DL_POLY: Application to molecular simulation

Non-Aufbau electronic structure in radical enzymes and control of the highly reactive intermediates

Radicals are highly reactive, short-lived chemical species that normally react indiscriminately with biological materials, and yet, nature has evolved thousands of enzymes that employ radicals to catalyze thermodynamically challenging chemistry. How these enzymes harness highly reactive radical intermediates to steer the catalysis to the correct outcome is a topic of intense investigation. Here, the results of detailed QM/MM calculations on archetype radical B12-enzymes are presented that provide new insights into how these enzymes control the reactivity of radicals within their active sites. The catalytic cycle in B12-enzymes is initiated through the formation of the 5'-deoxyadenosyl (Ado˙) moiety, a primary carbon-centred radical, which must migrate up to 8 Å to reach the target substrate to engage in the next step of the catalytic process, a hydrogen atom abstraction. Our calculations reveal that Ado˙ within the protein environment exhibits an unusual non-Aufbau electronic structure in which the singly occupied molecular orbital is lower in energy than the doubly occupied orbitals, an uncommon phenomenon known as SOMO-HOMO inversion (SHI). We find that the magnitude of SHI in the initially formed Ado˙ is larger compared to when the Ado˙ is near the intended substrate, leading to the former being relatively less reactive. The modulation of the SHI originates from Coulombic interactions of a quantum nature between a negative charge on a conserved glutamate residue and the spin on the Ado˙. Our findings support a novel hypothesis that these enzymes utilize this quantum Coulombic effect as a means of maintaining exquisite control over the chemistry of highly reactive radical intermediates in enzyme active sites.

Computational Insights into the Intramolecular Aromatic C-C Coupling Catalyzed by the Cytochrome P450 Enzyme CYP121 from Mycobacterium tuberculosis

CYP121 is a P450 enzyme that catalyzes the intramolecular C-C coupling of its native substrate, dicyclotyrosine (cYY). According to previous suggestions, when the cosubstrate peracetic acid was used to generate Cpd I, the substrate cYY was suggested to participate in the cleavage of the O-O bond; however, whether cYY is involved in the formation of Cpd I and how two distant aromatic carbon atoms are activated are still unclear. Here, we constructed computational models and performed QM/MM calculations to clarify the reaction mechanism. On the basis of our calculation results, cYY is not involved in the formation of Cpd I, and the C-C coupling reaction starts from hydrogen abstraction. In the second stage, the substrate should first undergo a complex conformational change, leading to two phenolic hydroxyls of cYY close to each other. In the subsequent reaction, the resultant Cpd II again abstracts a hydrogen atom from the proximal tyrosine to generate the diradical intermediate. In addition, the C-C coupling occurs in the active site, but the final aromatization may be a nonenzymatic reaction. In general, the intramolecular C-C coupling requires two basic conditions, including the active site having good flexibility and the substrate itself having a suitable and rotatable skeleton.

Unraveling relationship between complex lifetimes and microscopic diffusion in deep eutectic solvents

Aqueous mixtures of deep eutectic solvents (DESs) have emerged as a subject of interest in recent years for their tailored physicochemical properties. However, a comprehensive understanding of water's multifaceted influence on the microscopic dynamics, including its impact on improved transport properties of the DES, remains elusive. Additionally, the diffusion mechanisms within DESs manifest heterogeneous behavior, intricately tied to the formation and dissociation kinetics of complexes and hydrogen bonds. Therefore, it is imperative to explore the intricate interplay between bond kinetics, diffusion mechanism, and dynamical heterogeneity. This work employs water as an agent to explore their relationships by studying various relaxation phenomena in a DES based on acetamide and lithium perchlorate over a wide range of water concentrations. Notably, acetamide exhibits Fickian yet non-Gaussian diffusion across all water concentrations with Fickian (τf) and Gaussian (τg) timescales following a power-law relationship, τg∝τfγ, γ ∼ 1.4. The strength of coupling between bond kinetics and different diffusion timescales is estimated through various power-law relationships. Notably, acetamide-water hydrogen bond lifetime is linked to diffusive timescales through a single power-law over the entire water concentration studied. However, the relationship between diffusive timescales and the lifetime of acetamide-lithium complexes shows a sharp transition in behavior at 20 wt. % water, reflecting a change from vehicular diffusion below this concentration to structural diffusion above it. Our findings emphasize the critical importance of understanding bond dynamics within DESs, as they closely correlate with and regulate the molecular diffusion processes within these systems.

Vaccine design and development: Exploring the interface with computational biology and AI

Computational biology involves applying computer science and informatics techniques in biology to understand complex biological data. It allows us to collect, connect, and analyze biological data at a large scale and build predictive models. In the twenty first century, computational resources along with Artificial Intelligence (AI) have been widely used in various fields of biological sciences such as biochemistry, structural biology, immunology, microbiology, and genomics to handle massive data for decision-making, including in applications such as drug design and vaccine development, one of the major areas of focus for human and animal welfare. The knowledge of available computational resources and AI-enabled tools in vaccine design and development can improve our ability to conduct cutting-edge research. Therefore, this review article aims to summarize important computational resources and AI-based tools. Further, the article discusses the various applications and limitations of AI tools in vaccine development.

The Unique Role of the Second Coordination Sphere to Unlock and Control Catalysis in Nonheme Fe(II)/2-Oxoglutarate Histone Demethylase KDM2A

Nonheme Fe(II) and 2-oxoglutarate (2OG)-dependent histone lysine demethylases 2A (KDM2A) catalyze the demethylation of the mono- or dimethylated lysine 36 residue in the histone H3 peptide (H3K36me1/me2), which plays a crucial role in epigenetic regulation and can be involved in many cancers. Although the overall catalytic mechanism of KDMs has been studied, how KDM2 catalysis takes place in contrast to other KDMs remains unknown. Understanding such differences is vital for enzyme redesign and can help in enzyme-selective drug design. Herein, we employed molecular dynamics (MD) and combined quantum mechanics/molecular mechanics (QM/MM) to explore the complete catalytic mechanism of KDM2A, including dioxygen diffusion and binding, dioxygen activation, and substrate oxidation. Our study demonstrates that the catalysis of KDM2A is controlled by the conformational change of the second coordination sphere (SCS), specifically by a change in the orientation of Y222, which unlocks the 2OG rearrangement from off-line to in-line mode. The study demonstrates that the variant Y222A makes the 2OG rearrangement more favorable. Furthermore, the study reveals that it is the size of H3K36me3 that prevents the 2OG rearrangement, thus rendering the enzyme inactivity with trimethylated lysine. Calculations show that the SCS and long-range interacting residues that stabilize the HAT transition state in KDM2A differ from those in KDM4A, KDM7B, and KDM6A, thus providing the basics for the enzyme-selective redesign and modulation of KDM2A without influencing other KDMs.

