Efficient design and implementation of approximate FA, FS, and FA/S circuits for nanocomputing in QCA.

Recently, there has been a lot of research in Quantum Cellular Automata (QCA) technology because it promises low power consumption, low complexity, low latency, and compact space. Simultaneously, approximate arithmetic, a new paradigm in computing, streamlines the computational process and emerges as a low-power, high-performance design approach for arithmetic circuits. Furthermore, the XOR gate has been widely used in digital design and is a basic building block that can be used in many upcoming technologies. The full adder (FA) circuit is a key component of QCA technology and is utilized in arithmetic logic operations including subtraction, multiplication, and division. A great deal of research has been done on the design of approximate FA, full subtractor (FS), full adder/subtractor (FA/S), and 4-bit ripple carry adder (RCA) based on XOR logic, establishing them as essential components in the creation of QCA-based arithmetic circuits. This study presents three new and effective QCA-based circuits, based on XOR logic: an approximate FA, an approximate FS, an approximate FA/S, and an approximate 4-bit ripple carry adder (RCA). Interestingly, some designs have inputs on one side and outputs on the other, making it easier to reach the components without being encircled by other cells and leading to a more effective circuit design. In particular, a delay of 0.5 clock phases, an area of 0.01 µm2, and implementation utilizing just 11 cells was accomplished in the approximate FA and subtractor designs. In a similar vein, the estimated FA/S designs showed 0.5 clock phase delay, 0.01 µm2 area, and 12 cells used for implementation. An approximate 4-bit RCA is proposed using 64 QCA cells. The effectiveness of these designs is evaluated through functional verification with the QCADesigner program. According to simulation results, these proposed solutions not only function well but significantly outperform previous ideas in terms of speed and space. The proposed FA, FS, and RCA designs surpassed the previous best designs by 21%, 21%, and 43%, respectively, in terms of cell count.

Computer-Aided Drug Design Using the Fragment Molecular Orbital Method: Current Status and Future Applications for SBDD.

Owing to the increasing use of computers, computer-aided drug design (CADD) has become an essential component of drug discovery research. In structure-based drug design (SBDD), including inhibitor design and in silico screening of drug target molecules, concordance with wet experimental data is important to provide insights on unique perspectives derived from calculations. Fragment molecular orbital (FMO) method is a quantum chemical method that facilitates precise energy calculations. Fragmentation method makes it possible to apply the quantum chemical method to biological macromolecules for energy calculation based on the electron behavior. Furthermore, interaction energies calculated on a residue-by-residue basis via fragmentation aid in the analysis of interactions between the target and ligand molecule residues and molecular design. In this review, we outline the recent developments in SBDD and FMO methods and highlight the prospects of developing machine learning approaches for large computational data using the FMO method.

Interaction Analysis by Fragment Molecular Orbital Method for Drug Discovery Research.

The use of computational methods in drug discovery research has increased substantially in recent years. Computational chemistry techniques, such as quantum chemical calculations and molecular dynamics simulations, continue to be widely used. In this review, we focused on drug discovery-related studies that employ fragment molecular orbital methods. Furthermore, we focused on inhibitor discovery, protein-protein interaction analysis, including antigen-antibody interaction analysis, and integration with molecular dynamics simulations.

Influence of Solvent Polarity on the Conformer Ratio of Bicalutamide in Saturated Solutions: Insights from NOESY NMR Analysis and Quantum-Chemical Calculations.

The study presents a thorough and detailed analysis of bicalutamide's structural and conformational properties. Quantum chemical calculations were employed to explore the conformational properties of the molecule, identifying significant energy differences between conformers. Analysis revealed that hydrogen bonds stabilise the conformers, with notable variations in torsion angles. Conformers were classified into 'closed' and 'open' types based on the relative orientation of the cyclic fragments. NOE spectroscopy in different solvents (CDCl3 and DMSO-d6) was used to study the conformational preferences of the molecule. NOESY experiments provided the predominance of 'closed' conformers in non-polar solvents and a significant presence of 'open' conformers in polar solvents. The proportions of open conformers were 22.7 ± 3.7% in CDCl3 and 59.8 ± 6.2% in DMSO-d6, while closed conformers accounted for 77.3 ± 3.7% and 40.2 ± 6.2%, respectively. This comprehensive study underscores the solvent environment's impact on its structural behaviour. The findings significantly contribute to a deeper understanding of conformational dynamics, stimulating further exploration in drug development.

