Search Results (132)

The anion, cation, and radical structural forms of B₂N ^{(−, 0, +)} were studied in the case of symmetry breaking (SB) inside a (5, 5) BN nanotube ring and were also compared in terms of non-covalent interaction between these two parts. The non-bonded system of B₂N ^{(−, 0, +)} and the (5, 5) BN nanotube not only causes SB for BNB but also creates an energy barrier in the range of 10⁻³ Hartree of due to this non-bonded interaction. Moreover, several SBs appear via asymmetry stretching and symmetry bending normal mode interactions according to the multiple second-order Jahn–Teller effect. We also demonstrated that the twin minimum of BNB’s potential curve arises from the lack of a proper wave function with permutation symmetry, as well as abnormal charge distribution. Through this investigation, considerable enhancements in the energy barriers due to the SB effect were also observed during the electrostatic interaction of BNB (both radical and cation) with the BN nanotube ring. Additionally, these values were not observed for the isolated B₂N ^{(−, 0, +)} forms. This non-bonded complex operates as a quantum rotatory model and as a catalyst for producing a range of spectra in the IR region due to the alternative attraction and repulsion forces. Full article

The growing demand for safe and reliable weaponry has heightened performance requirements for explosives. Cocrystal systems, offering a balance between high energy density and safety, have become key targets in advanced energetic material research. However, the influence of molar ratios and crystal facets on thermal sensitivity, mechanical strength, and detonation properties remains underexplored. This study investigates cocrystals of hexanitrohexaazaisowurtzitane (CL-20) and 1,1-diamino-2,2-dinitroethylene (FOX-7) with molar ratios of 3:1, 5:1, and 8:1 on the (1 0 1) crystal facet, using the Forcite module in Materials Studio. Comparative analysis with (0 1 1) facet and pure explosives revealed that the 5:1 cocrystal achieved the highest cohesive energy density (0.773 kJ/cm³) and theoretical crystal density (1.953 g/cm³), driven by strong electrostatic and non-bonded interactions—indicating superior detonation performance. In contrast, the 3:1 cocrystal displayed optimal mechanical strength, with an elastic modulus of 8.562 GPa and shear modulus of 3.365 GPa, suitable for practical applications. The results suggest increasing CL-20 content enhances energy performance up to a point, beyond which structural loosening occurs (8:1 ratio) due to steric hindrance weakening van der Waals forces. This work clarifies how molar ratio regulates the influence between sensitivity, strength, and energy, providing guidance for designing application-specific high-energy cocrystals. Full article

Elucidating amyloid formation inside biomolecular condensates requires models that resolve (i) local, chemistry specific contacts controlling β registry and (ii) mesoscale phase behavior and cluster coalescence on microsecond timescales—capabilities beyond single resolution models. We present a hybrid united atom/coarse-grained (UA–CG) force field coupling a PACE UA peptide model with the MARTINI CG framework. Cross-resolution nonbonded parameters are first optimized against all-atom side chain potentials of mean force to balance the relative strength between different types of interactions and then refined through universal parameter scaling by matching radius of gyration distributions for specific systems. We applied this approach to simulate a recently reported model system comprising the LVFFAR₉ peptide that can co-assemble into amyloid fibrils via liquid–liquid phase separation. Our ten-microsecond simulations reveal rapid droplet formation populated by micelle-like nanostructures with its inner core composed of LVFF clusters. The nanostructures can further fuse but the fusion is reaction-limited due to an electrostatic coalescence barrier. β structures emerge once clusters exceed ~10 peptides, and the LVFFAR₉ fraction modulates amyloid polymorphism, reversing parallel versus antiparallel registry at lower LVFFAR₉. These detailed insights generated from long simulations highlight the promise of our hybrid UA–CG strategy in investigating the molecular mechanisms of condensate aging. Full article