Molecular Insights into Converting Hydroxide Adenosyltransferase into Halogenase

Halogenation plays a unique role in the design of agrochemicals. Enzymatic halogenation reactions have attracted great attention due to their excellent specificity and mild reaction conditions. S-adenosyl-l-methionine (SAM)-dependent halogenases mediate the nucleophilic attack of halide ions (X-) to SAM to produce 5'-XDA. However, only 11 SAM-dependent fluorinases and 3 chlorinases have been reported, highlighting the desire for additional halogenases. SAM-dependent hydroxide adenosyltransferase (HATase) has a similar reaction mechanism as halogenases but uses water as a substrate instead of halide ions. Here, we explored a HATase from the thermophile Thermotoga maritima MSB8 and transformed it into a halogenase. We identified a key dyad W8L/V71T for the halogenation reaction. We also obtained the best performing mutants for each halogenation reaction: M1, M2 and M4 for Cl-, Br- and I-, respectively. The M4 mutant retained the thermostability of HATase in the iodination reaction at 80 °C, which surpasses the natural halogenase SalL. QM/MM revealed that these mutants bind halide ions with more suitable angles for nucleophilic attack of C5' of SAM, thus conferring halogenation capabilities. Our work achieved the halide ion specificity of halogenases and generated thermostable halogenases for the first time, which provides new opportunities to expand the halogenase repertoire from hydroxylase.

XMECP: Reaching State-of-the-Art MECP Optimization in Multiscale Complex Systems

The Python-based program, XMECP, is developed for realizing robust, efficient, and state-of-the-art minimum energy crossing point (MECP) optimization in multiscale complex systems. This article introduces the basic capabilities of the XMECP program by theoretically investigating the MECP mechanism of several example systems including (1) the photosensitization mechanism of benzophenone, (2) photoinduced proton-coupled electron transfer in the cytosine-guanine base pair in DNA, (3) the spin-flip process in oxygen activation catalyzed by an iron-containing 2-oxoglutarate-dependent oxygenase (Fe/2OGX), and (4) the photochemical pathway of flavoprotein adjusted by the intensity of an external electric field. MECPs related to multistate reaction and multistate reactivity in large-scale complex biochemical systems can be well-treated by workflows suggested by the XMECP program. The branching plane updating the MECP optimization algorithm is strongly recommended as it provides derivative coupling vector (DCV) with explicit calculation and can equivalently evaluate contributions from non-QM residues to DCV, which can be nonadiabatic coupling or spin-orbit coupling in different cases. In the discussed QM/MM examples, we also found that the influence on the QM region by DCV can occur through noncovalent interactions and decay with distance. In the example of DNA base pairs, the nonadiabatic coupling occurs across the π-π stacking structure formed in the double-helix system. In contrast to general intuition, in the example of Fe/2OGX, the central ferrous and oxygen part contribute little to the spin-orbit coupling; however, a nearby arginine residue, which is treated by molecular mechanics in the QM/MM method, contributes significantly via two hydrogen bonds formed with α-ketoglutarate (α-KG). This indicates that the arginine residue plays a significant role in oxygen activation, driving the initial triplet state toward the productive quintet state, which is more than the previous knowledge that the arginine residue can bind α-KG at the reaction site by hydrogen bonds.

QM/MM-Based Energy Decomposition Analysis Method for Large Systems

In this work, a QM/MM-based EDA method, called GKS-EDA(QM/MM), is proposed. As an extension of GKS-EDA, this scheme divides the total interaction energy into electrostatic, exchange-repulsion, polarization, and correlation/dispersion terms. GKS-EDA(QM/MM) can be applied to describe the interactions of large-scale systems combined with various QM/MM platforms. By using the examples of a hydrated hydronium ion complex in water solution, the barnase-barstar complex, and MMP-13-pyrimidinetrione in a metalloprotein, the capability of GKS-EDA(QM/MM) for various interactions in large systems is validated.

Substrate Conformational Switch Enables the Stereoselective Dimerization in P450 NascB: Insights from Molecular Dynamics Simulations and Quantum Mechanical/Molecular Mechanical Calculations

P450 NascB catalyzes the coupling of cyclo-(l-tryptophan-l-proline) (1) to generate (-)-naseseazine C (2) through intramolecular C-N bond formation and intermolecular C-C coupling. A thorough understanding of its catalytic mechanism is crucial for the engineering or design of P450-catalyzed C-N dimerization reactions. By employing MD simulations, QM/MM calculations, and enhanced sampling, we assessed various mechanisms from recent works. Our study demonstrates that the most favorable pathway entails the transfer of a hydrogen atom from N7-H to Cpd I. Subsequently, there is a conformational change in the substrate radical, shifting it from the Re-face to the Si-face of N7 in Substrate 1. The Si-face conformation of Substrate 1 is stabilized by the protein environment and the π-π stacking interaction between the indole ring and heme porphyrin. The subsequent intermolecular C3-C6' bond formation between Substrate 1 radical and Substrate 2 occurs via a radical attack mechanism. The conformational switch of the Substrate 1 radical not only lowers the barrier of the intermolecular C3-C6' bond formation but also yields the correct stereoselectivity observed in experiments. In addition, we evaluated the reactivity of the ferric-superoxide species, showing it is not reactive enough to initiate the hydrogen atom abstraction from the indole NH group of the substrate. Our simulation provides a comprehensive mechanistic insight into how the P450 enzyme precisely controls both the intramolecular C-N cyclization and intermolecular C-C coupling. The current findings align with the available experimental data, emphasizing the pivotal role of substrate dynamics in governing P450 catalysis.

Multiscale Molecular Dynamics Simulations of Ice-Binding Proteins

Ice-binding proteins (IBPs) are a diverse class of proteins that are essential for the survival of organisms in cold conditions. IBPs are diverse in their function and can prevent or promote ice growth and selectively bind to specific crystallographic planes of the growing ice lattice. Moreover, IBPs are widely utilized to modulate ice crystal growth and recrystallization in the food industry and as cryoprotectants to preserve biological matter. A key unresolved aspect of the mode of action is how the ice-binding sites of these proteins distinguish between ice and water and interact with multiple crystal facets of the ice. The use of molecular dynamics (MD) simulation allows us to thoroughly investigate the binding mechanism and energetics of ice-binding proteins, to complement and expand on the mechanistic understandings gained from experiments. In this chapter, we describe a series of molecular dynamics simulation methodologies to investigate the mechanism of action of ice-binding proteins. Specifically, we provide detailed instructions to set up MD simulations to study the binding and interaction of ice-binding proteins using atomistic and coarse-grained simulations.

