Reactivities of acrylamide warheads toward cysteine targets: a QM/ML approach to covalent inhibitor design.

Covalent inhibition offers many advantages over non-covalent inhibition, but covalent warhead reactivity must be carefully balanced to maintain potency while avoiding unwanted side effects. While warhead reactivities are commonly measured with assays, a computational model to predict warhead reactivities could be useful for several aspects of the covalent inhibitor design process. Studies have shown correlations between covalent warhead reactivities and quantum mechanic (QM) properties that describe important aspects of the covalent reaction mechanism. However, the models from these studies are often linear regression equations and can have limitations associated with their usage. Applications of machine learning (ML) models to predict covalent warhead reactivities with QM descriptors are not extensively seen in the literature. This study uses QM descriptors, calculated at different levels of theory, to train ML models to predict reactivities of covalent acrylamide warheads. The QM/ML models are compared with linear regression models built upon the same QM descriptors and with ML models trained on structure-based features like Morgan fingerprints and RDKit descriptors. Experiments show that the QM/ML models outperform the linear regression models and the structure-based ML models, and literature test sets demonstrate the power of the QM/ML models to predict reactivities of unseen acrylamide warhead scaffolds. Ultimately, these QM/ML models are effective, computationally feasible tools that can expedite the design of new covalent inhibitors.

Computational modelling of supramolecular metallopeptide assemblies.

Among the important questions in supramolecular peptide self-assemblies are their interactions with metallic compounds and ions. In the last decade, intensive efforts have been devoted to understanding the structural properties of these interactions including their dynamical and catalytic impact in natural and de novo systems. Since structural insights from experimental approaches could be particularly challenging, computational chemistry methods are interesting complementary tools. Here, we present the general multiscale strategies we developed and applied for the study of metallopeptide assemblies. These strategies include prediction of metal binding site, docking of metallic moieties, classical and accelerated molecular dynamics and finally QM/MM calculations. The systems of choice for this chapter are, on one side, peptides involved in neurodegenerative diseases and, on the other, de novo fibrillar systems with catalytic properties. Both successes and remaining challenges are highlighted so that the protocol could be apply to other system of this kind.

Cysteine Radical and Glutamate Collaboratively Enable C-H Bond Activation and C-N Bond Cleavage in a Glycyl Radical Enzyme HplG.

Hydroxyprolines are abundant in nature and widely utilized by many living organisms. Isomerization of trans-4-hydroxy-d-proline (t4D-HP) to generate 2-amino-4-ketopentanoate has been found to need a glycyl radical enzyme HplG, which catalyzes the cleavage of the C-N bond, while dehydration of trans-4-hydroxy-l-proline involves a homologous enzyme of HplG. Herein, molecular dynamics simulations and quantum mechanics/molecular mechanics (QM/MM) calculations are employed to understand the reaction mechanism of HplG. Two possible reaction pathways of HplG have been explored to decipher the origin of its chemoselectivity. The QM/MM calculations reveal that the isomerization proceeds via an initial hydrogen shift from the Cγ site of t4D-HP to a catalytic cysteine radical, followed by cleavage of the Cδ-N bond in t4D-HP to form a radical intermediate that captures a hydrogen atom from the cysteine. Activation of the Cδ-H bond in t4D-HP to bring about dehydration of t4D-HP possesses an extremely high energy barrier, thus rendering the dehydration pathway implausible in HplG. On the basis of the current calculations, conserved residue Glu429 plays a pivotal role in the isomerization pathway: the hydrogen bonding between it and t4D-HP weakens the hydroxyalkyl Cγ-Hγ bond, and it acts as a proton acceptor to trigger the cleavage of the C-N bond in t4D-HP. Our current QM/MM calculations rationalize the origin of the experimentally observed chemoselectivity of HplG and propose an H-bond-assisted bond activation strategy in radical-containing enzymes. These findings have general implications on radical-mediated enzymatic catalysis and expand our understanding of how nature wisely and selectively activates the C-H bond to modulate catalytic selectivity.

Effects of the Y432S Cancer-Associated Variant on the Reaction Mechanism of Human DNA Polymerase κ.