Polyimide (PI) is widely used in aerospace, electronic packaging, and other fields due to its excellent dielectric and thermophysical properties. However, the performance of traditional PI materials under extreme conditions has become increasingly inadequate to meet the growing demands. To address this, this study designed a PI/Nano-Si₃N₄ advanced composite material and, based on molecular dynamics simulations, thoroughly explored the influence of silane coupling agents with different grafting densities on the interfacial microstructure and their correlation with the overall material’s physical properties. The results show that when the grafting density is 10%, the interfacial bonding of the PI/Nano-Si₃N₄ composite is optimized: non-bonded interaction energy increases by 18.4%, the number of hydrogen bonds increases by 32.5%, and the free volume fraction decreases to 18.13%. These changes significantly enhance the overall performance of the material, manifested by an increase of about 30 K in the glass transition temperature and a 49.5% improvement in thermal conductivity compared to pure PI. Furthermore, the system maintains high Young’s modulus and shear modulus in the temperature range of 300–700 K. The study reveals that silane coupling agents can effectively enhance the composite material’s overall performance by optimizing the interfacial structure and controlling the free volume, providing an efficient computational method for the design and performance prediction of advanced high-performance PI composites. Full article

Epoxy asphalt is a superior polymer-modified asphalt material; however, significant differences in physicochemical properties, such as solubility parameters and dielectric constants, between epoxy resin and asphalt have led to compatibility issues that hinder its development. This study employed molecular dynamics simulations to investigate the effect of maleic anhydride-grafted styrene-butadiene-styrene (MAH-g-SBS) on the compatibility of epoxy asphalt. By analyzing parameters such as cohesive energy density, solubility parameters, energy distribution, interaction energy, radial distribution function, free volume fraction, and mean square displacement, the molecular mechanism underlying the enhanced compatibility was elucidated. The results indicate that the amphiphilic molecular structure of MAH-g-SBS significantly improves the thermodynamic compatibility between asphalt and epoxy resin, enhances interfacial affinity and stability, reduces the system’s total interaction and nonbonded energies, facilitates the dispersion and permeation of epoxy molecules into asphalt, and increases molecular mobility, thereby comprehensively enhancing the compatibility of the epoxy asphalt blend. Segregation tests and fluorescence microscopy further verified the simulation results, demonstrating that MAH-g-SBS improves the storage stability and phase uniformity of the epoxy asphalt system. Full article

Density functional theory calculations were performed to elucidate the mechanistic details and origins of the selectivity of the nickel-catalyzed hydroboration of vinylarenes using B₂pin₂/MeOH. The catalytic cycles involved four sequential elementary steps: hydronickelation, anion exchange, transmetalation, and reductive elimination. Kinetic analyses identified hydronickelation as the rate-determining step with an activation barrier of 19.8 kcal/mol, while transmetalation proceeded through a stepwise mechanism characterized by two distinct transition states. Comprehensive analyses of the relevant transition structures and energetics demonstrated that the observed R-enantioselectivity (94% ee) originated from favorable nonbonding interactions. Lastly, our calculations suggested that the Markovnikov regioselectivity was predominantly governed by steric factors rather than electronic effects. Full article

The SARS-CoV-2 main protease (Mpro), essential for viral replication, remains a prime target for antiviral drug design against COVID-19 and related coronaviruses. In this study, we present a systematic investigation into the molecular determinants of Mpro inhibition using an integrated approach combining large-scale data mining, cheminformatics, and quantum chemical calculations. A curated dataset comprising 963 high-resolution structures of Mpro–ligand complexes—348 covalent and 615 non-covalent inhibitors—was mined from the Protein Data Bank. Cheminformatics analysis revealed distinct physicochemical profiles for each inhibitor class: covalent inhibitors tend to exhibit higher hydrogen bonding capacity and sp³ character, while non-covalent inhibitors are enriched in aromatic rings and exhibit greater aromaticity and lipophilicity. A novel descriptor, Weighted Hydrogen Bond Count (WHBC), normalized for molecular size, revealed a notable inverse correlation with aromatic ring count, suggesting a compensatory relationship between hydrogen bonding and π-mediated interactions. To elucidate the energetic underpinnings of molecular recognition, 40 representative inhibitors (20 covalent, 20 non-covalent) were selected based on principal component analysis and aromatic ring content. Quantum mechanical calculations at the double-hybrid B2PLYP/def2-QZVP level quantified non-bonded interaction energies, revealing that covalent inhibitors derive binding strength primarily through hydrogen bonding (~63.8%), whereas non-covalent inhibitors depend predominantly on π–π stacking and CH–π interactions (~62.8%). Representative binding pocket analyses further substantiate these findings: the covalent inhibitor F2F-2020198-00X exhibited strong hydrogen bonds with residues such as Glu166 and His163, while the non-covalent inhibitor EDG-MED-10fcb19e-1 engaged in extensive π-mediated interactions with residues like His41, Met49, and Met165. The distinct interaction patterns led to the establishment of pharmacophore models, highlighting key recognition motifs for both covalent and non-covalent inhibitors. Our findings underscore the critical role of aromaticity and non-bonded π interactions in driving binding affinity, complementing or, in some cases, substituting for hydrogen bonding, and offer a robust framework for the rational design of next-generation Mpro inhibitors with improved selectivity and resistance profiles. Full article