Catalytic Mechanism of Collagen Hydrolysis by Zinc(II)-Dependent Matrix Metalloproteinase-1

Human matrix metalloproteinase-1 (MMP-1) is a zinc(II)-dependent enzyme that catalyzes collagenolysis. Despite the availability of extensive experimental data, the mechanism of MMP-1-catalyzed collagenolysis remains poorly understood due to the lack of experimental structure of a catalytically productive enzyme-substrate complex of MMP-1. In this study, we apply molecular dynamics and combined quantum mechanics/molecular mechanics to reveal the reaction mechanism of MMP-1 based on a computationally modeled structure of the catalytically competent complex of MMP-1 that contains a large triple-helical peptide substrate. Our proposed mechanism involves the participation of an auxiliary (second) water molecule (wat2) in addition to the zinc(II)-coordinated water (wat1). The reaction initiates through a proton transfer to Glu219, followed by a nucleophilic attack by a zinc(II)-coordinated hydroxide anion nucleophile at the carbonyl carbon of the scissile bond, leading to the formation of a tetrahedral intermediate (IM2). The process continues with a hydrogen-bond rearrangement to facilitate proton transfer from wat2 to the amide nitrogen of the scissile bond and, finally, C-N bond cleavage. The calculations indicate that the rate-determining step is the water-mediated nucleophilic attack with an activation energy barrier of 22.3 kcal/mol. Furthermore, the calculations show that the hydrogen-bond rearrangement/proton-transfer step can proceed in a consecutive or concerted manner, depending on the conformation of the tetrahedral intermediate, with the consecutive mechanism being energetically preferable. Overall, the study reveals the crucial role of a second water molecule and the dynamics for effective MMP-1-catalyzed collagenolysis.

Identical Diffusion Distributions and Co-Cluster Formation Dictate Azeotrope Formation: Microscopic Evidences and Experimental Signatures

What selects azeotropic pairs and governs the azeotropic conditions (composition and temperature) is an open and intriguing question. A combined simulation and experimental work presented here investigates this by considering ethanol-water mixtures. We find identical distributions of center-of-mass diffusion coefficients for ethanol and water molecules under the azeotropic condition (95.5 wt % ethanol +4.5 wt % water, Tazeo = 351.1K). Moreover, the particle displacements show strong interspecies correlations at Tazeo. Interestingly, simulated reorientation time distributions become identical at Tazeo but at a composition different from that at which the translational diffusion distributions overlapped. Cluster analyses indicate that solutions at Tazeo with xwater ≤ 15 wt % are more microheterogeneous than those with higher water content, although no anomaly in the composition-dependent solution structural properties was detected. Ethanol-water and ethanol-ethanol interaction energies show pronounced nonideal composition dependence, but the size of the relative fluctuations in them remained small (∼0.5kBT). Rare water-water H-bonding, predominant water-ethanol H-bonding, and a sizable population of "free" water molecules characterize the azeotropic solutions. The red edge excitation spectroscopic (REES) measurements with a dissolved anionic fluorescent dye, coumarin343 (C343), support the predicted solution microheterogeneity by showing a nonmonotonic composition dependence of the excitation energy-induced changes in the fluorescence emission spectral frequencies and bandwidths, the largest changes being under the azeotropic condition. Subsequent dynamic anisotropy measurements reveal a nonmonotonic composition dependence of C343 rotation times with a peak under the azeotropic condition. In summary, equalization of the component translational diffusion coefficients and solution microheterogeneity with regular composition dependence of the solution structure appear to characterize the ethanol-water azeotrope.

Data on the intermolecular interactions of 1,1,1,2-tetrafluoroethane liquids from molecular dynamics simulations

Detailed atomistic interactions of 1,1,1,2-tetrafluoroethane (HFA-134a) liquid were presented in a data format, namely, DL_ANALYSER Notation for Atomic Interactions (DANAI), that annotates precisely the nature of interactions that is discoverable and searchable without having to resolve to diagrammatic illustrations. The datasets were obtained from raw atomic trajectory files of HFA-134a pure liquid models produced by using DL_POLY molecular dynamics software package. The trajectory datafiles contain expressions of atomic species in a natural chemical sense, and hence, provide localized key interactions, 'at a glance', of the liquid model on otherwise a typically disordered system consists of complex network of intermolecular interactions. The data provide insights to detailed structural behavior of molecules in liquid phase, and can be used as cheminformatics comparative investigations, linking to other molecular system models that contain similar interaction types and chemical species. This can form the foundation of investigations into the role of HFA-134a plays within different applications. For example, it can be used to compare structural and atomic interaction differences with alternative refrigerants, or as liquid propellants in pharmaceutical devices when solvating formulation ingredients.

Characterization and structure-based protein engineering of a regiospecific saponin acetyltransferase from Astragalus membranaceus

Acetylation contributes to the bioactivity of numerous medicinally important natural products. However, little is known about the acetylation on sugar moieties. Here we report a saponin acetyltransferase from Astragalus membranaceus. AmAT7-3 is discovered through a stepwise gene mining approach and characterized as the xylose C3'/C4'-O-acetyltransferse of astragaloside IV (1). To elucidate its catalytic mechanism, complex crystal structures of AmAT7-3/1 and AmAT7-3A310G/1 are obtained, which reveal a large active pocket decided by a specific sequence AADAG. Combining with QM/MM computation, the regiospecificity of AmAT7-3 is determined by sugar positioning modulated by surrounding amino acids including #A310 and #L290. Furthermore, a small mutant library is built using semi-rational design, where variants A310G and A310W are found to catalyze specific C3'-O and C4'-O acetylation, respectively. AmAT7-3 and its variants are also employed to acetylate other bioactive saponins. This work expands the understanding of saponin acetyltransferases, and provide efficient catalytic tools for saponin acetylation.

Insights into the Inhibitory Mechanisms of the Covalent Drugs for DNMT3A

The perturbations of DNA methyltransferase 3 alpha (DNMT3A) may cause uncontrolled gene expression, resulting in cancers and tumors. The DNMT inhibitors Azacytidine (AZA) and Zebularine (ZEB) inhibit the DNMT family with no specificities, and consequently would bring side effects during the treatment. Therefore, it is vital to understand the inhibitory mechanisms in DNMT3A to inform the new inhibitor design for DNMTs. Herein, we carried out molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) simulations to investigate the inhibitory mechanisms of the AZA and ZEB. The results were compared to the methyl transfer of cytosine. We showed how the AZA might stop the methyl transfer process, whereas the ZEB might be stuck in a methyl-transferred intermediate (IM3). The IM3 state then fails the elimination due to the unique protein dynamics that result in missing the catalytic water chain. Our results brought atomic-level insights into the mechanisms of the two drugs in DNMT3A, which could benefit the new generation of drug design for the DNMTs.