Revisiting the Most Stable Structures of the Benzene Dimer.

The benzene dimer (BD) is an archetypal model of π∙∙∙π and C-H∙∙∙π noncovalent interactions as they occur in its cofacial and perpendicular arrangements, respectively. The enthalpic stabilization of the related BD structures has been debated for a long time and is revisited here. The revisit is based on results of computations that apply the coupled-cluster theory with singles, doubles and perturbative triples [CCSD(T)] together with large basis sets and extrapolate results to the complete basis set (CBS) limit in order to accurately characterize the three most important stationary points of the intermolecular interaction energy (ΔE) surface of the BD, which correspond to the tilted T-shaped (TT), fully symmetric T-shaped (FT) and slipped-parallel (SP) structures. In the optimal geometries obtained by searching extensive sets of the CCSD(T)/CBS ΔE data of the TT, FT and SP arrangements, the resulting ΔE values were -11.84, -11.34 and -11.21 kJ/mol, respectively. The intrinsic strength of the intermolecular bonding in these configurations was evaluated by analyzing the distance dependence of the CCSD(T)/CBS ΔE data over wide ranges of intermonomer separations. In this way, regions of the relative distances that favor BD structures with either π∙∙∙π or C-H∙∙∙π interactions were found and discussed in a broader context.

Ab Initio Molecular Dynamics Insight to Structural Phase Transition and Thermal Decomposition of InN.

Extensive ab initio density functional theory molecular dynamics calculations were used to evaluate stability conditions for relevant phases of InN. In particular, the p-T conditions of the thermal decomposition of InN and pressure-induced wurtzite-rocksalt solid-solid phase transition were established. The comparison of the simulation results with the available experimental data allowed for a critical evaluation of the capabilities and limitations of the proposed simulation method. It is shown that ab initio molecular dynamics can be used as an efficient tool for simulations of phase transformations of InN, including solid-solid structural transition and thermal decomposition with formation of N2 molecules. It is of high interest, because InN is an important component of epitaxial quantum structures, but it has not been obtained as a bulk single crystal. This makes it difficult to determine its basic physical properties to develop new applications.

Multi-Level Protocol for Mechanistic Reaction Studies Using Semi-Local Fitted Potential Energy Surfaces.

In this work, we propose a multi-level protocol for routine theoretical studies of chemical reaction mechanisms. The initial reaction paths of our investigated systems are sampled using the Nudged Elastic Band (NEB) method driven by a cheap electronic structure method. Forces recalculated at the more accurate electronic structure theory for a set of points on the path are fitted with a machine learning technique (in our case symmetric gradient domain machine learning or sGDML) to produce a semi-local reactive potential energy surface (PES), embracing reactants, products and transition state (TS) regions. This approach has been successfully applied to a unimolecular (Bergman cyclization of enediyne) and a bimolecular (SN2 substitution) reaction. In particular, we demonstrate that with only 50 to 150 energy-force evaluations with the accurate reference methods (here complete-active-space self-consistent field, CASSCF, and coupled-cluster singles and doubles, CCSD) it is possible to construct a semi-local PES giving qualitative agreement for stationary-point geometries, intrinsic reaction coordinates and barriers. Furthermore, we find a qualitative agreement in vibrational frequencies and reaction rate coefficients. The key aspect of the method's performance is its multi-level nature, which not only saves computational effort but also allows extracting meaningful information along the reaction path, characterized by zero gradients in all but one direction. Agnostic to the nature of the TS and computationally economic, the protocol can be readily automated and routinely used for mechanistic reaction studies.

A Polarizable QM/MM Model That Combines the State-Averaged CASSCF and AMOEBA Force Field for Photoreactions in Proteins.

