An efficient computational scheme for solving coupled time-fractional Schrödinger equation via cubic B-spline functions.

The time fractional Schrödinger equation contributes to our understanding of complex quantum systems, anomalous diffusion processes, and the application of fractional calculus in physics and cubic B-spline is a versatile tool in numerical analysis and computer graphics. This paper introduces a numerical method for solving the time fractional Schrödinger equation using B-spline functions and the Atangana-Baleanu fractional derivative. The proposed method employs a finite difference scheme to discretize the fractional derivative in time, while a θ-weighted scheme is used to discretize the space directions. The efficiency of the method is demonstrated through numerical results, and error norms are examined at various values of the non-integer parameter, temporal directions, and spatial directions.

Halogen Bond via an Electrophilic π-Hole on Halogen in Molecules: Does It Exist?

This study reveals a new non-covalent interaction called a π-hole halogen bond, which is directional and potentially non-linear compared to its sister analog (σ-hole halogen bond). A π-hole is shown here to be observed on the surface of halogen in halogenated molecules, which can be tempered to display the aptness to form a π-hole halogen bond with a series of electron density-rich sites (Lewis bases) hosted individually by 32 other partner molecules. The [MP2/aug-cc-pVTZ] level characteristics of the π-hole halogen bonds in 33 binary complexes obtained from the charge density approaches (quantum theory of intramolecular atoms, molecular electrostatic surface potential, independent gradient model (IGM-δginter)), intermolecular geometries and energies, and second-order hyperconjugative charge transfer analyses are discussed, which are similar to other non-covalent interactions. That a π-hole can be observed on halogen in halogenated molecules is substantiated by experimentally reported crystals documented in the Cambridge Crystal Structure Database. The importance of the π-hole halogen bond in the design and growth of chemical systems in synthetic chemistry, crystallography, and crystal engineering is yet to be fully explicated.

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.

Impact of an Ionic Liquid Solution on Horseradish Peroxidase Activity.

Horseradish peroxidase (HRP) is an enzyme that oxidizes pollutants from wastewater. A previous report indicated that peroxidases can have an enhancement in initial enzymatic activity in an aqueous solution of 0.26 M 1-ethyl-3-methylimidazolium ethyl sulfate ([EMIm][EtSO4]) at neutral pH. However, the atomistic details remain elusive. In the enzymatic landscape of HRP, compound II (Cpd II) plays a key role and involves a histidine (H42) residue. Cpd II exists as oxoferryl (2a) or hydroxoferryl (2b(FeIV)) forms, where 2a is the predominantly observed form in experimental studies. Intriguingly, the ferric 2b(FeIII) form seen in synthetic complexes has not been observed in HRP. Here, we have investigated the structure and dynamics of HRP in pure water and aqueous [EMIm][EtSO4] (0.26 M), as well as the reaction mechanism of 2a to 2b conversion using polarizable molecular dynamics (MD) simulations and quantum mechanics/molecular mechanics (QM/MM) calculations. When HRP is solvated in aq [EMIm][EtSO4], the catalytic water displaces, and H42 directly orients over the ferryl moiety, allowing a direct proton transfer (PT) with a significant energy barrier reduction. Conversely, in neat water, the reaction of 2a to 2b follows the previously reported mechanism. We further investigated the deprotonated form of H42. Analysis of the electric fields at the active site indicates that the aq [EMIm][EtSO4] medium facilitates the reaction by providing a more favorable environment compared with the system solvated in neat water. Overall, the atomic level supports the previous experimental observations and underscores the importance of favorable electric fields in the active site to promote catalysis.

Theoretical Insights into N-Glycoside Bond Cleavage of 5-Carboxycytosine by Thymine DNA Glycosylase: A QM/MM Study.

Thymine DNA glycosylase (TDG)-mediated excision of 5-formylcytosine and 5-carboxylcytosine (5-caC) is a critical step in active DNA demethylation. Herein, we employed a combined quantum mechanics/molecular mechanics approach to investigate the reaction mechanism of TDG-catalyzed N-glycosidic bond cleavage of 5-caC. The calculated results show that TDG-catalyzed 5-caC excision follows a concerted (SN2) mechanism in which glycosidic bond dissociation is coupled with nucleophile attack. Protonation of the 5-caC anion contributes to the cleavage of the N-glycoside bond, in which the N3-protonated zwitterion and imino tautomers are more favorable than carboxyl-protonated amino tautomers. This is consistent with the experimental data. Furthermore, our results reveal that the configuration rearrangement process of the protonated 5-caC would lower the stability of the N-glycoside bond and substantially reduce the barrier height for the subsequent C1'-N1 bond cleavage. This should be attributed to the smaller electrostatic repulsion between the leaving base and the negative phosphate group as a result of the structural rearrangement.