Evaluating the Transition State Stabilization/Destabilization Effects of the Electric Fields from Scaffold Residues by a QM/MM Approach

The protein scaffolds of enzymes not only provide structural support for the catalytic center but also exert preorganized electric fields for electrostatic catalysis. In recent years, uniform oriented external electric fields (OEEFs) have been widely applied to enzymatic reactions to mimic the electrostatic effects of the environment. However, the electric fields exerted by individual residues in proteins may be quite heterogeneous across the active site, with varying directions and strengths at different positions of the active site. Here, we propose a QM/MM-based approach to evaluate the effects of the electric fields exerted by individual residues in the protein scaffold. In particular, the heterogeneity of the residue electric fields and the effect of the native protein environment can be properly accounted for by this QM/MM approach. A case study of the O-O heterolysis reaction in the catalytic cycle of TyrH shows that (1) for scaffold residues that are relatively far from the active site, the heterogeneity of the residue electric field in the active site is not very significant and the electrostatic stabilization/destabilization due to each residue can be well approximated with the interaction energy between a uniform electric field and the QM region dipole; (2) for scaffold residues near the active site, the residue electric fields can be highly heterogeneous along the breaking O-O bond. In such a case, approximating the residue electric fields as uniform fields may misrepresent the overall electrostatic effect of the residue. The present QM/MM approach can be applied to evaluate the residues' electrostatic impact on enzymatic reactions, which also can be useful in computational optimization of electric fields to boost the enzyme catalysis.

Computational Study of the Fe(II) and α-Ketoglutarate-Dependent Aryloxyalkanoate Dioxygenase (AAD-1) in the Degradation of the Herbicide 2,4-Dichlorophenoxyacetic Acid

The AAD-1 enzyme belongs to the Fe(II) and α-ketoglutarate (Fe/αKG)-dependent nonheme aryloxyalkanoate dioxygenase family (AADs), which catalyzes the breakdown of 2,4-dichlorophenoxyacetic acid (2,4-D, an active ingredient of thousands of commercial herbicides) by using the highly active Fe(IV)═O complex. Multiple species of bacteria degrade 2,4-D via a pathway initiated by AADs; however, the detail of how they promote the cleavage of the ether C-O bond to generate 2,4-dichlorophenol (2,4-DCP) and glyoxylate is still unclear, which is the prerequisite for the further degradation of these halogenated aromatics. In this work, based on the crystal structure of AAD-1, the computational models were constructed, and a series of QM/MM and QM-only calculations were performed to explore the cleavage of the ether bond in 2,4-D with the catalysis of AAD-1. Our calculations reveal that AAD-1 may be only responsible for the hydroxylation of the substrate to generate the intermediate hemiacetal, which corresponds to an overall energy barrier of 14.2 kcal/mol on the quintet state surface, and the decomposition of the hemiacetal in the active site center of AAD-1 was calculated to be rather slow, corresponding to an energy barrier of 24.5 kcal/mol. In contrast, the decomposition of the free hemiacetal molecule in a solvent was calculated to be quite easy. Whether the decomposition of the hemiacetal occurs inside or outside the activation site is still worthy of experimental verification.

Thermal Conductivities of Uniform and Random Sulfur Crosslinking in Polybutadiene by Molecular Dynamic Simulation

Thermal conductivities of polybutadiene crosslinked with sulfur as a function of the heat flux autocorrelation function by using an equilibrium molecular dynamic (EMD) simulation were investigated. The Green-Kubo method was used to calculate thermal conductivities. All simulations were performed by applying the LAMMPS software (version 3 Mar 2020) package. The united-atom force field (OPLS-UA) from the Moltemplate software (version 2.20.3) was applied in the simulations. The influence of uniform and random distributions of sulfur in polybutadiene on the final value of thermal conductivities was studied by polymeric model structures with similar and variable degrees of crosslinking. The results showed that for identical degrees of crosslinking, the distribution of crosslinkers in the polymeric model structures significantly influenced the final value of thermal conductivity. Moreover, the influence of the crosslinking degree on the final value of thermal conductivity was studied by considering polymeric model structures with different degrees of crosslinking. The results demonstrate that by having a random distribution of sulfur, the thermal conductivity will be enhanced. However, by increasing the degree of crosslinking to the higher percentage in random crosslinked model structures, the value of thermal conductivity drops significantly due to possible higher crystallization of the model structures, which decrease the degree of freedom for phonon contributions.

How the Conformational Movement of the Substrate Drives the Regioselective C-N Bond Formation in P450 TleB: Insights from Molecular Dynamics Simulations and Quantum Mechanical/Molecular Mechanical Calculations

P450 TleB catalyzes the oxidative cyclization of the dipeptide N-methylvalyl-tryptophanol into indolactam V through selective intramolecular C-H bond amination at the indole C4 position. Understanding its catalytic mechanism is instrumental for the engineering or design of P450-catalyzed C-H amination reactions. Using multiscale computational methods, we show that the reaction proceeds through a diradical pathway, involving a hydrogen atom transfer (HAT) from N1-H to Cpd I, a conformational transformation of the substrate radical species, and a second HAT from N13-H to Cpd II. Intriguingly, the conformational transformation is found to be the key to enabling efficient and selective C-N coupling between N13 and C4 in the subsequent diradical coupling reaction. The underlined conformational transformation is triggered by the first HAT, which proceeds with an energy-demanding indole ring flip and is followed by the facile approach of the N13-H group to Cpd II. Detailed analysis shows that the internal electric field (IEF) from the protein environment plays key roles in the transformation process, which not only provides the driving force but also stabilizes the flipped conformation of the indole radical. Our simulations provide a clear picture of how the P450 enzyme can smartly modulate the selective C-N coupling reaction. The present findings are in line with all available experimental data, highlighting the crucial role of substrate dynamics in controlling this highly valuable reaction.