This study presents the polarizable quantum mechanics/molecular mechanics (QM/MM) embedding of the state-averaged complete active space self-consistent field (SA-CASSCF) in the atomic multipole optimized energetics for biomolecular applications (AMOEBA) force field for the purpose of studying photoreactions in protein environments. We describe two extensions of our previous work that combine SA-CASSCF with AMOEBA water models, allowing it to be generalized to AMOEBA models for proteins and other macromolecules. First, we discuss how our QM/MM model accounts for the discrepancy between the direct and polarization electric fields that arises in the AMOEBA description of intramolecular polarization. A second improvement is the incorporation of link atom schemes to treat instances in which the QM/MM boundary goes through covalent bonds. A single-link atom scheme and double-link atom scheme are considered in this work, and we will discuss how electrostatic interaction, van der Waals interaction, and various kinds of valence terms are treated across the boundary. To test the accuracy of the link atom scheme, we will compare QM/MM with full QM calculations and study how the errors in ground state properties, excited state properties, and excitation energies change when tuning the parameters in the link atom scheme. We will also test the new SA-CASSCF/AMOEBA method on an elementary reaction step in NanoLuc, an artificial bioluminescence luciferase. We will show how the reaction mechanism is different when calculated in the gas phase, in polarizable continuum medium (PCM), versus in protein AMOEBA models.

Quantum modeling simulates nutrient effect of bioplastic polyhydroxyalkanoate (PHA) production in Pseudomonas putida.

Polyhydroxyalkanoates (PHAs) could be used to make sustainable, biodegradable plastics. However, the precise and accurate mechanistic modeling of PHA biosynthesis, especially medium-chain-length PHA (mcl-PHA), for yield improvement remains a challenge to biology. PHA biosynthesis is typically triggered by nitrogen limitation and tends to peak at an optimal carbon-to-nitrogen (C/N) ratio. Specifically, simulation of the underlying dynamic regulation mechanisms for PHA bioprocess is a bottleneck owing to surfeit model complexity and current modeling philosophies for uncertainty. To address this issue, we proposed a quantum-like decision-making model to encode gene expression and regulation events as hidden layers by the general transformation of a density matrix, which uses the interference of probability amplitudes to provide an empirical-level description for PHA biosynthesis. We implemented our framework modeling the biosynthesis of mcl-PHA in Pseudomonas putida with respect to external C/N ratios, showing its optimization production at maximum PHA production of 13.81% cell dry mass (CDM) at the C/N ratio of 40:1. The results also suggest the degree of P. putida's preference in channeling carbon towards PHA production as part of the bacterium's adaptative behavior to nutrient stress using quantum formalism. Generic parameters (kD, kN and theta θ) obtained based on such quantum formulation, representing P. putida's PHA biosynthesis with respect to external C/N ratios, was discussed. This work offers a new perspective on the use of quantum theory for PHA production, demonstrating its application potential for other bioprocesses.

Molecular Dynamical and Quantum Mechanical Exploration of the Site-Specific Dynamics of Cy3 Dimers Internally Linked to dsDNA.

Performing spectroscopic measurements on biomolecules labeled with fluorescent probes is a powerful approach to locating the molecular behavior and dynamics of large systems at specific sites within their local environments. The indocarbocyanine dye Cy3 has emerged as one of the most commonly used chromophores. The incorporation of Cy3 dimers into DNA enhances experimental resolution owing to the spectral characteristics influenced by the geometric orientation of excitonically coupled monomeric units. Various theoretical models and simulations have been utilized to aid in the interpretation of the experimental spectra. In this study, we employ all-atom molecular dynamics simulations to study the structural dynamics of Cy3 dimers internally linked to the dsDNA backbone. We used quantum mechanical calculations to derive insights from both the linear absorption spectra and the circular dichroism data. Furthermore, we explore potential limitations within a commonly used force field for cyanine dyes. The molecular dynamics simulations suggest the presence of four possible Cy3 dimeric populations. The spectral simulations on the four populations show one of them to agree better with the experimental signatures, suggesting it to be the dominant population. The relative orientation of Cy3 in this population compares very well with previous predictions from the Holstein-Frenkel Hamiltonian model.

Quantum mechanical electronic and geometric parameters for DNA k-mers as features for machine learning.