Computational study on the endocrine-disrupting metabolic activation of Benzophenone-3 catalyzed by cytochrome P450 1A1: A QM/MM approach.

Predicting the metabolic activation mechanism and potential hazardous metabolites of environmental endocrine-disruptors is a challenging and significant task in risk assessment. Here the metabolic activation mechanism of benzophenone-3 catalyzed by P450 1A1 was investigated by using Molecular Dynamics, Quantum Mechanics/Molecular Mechanics and Density Functional Theory approaches. Two elementary reactions involved in the metabolic activation of BP-3 with P450 1A1: electrophilic addition and hydrogen abstraction reactions were both discussed. Further conversion reactions of epoxidation products, ketone products and the formaldehyde formation reaction were investigated in the non-enzymatic environment based on previous experimental reports. Binding affinities analysis of benzophenone-3 and its metabolites to sex hormone binding globulin indirectly demonstrates that they all exhibit endocrine-disrupting property. Toxic analysis shows that the eco-toxicity and bioaccumulation values of the benzophenone-3 metabolites are much lower than those of benzophenone-3. However, the metabolites are found to have skin-sensitization effects. The present study provides a deep insight into the biotransformation process of benzophenone-3 catalyzed by P450 1A1 and alerts us to pay attention to the adverse effects of benzophenone-3 and its metabolites in human livers.

Exploring the Light-Emitting Agents in Renilla Luciferases by an Effective QM/MM Approach.

Bioluminescence is a fascinating natural phenomenon, wherein organisms produce light through specific biochemical reactions. Among these organisms, Renilla luciferase (RLuc) derived from the sea pansy Renilla reniformis is notable for its blue light emission and has potential applications in bioluminescent tagging. Our study focuses on RLuc8, a variant of RLuc with eight amino acid substitutions. Recent studies have shown that the luminescent emitter coelenteramide can adopt multiple protonation states, which may be influenced by nearby residues at the enzyme's active site, demonstrating a complex interplay between protein structure and bioluminescence. Herein, using the quantum mechanical consistent force field method and the semimacroscopic protein dipole-Langevin dipole method with linear response approximation, we show that the phenolate state of coelenteramide in RLuc8 is the primary light-emitting species in agreement with experimental results. Our calculations also suggest that the proton transfer (PT) from neutral coelenteramide to Asp162 plays a crucial role in the bioluminescence process. Additionally, we reproduced the observed emission maximum for the amide anion in RLuc8-D120A and the pyrazine anion in the presence of a Na+ counterion in RLuc8-D162A, suggesting that these are the primary emitters. Furthermore, our calculations on the neutral emitter in the engineered AncFT-D160A enzyme, structurally akin to RLuc8-D162A but with a considerably blue-shifted emission peak, aligned with the observed data, possibly explaining the variance in emission peaks. Overall, this study demonstrates an effective approach to investigate chromophores' bimolecular states while incorporating the PT process in emission spectra calculations, contributing valuable insights for future studies of PT in photoproteins.

High-resolution heteronuclear correlations between spin-1/2 and half-integer quadrupolar nuclei under fast MAS solid-state NMR.

High isotropic resolution is essential for the structural elucidation of samples with multiple sites. In this study, utilizing the benefits of TRAPDOR-based heteronuclear multiple quantum coherence (T-HMQC) and a pair of one rotor period long cosine amplitude modulated low-power (cos-lp) pulse-based symmetric-split-t1 multiple-quantum magic angle spinning (MQMAS) methods, we have developed a proton-detected 2D 35Cl/1H T-HMQC-MQMAS pulse sequence under fast MAS (70 kHz) to achieve high-resolution in the indirect dimension of the spin-3/2 (35Cl) nuclei connected via protons. As T-HMQC polarizes not only single-quantum central transition (SQCT) but also triple-quantum (TQ) coherences, the proposed 2D pulse sequence is implemented via selection of two coherence pathways (SQCT→TQ →SQCT and TQ → SQCT→TQ) resulting in the 35Cl isotropic dimension and is superior to the existing double-quantum satellite-transition (DQST) T-HMQC in terms of resolution.