Fundamentals behind the specificity of Cysteinyl-tRNA synthetase: MD and QM/MM joint investigations

Cysteinyl-tRNA synthetase (CysRS) catalyzes the aminoacylation reaction of cysteine to its cognate tRNA^Cys in the first step of protein translation. It is found that CysRS is different from other aaRSs as it transfers cysteine without the need for an editing reaction, which is not applicable in the case of serine despite the similarity in their structures. Surprisingly, the reasons why CysRS has high amino acid specificity are not clear yet. In this research, the binding configurations of Cys-AMP and its near-cognate amino acid Ser-AMP with CysRS are compared by Molecular Dynamics (MD). The results reveal that CysRS screens the substrate Cys-AMP to a certain extent in the process of combination and recognition, thus providing a guarantee for the high selectivity of the next reaction. While Ser-AMP is in a folded state in CysRS. In the meanwhile, the interaction between Cys-AMP and Zn963 in CysRS is much stronger than Ser-AMP. The substrate-assisted aminoacylation mechanism in CysRS is also explored by Quantum Mechanics/Molecular Mechanics (QM/MM) modeling. According to the QM/MM potential energies, the energy barrier of TS_Cys-AMP is 91.75 kJ/mol, while that of TS_Ser-AMP is close to 150 kJ/mol. Based on thermochemistry calculations, it is found that the product of Cys-AMP is more stable than the reactant. In contrast, Ser-AMP has a reactant that is more stable than its product. As a result, it reflects that the specificity of CysRS originates from both the kinetic and thermodynamical perspectives of the reaction. Our investigations demonstrate comprehensively on how CysRS recognizes and catalyzes the substrate Cys-AMP, hoping to provide some guidance for researchers in this area.

Cellulose Iβ microfibril interaction with pristine graphene in water: Effects of amphiphilicity by molecular simulation

Graphene-cellulose interactions have considerable potential in the development of new materials. In previous computational work (Biomacromolecules2016, 16, 1771), we predicted that the model 100 hydrophobic surface of cellulose interacted favourably with pristine graphene in aqueous solution molecular dynamics simulations; conversely, a model of the hydrophilic 010 surface of cellulose exhibited progressive rearrangement to present a more hydrophobic face with the graphene, with weakened hydrogen bonds between cellulose chains and partial permeation of water. Here, we extend this work by simulating the interaction in aqueous solution of the amphiphilic 110 surface of a cellulose Iβ microfibril model, comprising 36 chains of 40 glucosyl residues, with an infinite sheet of pristine graphene. This face of the microfibril is of intermediate hydrophilicity and progressively associates with graphene over replicate simulations. As cellulose chains adhere to the graphene surface, forming interactions via its CH and OH groups, we observe a degree of local and global untwisting of the microfibril. Complementary rippling of the graphene surface is also observed, as it adapts to interaction with the microfibril. This adsorption process is accompanied by increased exclusion of water between cellulose and graphene although some water localises between chains at the immediate interface. The predicted propensity of a cellulose microfibril to adsorb spontaneously on the graphene surface, with mutual structural accommodation, highlights the amphiphilic nature of cellulose and the types of interactions that can be harnessed to design new graphene-carbohydrate biopolymer materials.

Influence of Solvent on Selective Catalytic Reduction of Nitrogen Oxides with Ammonia over Cu-CHA Zeolite

The copper-exchanged zeolite Cu-CHA has received considerable attention in recent years, owing to its application in the selective catalytic reduction (SCR) of NO_x species. Here, we study the NH₃-SCR reaction mechanism on Cu-CHA using the hybrid quantum mechanical/molecular mechanical (QM/MM) technique and investigate the effects of solvent on the reactivity of active Cu species. To this end, a comparison is made between water- and ammonia-solvated and bare Cu species. The results show the promoting effect of solvent on the oxidation component of the NH₃-SCR cycle since the formation of important nitrate species is found to be energetically more favorable on the solvated Cu sites than in the absence of solvent molecules. Conversely, both solvent molecules are predicted to inhibit the reduction component of the NH₃-SCR cycle. Diffuse reflectance infrared fourier-transform spectroscopy (DRIFTS) experiments exploiting (concentration) modulation excitation spectroscopy (MES) and phase-sensitive detection (PSD) identified spectroscopic signatures of Cu-nitrate and Cu-nitrosamine (H₂NNO), important species which had not been previously observed experimentally. This is further supported by the QM/MM-calculated harmonic vibrational analysis. Additional insights are provided into the reactivity of solvated active sites and the formation of key intermediates including their formation energies and vibrational spectroscopic signatures, allowing the development of a detailed understanding of the reaction mechanism. We demonstrate the role of solvated active sites and their influence on the energetics of important species that must be explicitly considered for an accurate understanding of NH₃-SCR kinetics.

PyMM: An Open-Source Python Program for QM/MM Simulations Based on the Perturbed Matrix Method

Quantum mechanical/molecular mechanics (QM/MM) methods are important tools in molecular modeling as they are able to couple an extended phase space sampling with an accurate description of the electronic properties of the system. Here, we describe a Python software package, called PyMM, which has been developed to apply a QM/MM approach, the perturbed matrix method, in a simple and efficient way. PyMM requires a classical atomic trajectory of the whole system and a set of unperturbed electronic properties of the ground and electronic excited states. The software output includes a set of the most common perturbed properties, such as the electronic excitation energies and the transitions dipole moments, as well as the eigenvectors describing the perturbed electronic states, which can be then used to estimate whatever electronic property. The software is composed of a simple and complete command-line interface, a set of internal input validation, and three main analyses focusing on (i) the perturbed eigenvector behavior, (ii) the calculation of the electronic absorption spectrum, and (iii) the estimation of the free energy differences along a reaction coordinate.

Modulation of Diffusion Mechanism and Its Correlation with Complexation in Aqueous Deep Eutectic Solvents

Aqueous mixtures of deep eutectic solvents (DESs) have gained traction recently as an effective template to tailor their physicochemical properties. But detailed microscopic insights into the effects of water on the molecular relaxation phenomenon in DESs are not entirely understood. DESs are strong network-forming liquids due to the extensive hydrogen bonding and complex formation between their species, and therefore, water can behave as a controlled disruptor altering the microscopic structure and dynamics in DESs. In this study, the role of water in the diffusion mechanism of acetamide in the aqueous mixtures of DESs synthesized using acetamide and lithium perchlorate is investigated using molecular dynamics (MD) simulation and quasielastic neutron scattering (QENS). The acetamide dynamics comprises localized diffusion within transient cages and a jump diffusion process across cages. The jump diffusion process is observed to be strongly enhanced by about a factor of 10 as the water content in the system is increased. Meanwhile, the geometry of the localized dynamics is unaltered by addition of water, but the localized diffusion becomes significantly faster and more heterogeneous with increasing water concentration. The accelerating effects of water on localized diffusion are also substantiated by QENS experiments. The water concentration in the DES is observed to control the solvation structure of lithium ions, with the ions becoming significantly hydrated at 20 wt % water. The formation of interwater and water-acetamide hydrogen bonds is observed. The increase in water concentration is found to increase the number of H-bonds; however, their lifetimes are found to decrease substantially. Similarly, the lifetimes of acetamide-lithium complexes are also found to be diminished by increasing water concentration. A power-law scaling relationship between lifetimes and diffusion constants is established, elucidating the extent of coupling between diffusive processes and hydrogen bonding and microscopic complexation. This study demonstrates the ability to use water as an agent to probe the role of structural relaxation and complex lifetimes of diffusive processes at different time and length scales.