Human DNA polymerases are vital for genetic information management. Their function involves catalyzing the synthesis of DNA strands with unparalleled accuracy, which ensures the fidelity and stability of the human genomic blueprint. Several disease-associated mutations and their functional impact on DNA polymerases have been reported. One particular polymerase, human DNA polymerase kappa (Pol κ), has been reported to be susceptible to several cancer-associated mutations. The Y432S mutation in Pol κ, associated with various cancers, is of interest due to its impact on polymerization activity and markedly reduced thermal stability. Here, we have used computational simulations to investigate the functional consequences of the Y432S using classical molecular dynamics (MD) and coupled quantum mechanics/molecular mechanics (QM/MM) methods. Our findings suggest that Y432S induces structural alterations in domains responsible for nucleotide addition and ternary complex stabilization while retaining structural features consistent with possible catalysis in the active site. Calculations of the minimum energy path associated with the reaction mechanism of the wild type (WT) and Y432S Pol κ indicate that, while both enzymes are catalytically competent (in terms of energetics and the active site's geometries), the cancer mutation results in an endoergic reaction and an increase in the catalytic barrier. Interactions with a third magnesium ion and environmental effects on nonbonded interactions, particularly involving key residues, contribute to the kinetic and thermodynamic distinctions between the WT and mutant during the catalytic reaction. The energetics and electronic findings suggest that active site residues favor the catalytic reaction with dCTP3- over dCTP4-.

Application of molecular dynamics-based pharmacophore and machine learning approaches to identify novel Mcl1 inhibitors through drug repurposing and mechanics research.

Myeloid cell leukemia 1 (Mcl1), a critical protein that regulates apoptosis, has been considered as a promising target for antitumor drugs. The conventional pharmacophore screening approach has limitations in conformation sampling and data mining. Here, we offered an innovative solution to identify Mcl1 inhibitors with molecular dynamics-refined pharmacophore and machine learning methods. Considering the safety and druggability of FDA-approved drugs, virtual screening of the database was performed to discover Mcl1 inhibitors, and the hit was subsequently validated via TR-FRET, cytotoxicity, and flow cytometry assays. To reveal the binding characteristics shared by the hit and a typical Mcl1 selective inhibitor, we employed quantum mechanics and molecular mechanics (QM/MM) calculations, umbrella sampling, and metadynamics in this work. The combined studies suggested that fluvastatin had promising cell inhibitory potency and was suitable for further investigation. We believe that this research will shed light on the discovery of novel Mcl1 inhibitors that can be used as a supplemental treatment against leukemia and provide a possible method to improve the accuracy of drug repurposing with limited computational resources while balancing the costs of experimentation well.

First-principles design of heavy-atom-free singlet oxygen photosensitizers for photodynamic therapy.

In photodynamic therapy (PDT) treatment, heavy-atom-free photosensitizers (PSs) are a great source of singlet oxygen photosensitizer. Reactive oxygen species (ROS) are produced by an energy transfer from the lowest energy triplet excited state to the molecular oxygen of cancer cells. To clarify the photophysical characteristics in the excited states of a few experimentally identified thionated (>C=S) molecules and their oxygenated congeners (>C=O), a quantum chemical study is conducted. This study illustrates the properties of the excited states in oxygen congeners that render them unsuitable for PDT treatment. Concurrently, a hierarchy is presented based on the utility of the lowest-energy triplet excitons of thionated compounds. Their non-radiative decay rates are calculated for reverse-ISC and inter-system crossover (ISC) processes. In addition, the vibronic importance of C=O and C=S bonds is clarified by the computation of the Huang-Rhys factor, effective vibrational mode, and reorganization energy inside the Marcus-Levich-Jörtner system. ROS generation in thionated PSs exceeds their oxygen congeners as kf ≪ kISC, where radiative decay rate is designated as kf. As a result, the current work offers a calculated strategy for analyzing the effectiveness of thionated photosensitizers in PDT.

Synthesis, Cytotoxicity, and Photophysical Investigations of 2-Amino-4,6-diphenylnicotinonitriles: An Experimental and Theoretical Study.