We are witnessing a steep increase in model development initiatives in genomics that employ high-end machine learning methodologies. Of particular interest are models that predict certain genomic characteristics based solely on DNA sequence. These models, however, treat the DNA as a mere collection of four, A, T, G and C, letters, dismissing the past advancements in science that can enable the use of more intricate information from nucleic acid sequences. Here, we provide a comprehensive database of quantum mechanical (QM) and geometric features for all the permutations of 7-meric DNA in their representative B, A and Z conformations. The database is generated by employing the applicable high-cost and time-consuming QM methodologies. This can thus make it seamless to associate a wealth of novel molecular features to any DNA sequence, by scanning it with a matching k-meric window and pulling the pre-computed values from our database for further use in modelling. We demonstrate the usefulness of our deposited features through their exclusive use in developing a model for A->C mutation rates.

Quantum Chemical and Biological Insights into Redox Activity of Metallacarborane Complexes in Cancer Cells.

A relationship between the electronic properties of metal ions in metallacarboranes and their ability to modulate mitochondrial oxidase activity and membrane hyperpolarization in cancer cells was demonstrated. Quantum chemistry methods, including DFT and molecular dynamics simulations, were used to understand the oxidized and reduced forms of metallacarboranes and their intramolecular rotatory behavior. According to the low-spin assumption for metal ions, the intramolecular oscillations of cluster ligands in metallacarboranes are significantly influenced by the type of metal and correspond to the cellular uptake of these complexes in vitro. In particular, the low-spin iron compound may be a new xenogeneic booster of redox homeostasis in cancer cells resistant to cisplatin, which induces metabolic 'exhaustion' of cancer cells and their death.

Synthesis, photophysical characterisation, quantum-chemical study and in vitro antiproliferative activity of cyclometalated Ir(III) complexes based on 3,5-dimethyl-1-phenyl-1H-pyrazole and N,N-donor ligands.

In this paper, we present the synthesis of four new complexes: the dimeric precursor [Ir(dmppz)2(µ-Cl)]2 (1) (Hdmppz - 3,5-dimethyl-1-phenyl-1H-pyrazole) and heteroleptic bis-cyclometalated complexes: [Ir(dmppz)2(Py2CO)]PF6·½CH2Cl2 (2), [Ir(dmppz)2(H2biim)]PF6·H2O (3), and [Ir(dmppz)2(PyBIm)]PF6 (4), with auxiliary N,N-donor ligands: 2-di(pyridyl)ketone (Py2CO), 2,2'-biimidazole (H2biim) and 2-(2'-pyridyl)benzimidazole (PyBIm). In the obtained complexes, SC-X-ray analysis revealed that Ir(III) has an octahedral coordination sphere with chromophores of the type {IrN2C2Cl2} (1) or {IrN4C2} (2-4). The complexes obtained, which have been fully characterised by physicochemical methods (CHN, TG, FTIR, UV-Vis, PL and 1H, 13C, 15N NMR), were used to continue our studies on the factors influencing the cytotoxic properties of potential chemotherapeutic agents (in vitro). To this end, the following studies are presented: (i) comparative analysis of the effects on the biological properties of N,N-donor ligands and C,N-donor ligands in the studied complexes, (ii) studies of the interactions of the compounds with the selected molecular target: DNA and BSA (UV-Vis, CD and PL methods), (iii) and the reactivity towards redox molecules: GSH, NADH (UV-Vis and/or ESI-MS methods), (iv) cytotoxic activity (IC50) of potential chemotherapeutics against MCF-7, K-562 and CCRF-CEM cell lines.

A physical derivation of high-flux ion transport in biological channel via quantum ion coherence.

Biological ion channels usually conduct the high-flux transport of 107 ~ 108 ions·s-1; however, the underlying mechanism is still lacking. Here, by applying the KcsA potassium channel as a typical example, and performing multitimescale molecular dynamics simulations, we demonstrate that there is coherence of the K+ ions confined in biological channels, which determines transport. The coherent oscillation state of confined K+ ions with a nanosecond-level lifetime in the channel dominates each transport event, serving as the physical basis for the high flux of ~108 ions∙s-1. The coherent transfer of confined K+ ions only takes several picoseconds and has no perturbation effect on the ion coherence, acting as the directional key of transport. Such ion coherence is allowed by quantum mechanics. An increase in the coherence can significantly enhance the ion conductance. These findings provide a potential explanation from the perspective of coherence for the high-flux ion transport with ultralow energy consumption of biological channels.