Creation of memory-memory entanglement in a metropolitan quantum network.

Towards realizing the future quantum internet1,2, a pivotal milestone entails the transition from two-node proof-of-principle experiments conducted in laboratories to comprehensive multi-node set-ups on large scales. Here we report the creation of memory-memory entanglement in a multi-node quantum network over a metropolitan area. We use three independent memory nodes, each of which is equipped with an atomic ensemble quantum memory3 that has telecom conversion, together with a photonic server where detection of a single photon heralds the success of entanglement generation. The memory nodes are maximally separated apart for 12.5 kilometres. We actively stabilize the phase variance owing to fibre links and control lasers. We demonstrate concurrent entanglement generation between any two memory nodes. The memory lifetime is longer than the round-trip communication time. Our work provides a metropolitan-scale testbed for the evaluation and exploration of multi-node quantum network protocols and starts a stage of quantum internet research.

A Perspective on Protein Structure Prediction Using Quantum Computers.

Despite the recent advancements by deep learning methods such as AlphaFold2, in silico protein structure prediction remains a challenging problem in biomedical research. With the rapid evolution of quantum computing, it is natural to ask whether quantum computers can offer some meaningful benefits for approaching this problem. Yet, identifying specific problem instances amenable to quantum advantage and estimating the quantum resources required are equally challenging tasks. Here, we share our perspective on how to create a framework for systematically selecting protein structure prediction problems that are amenable for quantum advantage, and estimate quantum resources for such problems on a utility-scale quantum computer. As a proof-of-concept, we validate our problem selection framework by accurately predicting the structure of a catalytic loop of the Zika Virus NS3 Helicase, on quantum hardware.

Fusion of deterministically generated photonic graph states.

Entanglement has evolved from an enigmatic concept of quantum physics to a key ingredient of quantum technology. It explains correlations between measurement outcomes that contradict classical physics and has been widely explored with small sets of individual qubits. Multi-partite entangled states build up in gate-based quantum-computing protocols and-from a broader perspective-were proposed as the main resource for measurement-based quantum-information processing1,2. The latter requires the ex-ante generation of a multi-qubit entangled state described by a graph3-6. Small graph states such as Bell or linear cluster states have been produced with photons7-16, but the proposed quantum-computing and quantum-networking applications require fusion of such states into larger and more powerful states in a programmable fashion17-21. Here we achieve this goal by using an optical resonator22 containing two individually addressable atoms23,24. Ring25 and tree26 graph states with up to eight qubits, with the names reflecting the entanglement topology, are efficiently fused from the photonic states emitted by the individual atoms. The fusion process itself uses a cavity-assisted gate between the two atoms. Our technique is, in principle, scalable to even larger numbers of qubits and is the decisive step towards, for instance, a memory-less quantum repeater in a future quantum internet27-29.

Entanglement of nanophotonic quantum memory nodes in a telecom network.

A key challenge in realizing practical quantum networks for long-distance quantum communication involves robust entanglement between quantum memory nodes connected by fibre optical infrastructure1-3. Here we demonstrate a two-node quantum network composed of multi-qubit registers based on silicon-vacancy (SiV) centres in nanophotonic diamond cavities integrated with a telecommunication fibre network. Remote entanglement is generated by the cavity-enhanced interactions between the electron spin qubits of the SiVs and optical photons. Serial, heralded spin-photon entangling gate operations with time-bin qubits are used for robust entanglement of separated nodes. Long-lived nuclear spin qubits are used to provide second-long entanglement storage and integrated error detection. By integrating efficient bidirectional quantum frequency conversion of photonic communication qubits to telecommunication frequencies (1,350 nm), we demonstrate the entanglement of two nuclear spin memories through 40 km spools of low-loss fibre and a 35-km long fibre loop deployed in the Boston area urban environment, representing an enabling step towards practical quantum repeaters and large-scale quantum networks.

Accelerating reliable multiscale quantum refinement of protein-drug systems enabled by machine learning.