Manganese monoxide (MnO), a versatile manganese oxide, is highly regarded for its potential to address heavy metal and radioactive contamination effectively. In this study, we investigated the adsorption mechanism of strontium nitrate solution on MnO crystal surfaces using molecular dynamics simulations. We examined the effects of adsorption and diffusion of ions and water molecules on three distinct MnO crystal surfaces. The results revealed significant differences in the adsorption capacities of Sr²⁺, NO₃⁻, and H₂O on the MnO crystal surfaces. The radial distribution function (RDF), the non-bond interaction energy (E_int), and mean square displacement (MSD) data indicate that Sr²⁺ exhibits the strongest interaction with the MnO (111) crystal surface. This results in a shift of Sr²⁺ from outer-sphere adsorption to inner-sphere adsorption. This strong interaction is primarily due to the increase in the number and prominence of non-bridging oxygen atoms on the MnO crystal surfaces. Full article

Lactic acid bacteria exopolysaccharides (EPS) have a variety of excellent biological functions and are widely used in the food and pharmaceutical industries. The complex metabolic system of lactic acid bacteria and the mechanism of EPS biosynthesis have not been fully analyzed, which limits the wider application of EPS. EPS synthesis is regulated by cyclic diadenosine monophosphate (c-di-AMP), but the exact mechanism remains unclear. Dac and pde are c-di-AMP anabolic genes, gtfA, gtfB and gtfC are EPS synthesis gene clusters, among which gtfC was the key gene for EPS synthesis in Leuconostoc mesenteroides DRP105. In order to explore whether diadenylate cyclase (DAC) can catalyze the synthesis of c-di-AMP from ATP, the sequence of DAC was analyzed by bioinformatics based on the whole genome sequence. DAC was a CdaA type diadenylate cyclase containing the classical domain DisA_N and DGA and RHR motifs. The secondary structure was mainly composed of α-helices, and AlphaFold2 was used to model the 3D structure of the protein and evaluate the rationality of the DAC protein structure model. A total of 8 salt bridges, 21 hydrogen bonds and 221 non-bonded interactions were found between DAC and GtfC. Molecular docking simulations revealed ATP1 and ATP2 fully occupied the binding pocket of DAC and interacted directly with the binding site residues of DAC. The molecular dynamics simulations showed that the binding of DAC to ATP molecules was relatively stable. Gene and enzyme correlation analysis found that dac and gtfC gene expression were significantly positively correlated with DAC enzyme activity, c-di-AMP content and EPS production, and had no significant correlation with PDE enzyme activity responsible for c-di-AMP degradation. Bioinformatics analysis of the regulatory role of DAC in the synthesis of EPS by lactic acid bacteria was helpful to fully reveal the biosynthetic mechanism of EPS and provide theoretical basis for large-scale industrial production of EPS. Full article

Using the DFT method, an analogue of R,R-t-Bu-BenzP* was tried as a potential ligand for Ni-catalyzed asymmetric hydrogenation. This ligand contains benzyl groups instead of the t-Bu groups in R,R-t-Bu-BenzP*. Computational results imply that the R,R-Benz-BenzP* ligand (1) is expected to provide excellent enantioselectivity in the Ni-catalyzed asymmetric hydrogenation of 1-phenylethanone oxime. The computed effectiveness of the R,R-Benz-BenzP* ligand is stipulated by its conformational flexibility, which helps stabilize the crucial transition states via a non-bonding interaction between the substrate and the catalyst. R,R-Benz-BenzP* ligands with CN- and OMe-substituted benzyl rings were also computed to possess the same effectiveness. Full article