Quantum computing in bioinformatics: a systematic review mapping.

The field of quantum computing (QC) is expanding, with efforts being made to apply it to areas previously covered by classical algorithms and methods. Bioinformatics is one such domain that is developing in terms of QC. This article offers a broad mapping review of methods and algorithms of QC in bioinformatics, marking the first of its kind. It presents an overview of the domain and aids researchers in identifying further research directions in the early stages of this field of knowledge. The work presented here shows the current state-of-the-art solutions, focuses on general future directions, and highlights the limitations of current methods. The gathered data includes a comprehensive list of identified methods along with descriptions, classifications, and elaborations of their advantages and disadvantages. Results are presented not just in a descriptive table but also in an aggregated and visual format.

Multifaceted computational profiling of thymol and geraniol against the human proteome for bio-repellent alternatives: Toxicity predictions, degradation analysis, and quantum mechanical approaches.

With growing interest in natural compounds as alternative mosquito repellents, assessing the toxicity and structure of potential repellent naturals like thymol (monoterpene phenol) and geraniol (monoterpene alcohol) is vital for understanding their stability and human impact. This study aimed to determine the structural, toxicity, and binding profiles of thymol and geraniol using computational predictions, xTB metadynamics, quantum mechanics, and principal component analysis. Toxicity studies using Protox-II, T.E.S.T, and SwissADME indicated that thymol and geraniol belong to toxicity class 4 and 5, respectively, with low toxicity predictions in other endpoints. Overall pharmacokinetic profile was generated via pkCSM. Off-target predictions via SwissTarget Predictions, LigTMap, Pharmapper, and SuperPred showed that these molecules can bind to 614 human proteins. The degradation of thymol and geraniol were performed using xTB metadynamics and the outcomes showed that the degradants for both compounds were stable and had lower toxicity profile. Nine tautomers were generated via quantum mechanics for thymol and four for geraniol, with RMSD ranging from 3.8 to 6.3 Å for thymol and 3.6 to 4 Å for geraniol after superimpositions. DFT studies found that HOMO-LUMO values and electronegativity parameters of thymol and geraniol did not differ significantly from their isomers. Binding affinity studies against 614 proteins, analysed via PCA and violin plots, highlighted the probable range of binding. These multifaceted in-silico findings corroborate the stability and potential utility of thymol and geraniol as safer alternatives in repellent applications.

Analogies and Differences in the Photoactivation Mechanism of Bathy and Canonical Bacteriophytochromes Revealed by Multiscale Modeling.

Bacteriophytochromes are light-sensing biological machines that switch between two photoreversible states, Pr and Pfr. Their relative stability is opposite in canonical and bathy bacteriophytochromes, but in both cases the switch between them is triggered by the photoisomerization of an embedded bilin chromophore. We applied an integrated multiscale strategy of excited-state QM/MM nonadiabatic dynamics and (QM/)MM molecular dynamics simulations with enhanced sampling techniques to the Agrobacterium fabrum bathy phytochrome and compared the results with those obtained for the canonical phytochrome Deinococcus radiodurans. Contrary to what recently suggested, we found that photoactivation in both phytochromes is triggered by the same hula-twist motion of the bilin chromophore. However, only in the bathy phytochrome, the bilin reaches the final rotated structure already in the first intermediate. This allows a reorientation of the binding pocket in a microsecond time scale, which can propagate through the entire protein causing the spine to tilt.

SmartCADD: AI-QM Empowered Drug Discovery Platform with Explainability.