Biomacromolecule structures are essential for drug development and biocatalysis. Quantum refinement (QR) methods, which employ reliable quantum mechanics (QM) methods in crystallographic refinement, showed promise in improving the structural quality or even correcting the structure of biomacromolecules. However, vast computational costs and complex quantum mechanics/molecular mechanics (QM/MM) setups limit QR applications. Here we incorporate robust machine learning potentials (MLPs) in multiscale ONIOM(QM:MM) schemes to describe the core parts (e.g., drugs/inhibitors), replacing the expensive QM method. Additionally, two levels of MLPs are combined for the first time to overcome MLP limitations. Our unique MLPs+ONIOM-based QR methods achieve QM-level accuracy with significantly higher efficiency. Furthermore, our refinements provide computational evidence for the existence of bonded and nonbonded forms of the Food and Drug Administration (FDA)-approved drug nirmatrelvir in one SARS-CoV-2 main protease structure. This study highlights that powerful MLPs accelerate QRs for reliable protein-drug complexes, promote broader QR applications and provide more atomistic insights into drug development.

Quantum mechanics insights into melatonin and analogs binding to melatonin MT1 and MT2 receptors.

Melatonin receptors MT1 and MT2 are G protein-coupled receptors that mediate the effects of melatonin, a hormone involved in circadian rhythms and other physiological functions. Understanding the molecular interactions between these receptors and their ligands is crucial for developing novel therapeutic agents. In this study, we used molecular docking, molecular dynamics simulations, and quantum mechanics calculation to investigate the binding modes and affinities of three ligands: melatonin (MLT), ramelteon (RMT), and 2-phenylmelatonin (2-PMT) with both receptors. Based on the results, we identified key amino acids that contributed to the receptor-ligand interactions, such as Gln181/194, Phe179/192, and Asn162/175, which are conserved in both receptors. Additionally, we described new meaningful interactions with Gly108/Gly121, Val111/Val124, and Val191/Val204. Our results provide insights into receptor-ligand recognition's structural and energetic determinants and suggest potential strategies for designing more optimized molecules. This study enhances our understanding of receptor-ligand interactions and offers implications for future drug development.

Biomarker discovery with quantum neural networks: a case-study in CTLA4-activation pathways.

BACKGROUND: Biomarker discovery is a challenging task due to the massive search space. Quantum computing and quantum Artificial Intelligence (quantum AI) can be used to address the computational problem of biomarker discovery from genetic data. METHOD: We propose a Quantum Neural Networks architecture to discover genetic biomarkers for input activation pathways. The Maximum Relevance-Minimum Redundancy criteria score biomarker candidate sets. Our proposed model is economical since the neural solution can be delivered on constrained hardware. RESULTS: We demonstrate the proof of concept on four activation pathways associated with CTLA4, including (1) CTLA4-activation stand-alone, (2) CTLA4-CD8A-CD8B co-activation, (3) CTLA4-CD2 co-activation, and (4) CTLA4-CD2-CD48-CD53-CD58-CD84 co-activation. CONCLUSION: The model indicates new genetic biomarkers associated with the mutational activation of CLTA4-associated pathways, including 20 genes: CLIC4, CPE, ETS2, FAM107A, GPR116, HYOU1, LCN2, MACF1, MT1G, NAPA, NDUFS5, PAK1, PFN1, PGAP3, PPM1G, PSMD8, RNF213, SLC25A3, UBA1, and WLS. We open source the implementation at: https://github.com/namnguyen0510/Biomarker-Discovery-with-Quantum-Neural-Networks .

Quantum simulation of Pauli channels and dynamical maps: Algorithm and implementation.

Pauli channels are fundamental in the context of quantum computing as they model the simplest kind of noise in quantum devices. We propose a quantum algorithm for simulating Pauli channels and extend it to encompass Pauli dynamical maps (parametrized Pauli channels). A parametrized quantum circuit is employed to accommodate for dynamical maps. We also establish the mathematical conditions for an N-qubit transformation to be achievable using a parametrized circuit where only one single-qubit operation depends on the parameter. The implementation of the proposed circuit is demonstrated using IBM's quantum computers for the case of one qubit, and the fidelity of this implementation is reported.

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.

DFT/TDDFT calculations of geometry optimization, electronic structure and spectral properties of clevudine and telbivudine for treatment of chronic hepatitis B.