In this study, we present a comprehensive investigation of 2-amino-4,6-diphenylnicotinonitriles (APNs, 1-6), including their synthesis, cytotoxicity against breast cancer cell lines, and photophysical properties. Compound 3 demonstrates exceptional cytotoxicity, surpassing the potency of Doxorubicin. The fluorescence spectra of the synthesized 1-6 in different solvents reveal solvent-dependent shifts in the emission maximum values, highlighting the influence of the solvent environment on their fluorescence properties. A quantum chemical TD-DFT analysis provides insights into the electronic structure and fluorescence behavior of 1-6, elucidating HOMO-LUMO energy gaps, electronegativity values, and dipole moments, contributing to a deeper understanding of their electronic properties and potential reactivity. These findings provide valuable knowledge for the development of APNs (1-6) as fluorescent sensors and potential anticancer agents.

Quantum-enhanced hybrid feature engineering in thoracic CT image analysis for state-of-the-art nodule classification: an advanced lung cancer assessment.

The intricate nature of lung cancer treatment poses considerable challenges upon diagnosis. Early detection plays a pivotal role in mitigating its escalating global mortality rates. Consequently, there are pressing demands for robust and dependable early detection and diagnostic systems. However, the technological limitations and complexity of the disease make it challenging to implement an efficient lung cancer screening system. AI-based CT image analysis techniques are showing significant contributions to the development of computer-assisted detection (CAD) systems for lung cancer screening. Various existing research groups are working on implementing CT image analysis systems for assessing and classifying lung cancer. However, the complexity of different structures inside the CT image is high and comprehension of significant information inherited by them is more complex even after applying advanced feature extraction and feature selection techniques. Traditional and classical feature selection techniques may struggle to capture complex interdependencies between features. They may get stuck in local optima and sometimes require additional exploration strategies. Traditional techniques may also struggle with combinatorial optimization problems when applied to a prominent feature space. This paper proposed a methodology to overcome the existing challenges by applying feature extraction using Vision Transformer (FexViT) and Feature selection using the Quantum Computing based Quadratic unconstrained binary optimization (QC-FSelQUBO) technique. This algorithm shows better performance when compared with other existing techniques. The proposed methodology showed better performance as compared to other existing techniques when evaluated by applying necessary output measures, such as accuracy, Area under roc (receiver operating characteristics) curve, precision, sensitivity, and specificity, obtained as 94.28%, 99.10%, 96.17%, 90.16% and 97.46%. The further advancement of CAD systems is essential to meet the demand for more reliable detection and diagnosis of cancer, which can be addressed by leading the proposed quantum computation and growing AI-based technology ahead.

Haplotype-resolved assembly of diploid and polyploid genomes using quantum computing.

Precision medicine's emphasis on individual genetic variants highlights the importance of haplotype-resolved assembly, a computational challenge in bioinformatics given its combinatorial nature. While classical algorithms have made strides in addressing this issue, the potential of quantum computing remains largely untapped. Here, we present the vehicle routing problem (VRP) assembler: an approach that transforms this task into a vehicle routing problem, an optimization formulation solvable on a quantum computer. We demonstrate its potential and feasibility through a proof of concept on short synthetic diploid and triploid genomes using a D-Wave quantum annealer. To tackle larger-scale assembly problems, we integrate the VRP assembler with Google's OR-Tools, achieving a haplotype-resolved local assembly across the human major histocompatibility complex (MHC) region. Our results show encouraging performance compared to Hifiasm with phasing accuracy approaching the theoretical limit, underscoring the promising future of quantum computing in bioinformatics.

Quantum chemistry calculation-aided discovery of potent small-molecule mimics of glutathione peroxidases for the treatment of cisplatin-induced hearing loss.

