaction mechanism and shedding light on how steric and electronic effects affect the reaction path is an insightful and significant contribution of this work. Our theoretical results suggest that the final product of enzyme catalysis might be carbinolamine and not TMA and acetaldehyde. In addition, we found out that Glu₄₉₁ plays the role of a base in this reaction (a disputed fact) by temporarily abstracting a proton from the hydroxylic group of choline sometime during the reaction—with the proton transfer being critical for the reaction to proceed to completion. We also found that the choice of computational protocol not only alters the reaction energetics but can change the reaction path by creating new intermediates and transition states or eliminating existing ones. Full article

Among many metal ions in biological systems, iron plays a fundamental role. Transferrins are iron-binding glycoproteins responsible for transporting Fe³⁺ in vertebrate blood. Neisseria meningitidis, a Gram-negative pathogen causing meningitis, relies on iron for survival and acquires it from human transferrin (hTf) using two surface proteins, TbpA and TbpB. These proteins interact with hTf to form a ternary TbpA–TbpB–hTf complex, enabling iron capture from the host. The absence of an experimental crystal structure for this complex has hindered computational studies, a detailed understanding of Fe³⁺ dissociation, and designing efficient therapeutics. This study presents the first computational model of the ternary complex, its validation, and molecular dynamics simulations. Structural analyses revealed key electrostatic interactions regulating Fe³⁺ coordination and essential contact regions between proteins. The role of Lys359 from TbpA was investigated via QM/MM calculations by evaluating Fe³⁺ binding energies of isolated hTf, the ternary complex, and Lys359Ala, Lys359Arg, Lys359Asp mutant models. Results revealed that the proton transfer from Lys359 leads to disruption of Tyr517–Fe³⁺ coordination, facilitating iron transfer to the bacterial system. Natural bond orbital analysis confirmed this mechanism. The findings provide new molecular insight into N. meningitidis iron acquisition and identify Lys359 as a potential target for covalent inhibitor design, guiding the development of novel therapeutics against meningococcal infection. Full article

This study employed an integrated computational approach to discover novel nucleoprotein (NP) inhibitors for influenza A virus (IAV). Beginning with virtual screening of over 10 million compounds using Schrödinger’s Glide module (HTVS, SP, XP docking), the workflow identified promising candidates with favorable binding energies. Subsequent molecular mechanics/generalized born surface area (MM-GBSA) calculations and 100 ns molecular dynamics (MD) simulations prioritized 16 compounds for experimental validation. Surface plasmon resonance (SPR) assays revealed that compounds 8, 13, and 14 demonstrated superior target engagement, showing equilibrium dissociation constants (K_D) of 7.85 × 10⁻⁵ M, 3.82 × 10⁻⁵ M, and 6.97 × 10⁻⁵ M, respectively. Molecular dynamics, alanine scanning mutagenesis, and quantum mechanics/molecular mechanics (QM/MM) analysis were conducted to analyze the binding modes, providing a reference for the design of subsequent compounds. These findings validate the efficacy of structure-based virtual screening in identifying high-affinity NP inhibitors and provide insights for the development of broad-spectrum anti-influenza therapeutics. Full article

Methylation reactions catalyzed by S-adenosylmethionine (SAM)-dependent methyltransferases are essential to numerous biological functions, including gene expression regulation, epigenetic modifications, and biosynthesis of natural products. Dysregulation of these enzymes is associated with diseases, including cancer and neurodevelopmental disorders, making them attractive drug targets. This review explores the contribution of computational methods, particularly quantum chemical calculations and molecular dynamics (MD) simulations, in elucidating the mechanisms of SAM-dependent methyltransferases. These techniques enable detailed characterization of transition states and reaction pathways, often inaccessible by experimental methods. The review discusses molecular modeling approaches such as the quantum chemical cluster approach (QM-cluster) and hybrid QM/MM methods, emphasizing their applications in studying methyl group transfer, substrate specificity, and the roles of water molecules and metal ions in catalysis. Additionally, dynamic aspects of enzyme function are addressed using classical MD and QM/MM MD simulations. Case studies demonstrate how computational predictions align with experimental data and enable rational design of selective inhibitors and engineered enzymes with altered specificity. Overall, computational chemistry offers a powerful, atomistic view of SAM-dependent methyltransferases, not only complementing experimental studies but also providing a foundation for the design of future experiments in this field. Full article