Chronic hepatitis B remains a worldwide health concern. Presently, many drugs, such as Clevudine and Telbivudine, are recommended for the treatment of chronic hepatitis B disease. For this purpose, the quantum chemical analysis of ELUMO-HOMO (Egap), ionization potential (IP), electron affinity (EA), electronegativity (EN), chemical hardness (η), chemical potential (µ), chemical softness (S), electrophilicity index (ω), electron accepting capability (ω+), electron-donating capability (ω-), Nucleophilicity index (N), additional electronic charge (∆Nmax), Optical softness (σ0) and Dipole Moment, IR and UV-Vis spectra, molecular electrostatic potential (MEP) profile, Mulliken charge analysis, natural bond orbital (NBO) were examined in this study. The dipole moment of the compounds suggests their binding pose and predicted binding affinity. The electrophilic and nucleophilic regions were identified, and techniques such as NBO, UV-Vis, and IR were used to gain insights into the molecular structure, electronic transitions, and potential drug design for Hepatitis B treatment. Calculations for this study were carried out using the Gaussian 09 program package coupled with the DFT/TDDFT technique. The hybrid B3LYP functional method and the 6-311++G(d, p) basis set were used for the calculations.

Origin of Enantioselectivity in Engineered Cytochrome c-Catalyzed Carbon-Radical FePP Hydrolysis Revealed Using QM/MM (ABEEM Polarizable Force Field) and MD Simulations.

The origin of highly efficient asymmetric aminohydroxylation of styrene catalyzed by engineered cytochrome c is investigated by the developed Atom-Bond Electronegativity Equalization Method polarizable force field (ABEEM PFF), which is a combined outcome of electronic and steric effects. Model molecules were used to establish the charge parameters of the ABEEM PFF, for which the bond-stretching and angle-bending parameters were obtained by using a combination of modified Seminario and scan methods. The interactions between carbon-radical Fe-porphyrin (FePP) and waters are simulated by molecular dynamics, which shows a clear preference for the pre-R over the pre-S. This preference is attributed to the hydrogen-bond between the mutated 100S and 101P residues as well as van der Waals interactions, enforcing a specific conformation of the carbon-radical FePP complex within the binding pocket. Meanwhile, the hydrogen-bond between water and the nitrogen atom in the active intermediate dictates the stereochemical outcome. Quantum mechanics/molecular mechanics (QM/MM (ABEEM PFF)) and free-energy perturbation calculations elucidate that the 3RTS is characterized by sandwich-like structure among adjacent amino acid residues, which exhibits greater stability than crowed arrangement in 3STS and enables the R enantiomer to form more favorably. Thus, this study provides mechanistic insight into the catalytic reaction of hemoproteins.

Quantum mechanical analysis of yttrium-stabilized zirconia and alumina: implications for mechanical performance of esthetic crowns.

BACKGROUND: Yttrium-stabilized zirconia (YSZ) and alumina are the most commonly used dental esthetic crown materials. This study aimed to provide detailed information on the comparison between yttrium-stabilized zirconia (YSZ) and alumina, the two materials most often used for esthetic crowns in dentistry. METHODOLOGY: The ground-state energy of the materials was calculated using the Cambridge Serial Total Energy Package (CASTEP) code, which employs a first-principles method based on density functional theory (DFT). The electronic exchange-correlation energy was evaluated using the generalized gradient approximation (GGA) within the Perdew (Burke) Ernzerhof scheme. RESULTS: Optimization of the geometries and investigation of the optical properties, dynamic stability, band structures, refractive indices, and mechanical properties of these materials contribute to a holistic understanding of these materials. Geometric optimization of YSZ provides important insights into its dynamic stability based on observations of its crystal structure and polyhedral geometry, which show stable configurations. Alumina exhibits a distinctive charge, kinetic, and potential (CKP) geometry, which contributes to its interesting structural framework and molecular-level stability. The optical properties of alumina were evaluated using pseudo-atomic computations, demonstrating its responsiveness to external stimuli. The refractive indices, reflectance, and dielectric functions indicate that the transmission of light by alumina depends on numerous factors that are essential for the optical performance of alumina as a material for esthetic crowns. The band structures of both the materials were explored, and the band gap of alumina was determined to be 5.853 eV. In addition, the band structure describes electronic transitions that influence the conductivity and optical properties of a material. The stability of alumina can be deduced from its bandgap, an essential property that determines its use as a dental material. Refractive indices are vital optical properties of esthetic crown materials. Therefore, the ability to understand their refractive-index graphs explains their transparency and color distortion through how the material responds to light..The regulated absorption characteristics exhibited by YSZ render it a highly attractive option for the development of esthetic crowns, as it guarantees minimal color distortion. CONCLUSION: The acceptability of materials for esthetic crowns is strongly determined by mechanical properties such as elastic stiffness constants, Young's modulus, and shear modulus. YSZ is a highly durable material for dental applications, owing to its superior mechanical strength.