Introducing organic functional groups to adsorbent surfaces enhances vanadium adsorption, an effective strategy for vanadium enrichment. In a quest for a profounder comprehension of the above adsorption mechanism, this study synthesized five types of quaternary ammonium salt-functionalized silica (QAS-SiO₂) and investigated the influence of functional groups, pH values, contact time, and temperature on vanadium (V) adsorption. The results indicated that the optimal QAS-SiO₂ (SiO₂@DMOA) achieved a vanadium adsorption rate of 99.40% and a maximum adsorption capacity of 39.16 mg g⁻¹. SiO₂@DMOA exhibited favorable adsorption selectivity for V over chromium (Cr), with a maximum separation factor (β_V/Cr) of 135.42 at pH 3.3. SiO₂@DMOA maintained efficient adsorption performance over five repeated cycles. A fusion of adsorption trials with energy decomposition analysis (EDA) tentatively unveiled that both chemical bonds and non-bonding interactions contributed to the interaction energy between organic functional groups and vanadium. Among them, chemical bonds accounted for 80.26%, while non-bonding interactions accounted for 19.74%. Based on EDA analysis, the interaction characteristics of different structural quaternary ammonium salts with vanadium in adsorption and extraction processes are discussed. Additionally, steric hindrance, the charge of the vanadium species, polarizability, and solvation effects, all played significant roles in the adsorption process. Full article

Silver(I) ions and organometallic complexes thereof are well-established antimicrobial agents. They have been employed in medical applications for centuries. It is also known that some bacteria can resist silver(I) treatments through an efflux mechanism. However, the exact mechanism of action remains unclear. All-atom force-field simulations can provide valuable structural and thermodynamic insights into the molecular processes of the underlying mechanism. Lennard-Jones parameters of silver(I) have been available for quite some time; their applicability to properly describing the binding properties (affinity, binding distance) between silver(I) and peptide-based binding motifs is, however, still an open question. Here, we demonstrate that the standard 12-6 Lennard-Jones parameters (previously developed to describe the hydration free energy with the TIP3P water model) significantly underestimate the interaction strength between silver(I) and both methionine and histidine. These are two key amino-acid residues in silver(I)-binding motifs of proteins involved in the efflux process. Using free-energy calculations, we calibrated non-bonded fix (NBFIX) parameters for the CHARMM36m force field to reproduce the experimental binding constant between amino acid sidechain fragments and silver(I) ions. We then successfully validated the new parameters on a set of small silver-binding peptides with experimentally known binding constants. In addition, we monitored how silver(I) ions increased the α-helical content of the LP1 oligopeptide, in agreement with previously reported Circular Dichroism (CD) experiments. Future improvements are outlined. The implementation of these new parameters is straightforward in all simulation packages that can use the CHARMM36m force field. It sets the stage for the modeling community to study more complex silver(I)-binding processes such as the interaction with silver(I)-binding-transporter proteins. Full article

Diaryl ureas (DU) are a cornerstone scaffold in organic and medicinal chemistry, celebrated for their unique structural attributes and broad range of biomedical applications. Their therapeutic reach has broadened beyond kinase inhibition in cancer therapy to encompass diverse mechanisms, including modulation of chromatin remodeling complexes, interference with developmental signaling pathways, and inhibition of stress-activated protein kinases in inflammatory disorders. A critical element in the rational design and optimization of DU-based therapeutics is a detailed understanding of their molecular recognition by target proteins. In this study, we employed a multi-tiered computational approach to investigate the molecular determinants of DU–protein interactions. A large-scale data mining of the Protein Data Bank resulted in an in-house dataset of 158 non-redundant, high-resolution crystal structures of DU–protein complexes. This dataset serves as the basis for a systematic analysis of nonbonded interactions, including hydrogen bonding, salt bridges, π–π stacking, CH-π, cation–π, and XH-π interactions (X = OH, NH, SH). Advanced electronic structure calculations at the B2PLYP/def2-QZVP level are applied to quantify the energetic contributions of these interactions and their roles in molecular recognition of diaryl ureas in their target proteins. The study led to the following findings: central to the molecular recognition of diaryl ureas in proteins are nonbonded π interactions—predominantly CH-π and π–π stacking—that synergize with hydrogen bonding to achieve high binding affinity and specificity. Aromatic R groups in diaryl ureas play a pivotal role by broadening the interaction footprint within hydrophobic protein pockets, enabling energetically favorable and diverse binding modes. Comparative analyses highlight that diaryl ureas with aromatic R groups possess a more extensive and robust interaction profile than those with non-aromatic counterparts, emphasizing the critical importance of nonbonded π interactions in molecular recognition. These findings enhance our understanding of molecular recognition of diaryl ureas in proteins and provide valuable insights for the rational design of diaryl ureas as potent and selective inhibitors of protein kinases and other therapeutically significant proteins. Full article