Hearing loss (HL) is a health burden that seriously affects the quality of life of cancer patients receiving platinum-based chemotherapy, and few FDA-approved treatment specifically targets this condition. The main mechanisms that contribute to cisplatin-induced hearing loss are oxidative stress and subsequent cell death, including ferroptosis revealed by us as a new mechanism recently. In this study, we employed the frontier molecular orbital (FMO) theory approach as a convenient prediction method for the glutathione peroxidase (GPx)-like activity of isoselenazolones and discovered new isoselenazolones with great GPx-like activity. Notably, compound 19 exhibited significant protective effects against cisplatin-induced hair cell (HC) damage in vitro and in vivo and effectively reverses cisplatin-induced hearing loss through oral administration. Further investigations revealed that this compound effectively alleviated hair cell oxidative stress, apoptosis and ferroptosis. This research highlights the potential of GPx mimics as a therapeutic strategy against cisplatin-induced hearing loss. The application of quantum chemistry (QC) calculations in the study of GPx mimics sheds light on the development of new, innovative treatments for hearing loss.

Influence of acid-base equilibrium on interactions of some monofunctional coumarin Pd(II) complexes with biologically relevant nucleophiles-comprehensive kinetic study.

This aimed to develop a comprehensive theoretical protocol for examining substitution reaction processes. The researchers used a theoretical quantum-mechanical protocol based on the QM-ORSA approach, which estimates the kinetic parameters of thermodynamically favourable reaction pathways. This theoretical protocol was validated by experimentally investigating substitution mechanisms in two previously synthesised Pd(II) complexes: chlorido-[(3-(1-(2-hydroxypropylamino)ethylidene)chroman-2,4-dione)]palladium(II) (C1) and chlorido-[(3-(1-(2-mercaptoethylamino)-ethylidene)-chroman-2,4dione)]palladium(II) (C2), along with biologically relevant nucleophiles, namely L-cysteine (l-Cys), L-methionine (l-Met), and guanosine-5'-monophosphate (5'-GMP). Reactions were investigated under pseudo-first-order conditions, monitoring nucleophile concentration and temperature changes using stopped-flow UV-vis spectrophotometry. All reactions were conducted under physiological conditions (pH = 7.2) at 37 °C. The reactivity of the studied nucleophiles follows the order: l-Cys > l-Met > 5'-GMP, and the reaction mechanism is associative based on the activation parameters. The experimental and theoretical data showed that C2 is more reactive than C1, confirming that the complexes' structural and electronic properties greatly affect their reactivity with selected nucleophiles. The study's findings have confirmed that the primary interaction occurs with the acid-base species L-Cys, mostly through the involvement of the partially negative sulfur atom (87.2%). On the other hand, C2 has a higher propensity for reacting with L-Cys-, primarily through the partially negative oxygen atom (92.6%). The implementation of this theoretical framework will significantly restrict the utilization of chemical substances, hence facilitating cost reduction and environmental protection.

Quantum Defect Sensitization via Phase-Changing Supercharged Antibody Fragments.

Quantum defects in single-walled carbon nanotubes promote exciton localization, which enables potential applications in biodevices and quantum light sources. However, the effects of local electric fields on the emissive energy states of quantum defects and how they can be controlled are unexplored. Here, we investigate quantum defect sensitization by engineering an intrinsically disordered protein to undergo a phase change at a quantum defect site. We designed a supercharged single-chain antibody fragment (scFv) to enable a full ligand-induced folding transition from an intrinsically disordered state to a compact folded state in the presence of a cytokine. The supercharged scFv was conjugated to a quantum defect to induce a substantial local electric change upon ligand binding. Employing the detection of a proinflammatory biomarker, interleukin-6, as a representative model system, supercharged scFv-coupled quantum defects exhibited robust fluorescence wavelength shifts concomitant with the protein folding transition. Quantum chemical simulations suggest that the quantum defects amplify the optical response to the localization of charges produced upon the antigen-induced folding of the proteins, which is difficult to achieve in unmodified nanotubes. These findings portend new approaches to modulate quantum defect emission for biomarker sensing and protein biophysics and to engineer proteins to modulate binding signal transduction.

Systematic QM/MM Study for Predicting 31P NMR Chemical Shifts of Adenosine Nucleotides in Solution and Stages of ATP Hydrolysis in a Protein Environment.