Background/Objectives: This study identifies novel dihydroorotate dehydrogenase (DHODH) inhibitors exhibiting potent broad-spectrum antiviral agents, particularly against influenza A virus (A/PR/8/34(H1N1)) and SARS-CoV-2. Methods: Structure-based virtual screening of 1.6 million compounds (ChemDiv and TargetMol databases) yielded 10 candidates, with compounds 6, 9, and 10 demonstrating significant anti-influenza activity (IC₅₀ = 4.85 ± 0.58, 7.35 ± 1.65, and 1.75 ± 0.28 μM, respectively). Building on these, molecular hybridization principles and scaffold hopping principles were applied to design and synthesize six novel compounds (11–16) through cyclization, coupling, and carboxylate deprotection. Prior to subsequent biological assays, the molecular structures of each compound were elucidated by NMR spectroscopy and MS. Their antiviral activities were subsequently assessed against both influenza virus and SARS-CoV-2. The compound 11, demonstrating the most potent antiviral activity, was further subjected to surface plasmon resonance (SPR) analysis to assess its binding affinity for human DHODH. Results: Compound 11 emerged as the most potent DHODH inhibitor (K_D = 6.06 μM), exhibiting superior broad-spectrum antiviral activities (IC₅₀ = 0.85 ± 0.05 μM, A/PR/8/34(H1N1); IC₅₀ = 3.60 ± 0.67 μM, SARS-CoV-2) to the reported DHODH inhibitor (Teriflunomide, IC₅₀ = 35.02 ± 3.33 μM, A/PR/8/34(H1N1); IC₅₀ = 26.06 ± 4.32 μM, SARS-CoV-2). Mechanistic evaluations via 100 ns MD simulations and QM/MM calculations revealed stable binding interactions, particularly hydrogen bonds with GLN47 and ARG136, while alanine scanning mutagenesis confirmed these residues’ critical roles in binding stability. Conclusions: This work identifies compound 11 as a potent broad-spectrum antiviral compound, offering a promising strategy for broad-spectrum antiviral therapy against RNA viruses by depleting pyrimidine pools essential for viral replication. Full article

Quantum mechanics (QM) revolutionizes drug discovery by providing precise molecular insights unattainable with classical methods. This review explores QM’s role in computational drug design, detailing key methods like density functional theory (DFT), Hartree–Fock (HF), quantum mechanics/molecular mechanics (QM/MM), and fragment molecular orbital (FMO). These methods model electronic structures, binding affinities, and reaction mechanisms, enhancing structure-based and fragment-based drug design. This article highlights the applicability of QM to various drug classes, including small-molecule kinase inhibitors, metalloenzyme inhibitors, covalent inhibitors, and fragment-based leads. Quantum computing’s potential to accelerate quantum mechanical (QM) calculations is discussed alongside novel applications in biological drugs (e.g., gene therapies, monoclonal antibodies, biosimilars), protein–receptor dynamics, and new therapeutic indications. A molecular dynamics (MD) simulation exercise is included to teach QM/MM applications. Future projections for 2030–2035 emphasize QM’s transformative impact on personalized medicine and undruggable targets. The qualifications and tools required for researchers, including advanced degrees, programming skills, and software such as Gaussian and Qiskit, are outlined, along with sources for training and resources. Specific publications on quantum mechanics (QM) in drug discovery relevant to QM and molecular dynamics (MD) studies are incorporated. Challenges, such as computational cost and expertise requirements, are addressed, offering a roadmap for educators and researchers to leverage quantum mechanics (QM) and molecular dynamics (MD) in drug discovery. Full article