Can Second Coordination Sphere and Long-Range Interactions Modulate Hydrogen Atom Transfer in a Non-Heme Fe(II)-Dependent Histone Demethylase?

Fe(II)-dependent oxygenases employ hydrogen atom transfer (HAT) to produce a myriad of products. Understanding how such enzymes use dynamic processes beyond the immediate vicinity of the active site to control the selectivity and efficiency of HAT is important for metalloenzyme engineering; however, obtaining such knowledge by experiments is challenging. This study develops a computational framework for identifying second coordination sphere (SCS) and especially long-range (LR) residues relevant for catalysis through dynamic cross-correlation analysis (DCCA) using the human histone demethylase PHF8 (KDM7B) as a model oxygenase. Furthermore, the study explores the mechanistic pathways of influence of the SCS and LR residues on the HAT reaction. To demonstrate the plausibility of the approach, we investigated the effect of a PHF8 F279S clinical mutation associated with X-linked intellectual disability, which has been experimentally shown to ablate PHF8-catalyzed demethylation. In agreement, the molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) studies showed a change in the H3_1-14K9me2 substrate orientation and an increased HAT barrier. We systematically analyzed the pathways by which the identified SCS and LR residues may influence HAT by exploring changes in H3K9me2 substrate orientation, interdomain correlated motions, HAT transition state stabilization, reaction energetics, electron transfer mechanism, and alterations in the intrinsic electric field of PHF8. Importantly, SCS and LR variations decrease key motions of α9-α12 of the JmjC domain toward the Fe(IV)-center that are associated with tighter binding of the H3_1-14K9me2 substrate. SCS and LR residues alter the intrinsic electric field of the enzyme along the reaction coordinate and change the individual energetic contributions of residues toward TS stabilization. The overall results suggest that DCCA can indeed identify non-active-site residues relevant for catalysis. The substitutions of such dynamically correlated residues might be used as a tool to tune HAT in non-heme Fe(II)- and 2OG-dependent enzymes.

Multilayer Graphtriyne Membranes for Separation and Storage of CO2: Molecular Dynamics Simulations of Post-Combustion Model Mixtures

The ability to remove carbon dioxide from gaseous mixtures is a necessary step toward the reduction of greenhouse gas emissions. As a contribution to this field of research, we performed a molecular dynamics study assessing the separation and adsorption properties of multi-layered graphtriyne membranes on gaseous mixtures of CO₂, N₂, and H₂O. These mixtures closely resemble post-combustion gaseous products and are, therefore, suitable prototypes with which to model possible technological applications in the field of CO₂ removal methodologies. The molecular dynamics simulations rely on a fairly accurate description of involved force fields, providing reliable predictions of selectivity and adsorption coefficients. The characterization of the interplay between molecules and membrane structure also permitted us to elucidate the adsorption and crossing processes at an atomistic level of detail. The work is intended as a continuation and a strong enhancement of the modeling research and characterization of such materials as molecular sieves for CO₂ storage and removal.

Applications of Molecular Dynamics Simulation in Protein Study

Molecular Dynamics (MD) Simulations is increasingly used as a powerful tool to study protein structure-related questions. Starting from the early simulation study on the photoisomerization in rhodopsin in 1976, MD Simulations has been used to study protein function, protein stability, protein-protein interaction, enzymatic reactions and drug-protein interactions, and membrane proteins. In this review, we provide a brief review for the history of MD Simulations application and the current status of MD Simulations applications in protein studies.

Prediction of the Glass Transition Temperature in Polyethylene Terephthalate/Polyethylene Vanillate (PET/PEV) Blends: A Molecular Dynamics Study

Polyethylene terephthalate (PET) is one of the most common polymers used in industries. However, its accumulation in the environment is a health risk to humans and animals. Polyethylene vanillate (PEV) is a bio-based material with topological, mechanical, and thermal properties similar to PET, allowing it to be used as a PET replacement or blending material. This study aimed to investigate some structural and dynamical properties as well as the estimated glass transition temperature (T_g) of PET/PEV blended polymers by molecular dynamics (MD) simulations with an all-atom force field model. Four blended systems of PET/PEV with different composition ratios (4/1, 3/2, 2/3, and 1/4) were investigated and compared to the parent polymers, PET and PEV. The results show that the polymers with all blended ratios have T_g values around 344–347 K, which are not significantly different from each other and are close to the T_g of PET at 345 K. Among all the ratios, the 3/2 blended polymer showed the highest number of contacting atoms and possible hydrogen bonds between the two chain types. Moreover, the radial distribution results suggested the proper interactions in this system, which indicates that this is the most suitable ratio model for further experimental studies of the PET/PEV polymer blend.

Defective Nature of CdSe Quantum Dots Embedded in Inorganic Matrices

Quantum dots (QDs) embedded in inorganic matrices have been extensively studied for their potential applications in lighting, displays, and solar cells. While a significant amount of research studies focused on their experimental fabrication, the origin of their relatively low photoluminescence quantum yield has not been investigated yet, although it severely hinders practical applications. In this study, we use time-dependent density functional theory (TDDFT) to pinpoint the nature of excited states of CdSe QDs embedded in various inorganic matrices. The formation of undercoordinated Se atoms and nonbridging oxygen atoms at the QD/glass interface is responsible for the localization of a hole wave function, leading to the formation of low-energy excited states with weak oscillator strength. These states provide pathways for nonradiative processes and compete with radiative emission. The photoluminescence performance is predicted for CdSe QDs in different matrices and validated by experiments. The results of this study have significant implications for understanding the underlying photophysics of CdSe QDs embedded in inorganic matrices that would facilitate the fabrication of highly luminescent glasses.

Water-Regulated Mechanisms for Degradation of Pesticides Paraoxon and Parathion by Phosphotriesterase: Insight from QM/MM and MD Simulations

The enzymatic degradation of pesticides paraoxon (PON) and parathion (PIN) by phosphotriesterase (PTE) has been investigated by QM/MM calculations and MD simulations. In the PTE-PON complex, Zn α and Zn β in the active site are five- and six-coordinated, respectively, while both zinc ions are six coordinated with the Zn α -bound water molecule (WT1) for the PTE-PIN system. The hydrolytic reactions for PON and PIN are respectively driven by the nucleophilic attack of the bridging-OH - and the Zn α -bound water molecule on the phosphorus center of substrate, and the two-step hydrolytic process is predicted to be the rate-limiting step with the energy spans of 13.8 and 14.4 kcal/mol for PON and PIN, respectively. The computational studies reveal that the presence of the Zn α -bound water molecule depends on the structural feature of substrates characterized by P=O and P=S, which determines the hydrolytic mechanism and efficiency for the degradation of organophosphorus pesticides by PTE.