NMR (nuclear magnetic resonance) spectroscopy allows for important atomistic insights into the structure and dynamics of biological macromolecules; however, reliable assignments of experimental spectra are often difficult. Herein, quantum mechanical/molecular mechanical (QM/MM) calculations can provide crucial support. A major problem for the simulations is that experimental NMR signals are time-averaged over much longer time scales, and since computed chemical shifts are highly sensitive to local changes in the electronic and structural environment, sufficiently large averages over representative structural ensembles are essential. This entails high computational demands for reliable simulations. For NMR measurements in biological systems, a nucleus of major interest is 31P since it is both highly present (e.g., in nucleic acids) and easily observable. The focus of our present study is to develop a robust and computationally cost-efficient framework for simulating 31P NMR chemical shifts of nucleotides. We apply this scheme to study the different stages of the ATP hydrolysis reaction catalyzed by p97. Our methodology is based on MM molecular dynamics (MM-MD) sampling, followed by QM/MM structure optimizations and NMR calculations. Overall, our study is one of the most comprehensive QM-based 31P studies in a protein environment and the first to provide computed NMR chemical shifts for multiple nucleotide states in a protein environment. This study sheds light on a process that is challenging to probe experimentally and aims to bridge the gap between measured and calculated NMR spectroscopic properties.

On-site rapid detection of perfluorooctanoic acid by visual immunochromatographic strip biosensor in domestic water and real human samples.

The International Agency for Research on Cancer (IARC) classifies PFOA as a Class 1 carcinogen. Here, a new naked-eye PFOA immunochromographic strip was developed to recognize PFOA in domestic water and real human samples within 10 min based on a novel custom designed anti-PFOA monoclonal antibody (mAb) 2A3, which was firstly an immune rapid detection method for PFOA has been proposed. Using computer simulation techniques such as quantum computing to assist in designing the structural formula of PFOA semi antigen, which hapten was firstly proposed. The half maximal inhibitory concentration of PFOA monoclonal antibody (mAb) 2A3 was 2.4 µg/mL. Using mAb 2A3, we developed an immunochromatographic strip (ICS) for detecting PFOA in real samples. The developed method generated results in 10 min, with visual detection limits of 20, 20, and 200 µg/mL and limit of detection of 50, 200, and 500 µg/mL for water, blood and urine samples, respectively. The established ICS and indirect competitive enzyme-linked immunosorbent assay were used to analyze the actual samples, and the results were confirmed by LC-MS/MS. Our study findings showed that the ICS and ic-ELISA can quickly detect PFOA in actual samples.

Computational Investigation of the Covalent Inhibition Mechanism of Bruton's Tyrosine Kinase by Ibrutinib.

Covalent inhibitors represent a promising class of therapeutic compounds. Nonetheless, rationally designing covalent inhibitors to achieve a right balance between selectivity and reactivity remains extremely challenging. To better understand the covalent binding mechanism, a computational study is carried out using the irreversible covalent inhibitor of Bruton tyrosine kinase (BTK) ibrutinib as an example. A multi-µs classical molecular dynamics trajectory of the unlinked inhibitor is generated to explore the fluctuations of the compound associated with the kinase binding pocket. Then, the reaction pathway leading to the formation of the covalent bond with the cysteine residue at position 481 via a Michael addition is determined using the string method in collective variables on the basis of hybrid quantum mechanical-molecular mechanical (QM/MM) simulations. The reaction pathway shows a strong correlation between the covalent bond formation and the protonation/deprotonation events taking place sequentially in the covalent inhibition reaction, consistent with a 3-step reaction with transient thiolate and enolates intermediate states. Two possible atomistic mechanisms affecting deprotonation/protonation events from the thiolate to the enolate intermediate were observed: a highly correlated direct pathway involving proton transfer to the Cα of the acrylamide warhead from the cysteine involving one or a few water molecules and a more indirect pathway involving a long-lived enolate intermediate state following the escape of the proton to the bulk solution. The results are compared with experiments by simulating the long-time kinetics of the reaction using kinetic modeling.

Mechanism of AGT-Mediated Repair of dG-dC Cross-Links in the Drug Resistance to Chloroethylnitrosoureas: Molecular Docking, MD Simulation, and ONIOM (QM/MM) Investigation.