Leishmaniasis is a neglected tropical disease caused by Leishmania sp. The therapeutic arsenal is reduced and limited. In this context, acridine derivatives present themselves as promising leishmanicidal compounds. This paper involved synthesizing and evaluating the antileishmanial and immunomodulatory potential of spiro-acridine derivatives. Six spiro-acridine derivatives were obtained through nucleophilic substitution reactions between the acetohydrazide/acetamide intermediates and 9-carbaldehydeacridine, followed by spontaneous cyclization. IR, NMR, and HRMS confirmed the structures. These were analyzed in vitro against L. infantum and L. amazonensis to determine anti-promastigote, anti-amastigote, and cytotoxicity effects. Immunomodulatory activity was evaluated using CBA, DCF-DA, and DAF-FM diacetate. In silico evaluation included molecular docking and dynamics. The spiro-acridines showed a wide range of anti-promastigote activities (IC₅₀ = 0.73–234.95 µM) and non-toxicity to red blood cells. AMTAC-02 and ACMD-03 demonstrated satisfactory anti-amastigote effect (IC₅₀ = 10.47–13.50 µM), low toxicity to macrophages (CC₅₀ = 27.22–569.50 µM), and cytokine and reactive species modulation. Molecular docking proposed cysteine protease B of L. amazonensis as a target, and molecular dynamics analysis highlighted the complex’s stability using RMSD, R_g, SASA, DCCM, PCA, and MM-PBSA (ΔG = −65.225 kJ/mol). Furthermore, QM-MM calculation provided the best energy for ACMD-03 (−199.30 au). Hence, AMTAC-02 and ACMD-03 demonstrated antileishmanial potential, making them promising entities for the development of leishmanicidal drug candidates. Full article

QM/MM simulations were performed to investigate the ionizations of four DNA nucleotides in the explicit solution. The vertical ionization energies (VIEs) and adiabatic ionization energies (AIEs) were averaged over 40 snapshots to calculate mean values. The QM/MM VIEs (6.92–7.63 eV) were ~0.70 eV lower than those of the corresponding nucleosides. This suggests that the water environment cannot fully screen the effect of the phosphate group on ionizations. The result is inconsistent with computations using implicit solvent models. The distributions of holes in both adiabatic and vertical ionizations suggest that bulk-water polarization drives the hole transfer from first-shell water to nucleobases, resulting in increases in VIEs and AIEs. Moreover, we computed the released energies in the structural relaxations after ionizations. The results indicate that the minimal energies are released by the structural relaxations of both the bulk-water and the QM region. The redistributions of the electron density on first-shell water molecules and nucleobases produce the primary contributions to released energies. Full article

Here, we demonstrate through AFM imaging and CD spectroscopy that the binding of silver ions (Ag⁺) to poly(dGdC), a double-stranded (ds) DNA composed of two identical repeating strands, at a stoichiometry of one Ag⁺ per GC base pair induces a one-base shift of one strand relative to the other. This results in a ds nucleic acid-Ag⁺ conjugate consisting of alternating CC and GG base pairs coordinated by silver ions. The proposed organization of the conjugate is supported by the results of our Quantum Mechanical (QM) and Molecular Mechanics (MMs) calculations. The reduction of Ag⁺ ions followed by the partial oxidation of silver atoms yields a highly fluorescent conjugate emitting at 720 nm. This fluorescent behavior in conjugates of long, repetitive ds DNA (thousands of base pairs) with silver has never been demonstrated before. We propose that the poly(dGdC)–Ag conjugate functions as a dynamic system, comprising various small clusters embedded within the DNA and interacting with one another through energy transfer. This hypothesis is supported by the results of our QM and MMs calculations. Additionally, these DNA–silver conjugates, comprising silver nanoclusters, may possess conductive properties, making them potential candidates for use as nanowires in nanodevices and nanosensors. Full article