All-Atom Molecular Dynamics Simulations on a Single Chain of PET and PEV Polymers

Polyethylene vanillic (PEV), a bio-based material, has mechanical and thermal properties similar to polyethylene terephthalate (PET), the most common polymer used in industries. The present study aimed to investigate and compare their structural dynamics and physical data using a computational approach. The simple model of a single-chain polymer containing 100 repeating units was performed by all-atom molecular dynamics (MD) simulations with refined OPLS–AA force field parameters. As a result, the flexibility of the PEV structure was greater than that of PET. PET and PEV polymers had the predicted glass transition temperature T_g values of approximately 345 K and 353 K, respectively. PEV showed a slightly higher T_g than PET, consistent with current experimental evidence.

Data-Driven Methods for Accelerating Polymer Design

Optimal design of polymers is a challenging task due to their enormous chemical and configurational space. Recent advances in computations, machine learning, and increasing trends in data and software availability can potentially address this problem and accelerate the molecular-scale design of polymers. Here, the central problem of polymer design is reviewed, and the general ideas of data-driven methods and their working principles in the context of polymer design are discussed. This Review provides a historical perspective and a summary of current trends and outlines future scopes of data-driven methods for polymer research. A few representative case studies on the use of such data-driven methods for discovering new polymers with exceptional properties are presented. Moreover, attempts are made to highlight how data-driven strategies aid in establishing new correlations and advancing the fundamental understanding of polymers. This Review posits that the combination of machine learning, rapid computational characterization of polymers, and availability of large open-sourced homogeneous data will transform polymer research and development over the coming decades. It is hoped that this Review will serve as a useful reference to researchers who wish to develop and deploy data-driven methods for polymer research and education.

Molecular basis of enzymatic nitrogen-nitrogen formation by a family of zinc-binding cupin enzymes

Molecules with a nitrogen-nitrogen (N-N) bond in their structures exhibit various biological activities and other unique properties. A few microbial proteins are recently emerging as dedicated N-N bond forming enzymes in natural product biosynthesis. However, the details of these biochemical processes remain largely unknown. Here, through in vitro biochemical characterization and computational studies, we report the molecular basis of hydrazine bond formation by a family of di-domain enzymes. These enzymes are widespread in bacteria and sometimes naturally exist as two standalone enzymes. We reveal that the methionyl-tRNA synthase-like domain/protein catalyzes ATP-dependent condensation of two amino acids substrates to form a highly unstable ester intermediate, which is subsequently captured by the zinc-binding cupin domain/protein and undergoes redox-neutral intramolecular rearrangement to give the N-N bond containing product. These results provide important mechanistic insights into enzymatic N-N bond formation and should facilitate future development of novel N-N forming biocatalyst.

Rational prioritization strategy allows the design of macrolide derivatives that overcome antibiotic resistance

Due to the development of resistance against commonly used antibiotics, new derivatives that avoid resistance mechanisms need to be developed. To address this problem, a rational prioritization strategy is outlined for macrolide antibiotics. Candidates are screened based on their solubility, membrane permeability, and binding affinity using a tiered optimization approach of free energy simulations and quantum mechanics/molecular mechanics calculations. After prioritization by computational methods, the best candidates are evaluated experimentally. The strategy creates a targeted substance library that is highly enriched in compounds with antibacterial activity. This allows for faster iterations in the development of new antibiotic derivatives.

Antibiotic resistance is a major threat to global health; this problem can be addressed by the development of new antibacterial agents to keep pace with the evolutionary adaptation of pathogens. Computational approaches are essential tools to this end since their application enables fast and early strategical decisions in the drug development process. We present a rational design approach, in which acylide antibiotics were screened based on computational predictions of solubility, membrane permeability, and binding affinity toward the ribosome. To assess our design strategy, we tested all candidates for in vitro inhibitory activity and then evaluated them in vivo with several antibiotic-resistant strains to determine minimal inhibitory concentrations. The predicted best candidate is synthetically more accessible, exhibits higher solubility and binding affinity to the ribosome, and is up to 56 times more active against resistant pathogens than telithromycin. Notably, the best compounds designed by us show activity, especially when combined with the membrane-weakening drug colistin, against Acinetobacter baumanii, Pseudomonas aeruginosa, and Escherichia coli, which are the three most critical targets from the priority list of pathogens of the World Health Organization.

Hydrolysis Mechanism of the Linkers by Matrix Metalloproteinase-9 Using QM/MM Calculations

Activatable cell-penetrating peptides (ACPPs) are known to be able to decrease the cytotoxicity of cell-penetrating peptide (CPP)-based drug delivery systems. Furthermore, they can improve the targeting of CPPs when specifically recognized and hydrolyzed by characteristic proteases. A comprehensive and profound understanding of the recognition and hydrolysis process will provide a better design of the ACPP-based drug delivery system. Previous studies have clearly described how ACPPs are recognized and bound by MMPs. However, the hydrolysis mechanism of ACPPs is still unsolved. This work focuses on a proteinase-sensitive cleavable linker of ACPPs (PLGLAG), the key structure for recognition and hydrolysis, trying to determine the mechanism by which MMP-9 hydrolyzes its substrate PLGLAG. The quantum mechanics/molecular mechanics (QM/MM) calculations herein show that MMP-9 proteolysis is a water-mediated four-step reaction. More specifically, it consists of (i) nucleophilic attack, (ii) hydrogen-bond rearrangement, (iii) proton transfer, and finally (iv) amide bond rupture. Considering the reversibility of multistep reaction, the second step (i.e., hydrogen-bond rearrangement) has the highest barrier and is the rate-limiting step in the hydrolysis of PLGLAG. The possible design and improvement of the key P1 and P1' sites are also explored through mutations. The present results indicate that, while the mutations affect the reaction energy barriers and the rate-limiting steps, all mutants considered could be hydrolyzed by MMP-9. To provide further insights, the hydrolysis mechanism of MMP-2, which has a similar hydrolysis process to that of MMP-9 but with different reaction barriers, is also studied and compared. As a result, this work provides detailed insights into the hydrolysis mechanism of ACPPs by MMP-9 and, thus, also possible insights for the development of new strategies for ACPP-based delivery systems.