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, continually undergoes mutation, leading to variants with altered pathogenicity and transmissibility. The Omicron variant (B.1.1.529), first identified in South Africa in 2021, has become the dominant strain worldwide. It harbors approximately 50 mutations compared to the original strain, with 15 located in the receptor-binding domain (RBD) of the spike protein that facilitates viral entry via binding to the human angiotensin-converting enzyme 2 (ACE2) receptor. How do these mutated residues modulate the intermolecular interactions and binding affinity between the RBD and ACE2? This is a question of great theoretical importance and practical implication. In this study, we employed quantum chemical calculations at the B2PLYP-D3/def2-TZVP level of theory to investigate the molecular determinants governing Omicron’s ACE2 interaction. Comparative analysis of the Omicron and wild-type RBD–ACE2 interfaces revealed that mutations including S477N, Q493R, Q498R, and N501Y enhance binding through the formation of bifurcated hydrogen bonds, π–π stacking, and cation–π interactions. These favorable interactions counterbalance such destabilizing mutations as K417N, G446S, G496S, and Y505H, which disrupt salt bridges and hydrogen bonds. Additionally, allosteric effects improve the contributions of non-mutated residues (notably A475, Y453, and F486) via structural realignment and novel hydrogen bonding with ACE2 residues such as S19, leading to an overall increase in the electrostatic and π-system interaction energy. In conclusion, our findings provide a mechanistic basis for Omicron’s increased infectivity and offer valuable insights for the development of targeted antiviral therapies. Moreover, from a methodological perspective, we directly calculated mutation-induced binding energy changes at the residue level using advanced quantum chemical methods rather than relying on the indirect decomposition schemes typical of molecular dynamics-based free energy analyses. The strong correlation between calculated energy differences and experimental deep mutational scanning (DMS) data underscores the robustness of the theoretical framework in predicting the effects of RBD mutations on ACE2 binding affinity. This demonstrates the potential of quantum chemical methods as predictive tools for studying mutation-induced changes in protein–protein interactions and guiding rational therapeutic design. Full article

The development of anticancer drugs is costly and time intensive. Computational approaches optimize the process by studying molecules such as naphthoquinones. This research explores the quantitative structure–activity relationship (QSPR) and molecular interactions among 2,2-dimethyl-3-((3-nitrophenyl)amino)-2,3-dihydronaphtho[1,2-b]furan-4,5-dione (QPhNO₂), a Nor-β-Lapachone derivative with anticancer properties, and the following polymers for nanoencapsulation: polymethyl methacrylate (PMMA), polycaprolactone (PCL), and poly-lactic-co-glycolic acid (PLGA). Spartan 14 optimized the compounds using density functional theory (DFT), while ArgusLab performed docking, and Discovery Studio analyzed post-docking results. Simulations indicated that polymers with larger energy gaps are more stable and less prone to deformation than QPhNO₂, facilitating interaction with polymer chains. The binding energies for PMMA/QPhNO₂, PCL/QPhNO₂, and PLGA/QPhNO₂ interactions were −4.607, −4.437, and −1.814 kcal/mol, respectively. Docking analysis revealed non-bonded interactions between polymers and QPhNO₂. These findings highlight the role of computational methods in nanoencapsulation and molecular characterization, guiding the development of future analogs and combinations. Full article