Artificial intelligence (AI) has emerged as a pivotal force in enhancing productivity across various sectors, with its impact being profoundly felt within the pharmaceutical and biotechnology domains. Despite AI's rapid adoption, its integration into scientific research faces resistance due to myriad challenges: the opaqueness of AI models, the intricate nature of their implementation, and the issue of data scarcity. In response to these impediments, we introduce SmartCADD, an innovative, open-source virtual screening platform that combines deep learning, computer-aided drug design (CADD), and quantum mechanics methodologies within a user-friendly Python framework. SmartCADD is engineered to streamline the construction of comprehensive virtual screening workflows that incorporate a variety of formerly independent techniques─spanning ADMET property predictions, de novo 2D and 3D pharmacophore modeling, molecular docking, to the integration of explainable AI mechanisms. This manuscript highlights the foundational principles, key functionalities, and the unique integrative approach of SmartCADD. Furthermore, we demonstrate its efficacy through a case study focused on the identification of promising lead compounds for HIV inhibition. By democratizing access to advanced AI and quantum mechanics tools, SmartCADD stands as a catalyst for progress in pharmaceutical research and development, heralding a new era of innovation and efficiency.

A Theoretical Exploration of the Photoinduced Breaking Mechanism of the Glycosidic Bond in Thymine Nucleotide.

DNA glycosidic bond cleavage may induce cancer under the ultraviolet (UV) effect. Yet, the mechanism of glycosidic bond cleavage remains unclear and requires more detailed clarification. Herein, quantum chemical studies on its photoinduced mechanism are performed using a 5'-thymidine monophosphate (5'-dTMPH) model. In this study, four possible paths were examined to study the glycosidic bond cleavage. The results showed that, upon excitation, the electronic transition from the π bonding to π antibonding orbitals of the thymine ring leads to the damage of the thymine ring. Afterwards, the glycosidic bond is cleaved. At first, the doublet ground state (GS) path of glycosidic bond cleavage widely studied by other groups is caused by free electron generated by photoirradiation, with a kinetically feasible energy barrier of ~23 kcal/mol. Additionally, then, the other three paths were proposed that also might cause the glycosidic bond cleavage. The first one is the doublet excited state (ES) path, triggered by free electron along with UV excitation, which can result in a very-high-energy barrier ~49 kcal/mol that is kinetically unfavorable. The second one is the singlet ES path, induced by direct UV excitation, which assumes DNA is directly excited by UV light, which features a very low-energy barrier ~16 kcal/mol that is favored in kinetics. The third one is the triplet ES path, from the singlet state via intersystem crossing (ISC), which refers to a feasible ~27 kcal/mol energy barrier. This study emphasizes the pivotal role of the DNA glycosidic bond cleavage by our proposed direct UV excitation (especially singlet ES path) in addition to the authorized indirect free-electron-induced path, which should provide essential insights to future mechanistic comprehension and novel anti-cancer drug design.

Exploring the Bonding Nature of Iron(IV)-Oxo Species through Valence Bond Calculations and Electron Density Analysis.

Compound I (Cpd I) plays a pivotal role in substrate transformations within the catalytic cycle of cytochrome P450 enzymes (P450s). A key constituent of Cpd I is the iron(IV)-oxo unit, a structural motif also found in other heme enzymes and nonheme enzymes. In this study, we performed ab initio valence bond (VB) calculations, employing the valence bond self-consistent field (VBSCF) and breathing orbital valence bond (BOVB) methods, to unveil the bonding nature of this vital "Fe(IV)═O″ unit in bioinorganic chemistry. Comparisons were drawn with the triplet O2 molecule, which shares some electronic characteristics with iron(IV)-oxo. Additionally, Cpd I models of horseradish peroxidase (HRP) and catalase (CAT) were analyzed to assess the proximal ligand effect on the electronic structure of iron(IV)-oxo. Our VB analysis underscores the significant role of noncovalent resonance effects in shaping the iron(IV)-oxo bonding. The resonance stabilization within the π and σ frameworks occurs to comparable degrees, with additional stabilization resulting from resonance between VB structures from these frameworks. Furthermore, we elucidated the substantial influence of proximal and equatorial ligands in modulating the relative significance of different VB structures. Notably, in the presence of these ligands, iron(IV)-oxo is better described as iron(III)-oxyl or iron(II)-oxygen, displaying weak covalent character but enhanced by resonance effects. Although both species exhibit diradicaloid characters, resonance stabilization in iron(IV)-oxo is weaker than in O2. Further exploration using the Laplacian of electron density shows that, unlike O2, which exhibits a charge concentration region between its two oxygen atoms, iron(IV)-oxo species display a charge depletion region.