Chloroethylnitrosoureas (CENUs) are important chemotherapies applied in the treatment of cancer. They exert anticancer activity by inducing DNA interstrand cross-links (ICLs) via the formation of two O6-alkylguanine intermediates, O6-chloroethylguanine (O6-ClEtG) and N1,O6-ethanoguanine (N1,O6-EtG). However, O6-alkylguanine-DNA alkyltransferase (AGT), a DNA-repair enzyme, can restore the O6-alkylguanine damages and thereby obstruct the formation of ICLs (dG-dC cross-link). In this study, the inhibitory mechanism of ICL formation was investigated to elucidate the drug resistance of CENUs mediated by AGT in detail. Based on the structures of the substrate-enzyme complexes obtained from docking and MD simulations, two ONIOM (QM/MM) models with different sizes of the QM region were constructed. The model with a larger QM region, which included the substrate (O6-ClEtG or N1,O6-EtG), a water molecule, and five residues (Tyr114, Cys145, His146, Lys165, and Glu172) in the active pocket of AGT, accurately described the repairing reaction and generated the results coinciding with the experimental outcomes. The repair process consists of two sequential steps: hydrogen transfer to form a thiolate anion on Cys145 and alkyl transfer from the O6 site of guanine (the rate-limiting step). The repair of N1,O6-EtG was more favorable than that of O6-ClEtG from both kinetics and thermodynamics aspects. Moreover, the comparison of the repairing process with the formation of dG-dC cross-link and the inhibition of AGT by O6-benzylguanine (O6-BG) showed that the presence of AGT could effectively interrupt the formation of ICLs leading to drug resistance, and the inhibition of AGT by O6-BG that was energetically more favorable than the repair of O6-ClEtG could not prevent the repair of N1,O6-EtG. Therefore, it is necessary to completely eliminate AGT activity before CENUs medication to enhance the chemotherapeutic effectiveness. This work provides reasonable explanations for the supposed mechanism of AGT-mediated drug resistance of CENUs and will assist in the development of novel CENU chemotherapies and their medication strategies.

Single-and double transition metal atoms anchored C2N as a high-activity catalyst for CO oxidation: A first-principles study.

The oxidation of CO has attracted great interest in recent years due to its important role in enhancing the catalyst durability in fuel cells and solving the growing environmental problems caused by CO emissions. Consequently, the catalytic oxidation of CO at double non-noble metal atoms anchored C2N is investigated using density functional theory (DFT) computations. All the screened Ti@C2N and Ti2@C2N are thermodynamically stable based on their binding energy calculations. The electronic characteristics, the natural bond orbital analyses (NBO), Frontier orbital, statistical thermodynamics, projected densities of states (PDOS) characteristics, non-covalent interactions (NCI), and quantum theory of atoms in molecules (QTAIM) descriptors of these systems have been examined to analyze the interaction process. Our comparative study suggested that the newly predicted double-atom catalyst (Ti2@C2N) is highly active for CO oxidation, which is a useful guideline for further development. The calculated static first-order hyperpolarizability (ßo) illustrated that the double-atom catalyst under investigation can be considered a potential candidate for non-linear optical behavior and could be used for NLO applications. CO oxidation on Ti2@C2N along the Eley-Rideal (ER) mechanism with a low energy barrier of 0.16 eV, which is smaller than the maximum energy barrier (0.73 eV) of CO oxidation along the Langmuir-Hinshelwood (LH) mechanism. Consequently, the ER mechanism is more favorable both thermodynamically and dynamically. This work can provide useful insights and guidelines for future theoretical and experimental investigations to promote the design and development of highly effective and low-cost non-precious-metal Ti2@C2N nanocatalysts towards CO oxidation at ambient temperature.

QM/MM Study of the Catalytic Mechanism and Substrate Specificity of the Aromatic Substrate C-Methyltransferase Fur6.