QM/MM study of the reactivity of zeolite bound methoxy and carbene groups

The conversion of methanol-to-hydrocarbons (MTH) is known to occur via an autocatalytic process in zeolites, where framework-bound methoxy species play a pivotal role, especially during catalyst induction. Recent NMR and FT-IR experimental studies suggest that methoxylated zeolites are able to produce hydrocarbons by a mechanism involving carbene migration and association. In order to understand these observations, we have performed QM/MM computational investigations on a range of reaction mechanisms for the reaction of zeolite bound methoxy and carbene groups, which are proposed to initiate hydrocarbon formation in the MTH process. Our simulations demonstrate that it is kinetically unfavourable for methyl species to form on the framework away from the zeolite acid site, and both kinetically and thermodynamically unfavourable for methyl groups to migrate through the framework and aggregate around an acid site. Formation of carbene moieties was considered as an alternative pathway to the formation of C-C bonds; however, the reaction energy for conversion of a methyl to a carbene is unfavourable. Metadynamics simulations help confirm further that methyl species at the framework acid sites would be more reactive towards formed C₂₊ species, rather than inter-framework migration, and that the role of carbenes in the formation of the first C-C bond will be via a concerted type of mechanism rather than stepwise.

Water accelerates the hydrogen-bond dynamics and abates heterogeneity in deep eutectic solvent based on acetamide and lithium perchlorate

Deep eutectic solvents (DESs) have become a prevalent and promising medium in various industrial applications. The addition of water to DESs has attracted a lot of attention as a scheme to modulate their functionalities and improve their physicochemical properties. In this work, we study the effects of water on an acetamide based DES by probing its microscopic structure and dynamics using classical molecular dynamics simulation. It is observed that, at low water content, acetamide still remains the dominant solvate in the first solvation shell of lithium ions, however, beyond 10 wt. %, it is replaced by water. The increase in the water content in the solvent accelerates the H-bond dynamics by drastically decreasing the lifetimes of acetamide-lithium H-bond complexes. Additionally, water-lithium H-bond complexes are also found to form, with systematically longer lifetimes in comparison to acetamide-lithium complexes. Consequently, the diffusivity and ionic conductivity of all the species in the DES are found to increase substantially. Non-Gaussianity parameters for translational motions of acetamide and water in the DES show a conspicuous decrease with addition of water in the system. The signature of jump-like reorientation of acetamide is observed in the DES by quantifying the deviation from rotational Brownian motion. However, a notable decrease in the deviation is observed with an increase in the water content in the DES. This study demonstrates the intricate connection between H-bond dynamics and various microscopic dynamical parameters in the DES, by investigating the modulation of the former with addition of water.

An Updated Review of Computer-Aided Drug Design and Its Application to COVID-19

The recent outbreak of the deadly coronavirus disease 19 (COVID-19) pandemic poses serious health concerns around the world. The lack of approved drugs or vaccines continues to be a challenge and further necessitates the discovery of new therapeutic molecules. Computer-aided drug design has helped to expedite the drug discovery and development process by minimizing the cost and time. In this review article, we highlight two important categories of computer-aided drug design (CADD), viz., the ligand-based as well as structured-based drug discovery. Various molecular modeling techniques involved in structure-based drug design are molecular docking and molecular dynamic simulation, whereas ligand-based drug design includes pharmacophore modeling, quantitative structure-activity relationship (QSARs), and artificial intelligence (AI). We have briefly discussed the significance of computer-aided drug design in the context of COVID-19 and how the researchers continue to rely on these computational techniques in the rapid identification of promising drug candidate molecules against various drug targets implicated in the pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The structural elucidation of pharmacological drug targets and the discovery of preclinical drug candidate molecules have accelerated both structure-based as well as ligand-based drug design. This review article will help the clinicians and researchers to exploit the immense potential of computer-aided drug design in designing and identification of drug molecules and thereby helping in the management of fatal disease.

Atomistic insight into salinity dependent preferential binding of polar aromatics to calcite/brine interface: implications to low salinity waterflooding

This paper resolve the salinity-dependent interactions of polar components of crude oil at calcite-brine interface in atomic resolution. Molecular dynamics simulations carried out on the present study showed that ordered water monolayers develop immediate to a calcite substrate in contact with a saline solution. Carboxylic compounds, herein represented by benzoic acid (BA), penetrate into those hydration layers and directly linking to the calcite surface. Through a mechanism termed screening effect, development of hydrogen bonding between –COOH functional groups of BA and carbonate groups is inhibited by formation of a positively-charged Na⁺ layer over CaCO₃ surface. Contrary to the common perception, a sodium-depleted solution potentially intensifies surface adsorption of polar hydrocarbons onto carbonate substrates; thus, shifting wetting characteristic to hydrophobic condition. In the context of enhanced oil recovery, an ion-engineered waterflooding would be more effective than injecting a solely diluted saltwater.

The influence of external electric fields on proton transfer tautomerism in the guanine-cytosine base pair

The Watson-Crick base pair proton transfer tautomers would be widely considered as a source of spontaneous mutations in DNA replication if not for their short lifetimes and thermodynamic instability. This work investigates the effects external electric fields have on the stability of the guanine-cytosine proton transfer tautomers within a realistic strand of aqueous DNA using a combination of ensemble-based classical molecular dynamics (MD) coupled to quantum mechanics/molecular mechanics (QM/MM). Performing an ensemble of calculations accounts for the stochastic aspects of the simulations while allowing for easier identification of systematic errors. The methodology applied in this work has previously been shown to estimate base pair proton transfer rate coefficients that are in good agreement with recent experimental data. A range of electric fields in the order of 104 to 109 V m-1 is investigated based on their real-life medicinal applications which include gene therapy and cancer treatments. The MD trajectories confirm that electric fields up to 1.00 × 109 V m-1 have a negligible influence on the structure of the base pairs within DNA. The QM/MM results show that the application of large external electric fields (1.00 × 109 V m-1) parallel to the hydrogen bonds increases the thermodynamic population of the tautomers by up to one order of magnitude; moreover, the lifetimes of the tautomers remain insignificant when compared to the timescale of DNA replication.

QM/MM study of the stability of dimethyl ether in zeolites H-ZSM-5 and H-Y

The methanol-to-hydrocarbons (MTH) process transforms C1 carbon sources to higher hydrocarbons, but details of the mechanism that leads to the formation of the first carbon-carbon bond remain unclear. Here, we present a computational investigation of how a crucial intermediate, dimethyl ether (DME), interacts with different zeolite catalysts (H-ZSM-5, H-Y) to gain insight into the initial stages in the MTH process. We use QM/MM computational simulations to model the conversion of methanol to DME in H-ZSM-5, which is a well characterised and important reaction intermediate. We analyse and compare the stability of DME on several acid sites in H-ZSM-5 and H-Y, and show that the more acidic and open "intersection sites" in the H-ZSM-5 framework are able to bond strongest with DME, with complete deprotonation of the acid site occurring. The conversion of methanol to DME in H-ZSM-5 is calculated as requiring a higher activation energy than framework methoxylation, which indicates that a stepwise (indirect) mechanism, through a methoxy intermediate, is the most likely route to DME formation during the initiation of the MTH process.