In the field of medical chemistry and other organic chemistry, introducing a methyl group into a designed position has been difficult to achieve. However, owing to the vigorous developments in the field of enzymology, methyltransferases are considered potential tools for addressing this problem. Within the methyltransferase family, Fur6 catalyzes the methylation of C3 of 1,2,4,5,7-pentahydroxynaphthalene (PHN) using S-adenosyl-l-methionine (SAM) as the methyl donor. Here, we report the catalytic mechanism and substrate specificity of Fur6 based on computational studies. Our molecular dynamics (MD) simulation studies reveal the reactive form of PHN and its interactions with the enzyme. Our hybrid quantum mechanics/molecular mechanics (QM/MM) calculations suggest the reaction pathway of the methyl transfer step in which the energy barrier is 8.6 kcal mol-1. Our free-energy calculations with a polarizable continuum model (PCM) indicate that the final deprotonation step of the methylated intermediate occurs after it is ejected into the water solvent from the active center pocket of Fur6. Additionally, our studies on the protonation states, the highest occupied molecular orbital (HOMOs), and the energy barriers of the methylation reaction for the analogs of PHN demonstrate the mechanism of the specificity to PHN. Our study provides valuable insights into Fur6 chemistry, contributing to a deeper understanding of molecular mechanisms and offering an opportunity to engineer the enzyme to achieve high yields of the desired product(s).

On the Existence of Pnictogen Bonding Interactions in As(III) S-Adenosylmethionine Methyltransferase Enzymes.

As(III) S-adenosylmethionine methyltransferases, pivotal enzymes in arsenic metabolism, facilitate the methylation of arsenic up to three times. This process predominantly yields trivalent mono- and dimethylarsenite, with trimethylarsine forming in smaller amounts. While this enzyme acts as a detoxifier in microbial systems by altering As(III), in humans, it paradoxically generates more toxic and potentially carcinogenic methylated arsenic species. The strong affinity of As(III) for cysteine residues, forming As(III)-thiolate bonds, is exploited in medical treatments, notably in arsenic trioxide (Trisenox®), an FDA-approved drug for leukemia. The effectiveness of this drug is partly due to its interaction with cysteine residues, leading to the breakdown of key oncogenic fusion proteins. In this study, we extend the understanding of As(III)'s binding mechanisms, showing that, in addition to As(III)-S covalent bonds, noncovalent O⋅⋅⋅As pnictogen bonding plays a vital role. This interaction significantly contributes to the structural stability of the As(III) complexes. Our crystallographic analysis using the PDB database of As(III) S-adenosylmethionine methyltransferases, augmented by comprehensive theoretical studies including molecular electrostatic potential (MEP), quantum theory of atoms in molecules (QTAIM), and natural bond orbital (NBO) analysis, emphasizes the critical role of pnictogen bonding in these systems. We also undertake a detailed evaluation of the energy characteristics of these pnictogen bonds using various theoretical models. To our knowledge, this is the first time pnictogen bonds in As(III) derivatives have been reported in biological systems, marking a significant advancement in our understanding of arsenic's molecular interactions.

Spectroscopic, computational, cytotoxicity, and docking studies of 6-bromobenzimidazole as anti-breast cancer agent.

6-Bromobenzimidazole (6BBZ) has been calculated in this study utilizing the 6-311++G(d,p) basis set and the Becke-3-Lee-Yang-Parr density functional approaches. The basic frequencies and geometric optimization are known. FTIR, FT-Raman, and UV-Vis spectra of the substance are compared between its computed and observed values. The energy gap between highest occupied molecular orbital-lowest unoccupied molecular orbital and molecule electrostatic potentials has been represented by charge density distributions that may be associated with the biological response. Time-dependent density functional theory calculations in the gas phase and dimethyl sulfoxide were carried out to ascertain the electronic properties and energy gap values using the same basis set. Molecular orbital contributions are investigated using the overlap population, partial, and total densities of states. Natural bond analysis was found to have strong electron delocalization by means of π(C4-C9) → π*(C5-C6), LP (N1) → π*(C7-C8), and LP(Br12) → π*(C5-C6) interactions. The Fukui function and Mulliken analysis have been explored on the atomic charges of the molecule. The nuclear magnetic resonance chemical shifts for 1 H and 13 C have been computed using the gauge-independent atomic orbital technique. With the highest binding affinity (-6.2 kcal mol-1 ) against estrogen sulfotransferase receptor (PDB ID: 1AQU) and low IC50 value of 17.23 µg/mL, 6BBZ demonstrated potent action against the MCF-7 breast cancer cell line. Studies on the antibacterial activity and ADMET prediction of the molecule have also been carried out.