Search Results (127)

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

Polyurea (PUR) has been widely used as a protective coating in recent years. In order to complete the understanding of the relationship between PUR microstructure and its energy absorption capabilities, the mechanical and dynamic performance of PURs containing various macrodiol structural units were compared using material characterization techniques and molecular dynamic simulation. The results showed that the PUR polycarbonate diols formed as energy absorbing materials showed high tensile strength, high toughness, and excellent loss factor distribution based on the comparison of stress–strain tensile curves, glass transition temperatures, phase images, and dynamic storage loss modulus. External energy from simple shear deformation was absorbed to convert non-bond energy, in particular, based on fractional free volume, interaction energy, and total energy and hydrogen bond number change from the molecular dynamic simulation. Hydrogen bonds formed between soft segments and hard segments in the PURs have been proven to play a significant role in determining their mechanical and dynamic performance. The mechanical and dynamic properties of PURs characterized and tested using experimental techniques were quantified effectively using molecular dynamic simulation. This is believed to be an innovative theoretical guidance for the structural design of PURs at the molecular level for the optimization of energy absorption capabilities. Full article

Bombyx mori silk fibroin is a promising biopolymer with notable mechanical strength, biocompatibility, and potential for diverse biomedical applications, such as tissue engineering scaffolds, and drug delivery. These properties are intrinsically linked to the structural characteristics of silk fibroin, making it essential to understand its molecular stability under varying environmental conditions. This study employed molecular dynamics simulations to examine the structural stability of silk I and silk II conformations of silk fibroin under changes in temperature (298 K to 378 K) and pressure (0.1 MPa to 700 MPa). Key parameters, including Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), and Radius of Gyration (R_g) were analyzed, along with non-bonded interactions such as van der Waals and electrostatic potential energy. Our findings demonstrate that both temperature and pressure exert a destabilizing effect on silk fibroin, with silk I exhibiting a higher susceptibility to destabilization compared to silk II. Additionally, pressure elevated the van der Waals energy in silk I, while temperature led to a reduction. In contrast, electrostatic potential energy remained unaffected by these environmental conditions, highlighting stable long-range interactions throughout the study. Silk II’s tightly packed β-sheet structure offers greater resilience to environmental changes, while the more flexible α-helices in silk I make it more susceptible to structural perturbations. These findings provide valuable insights into the atomic-level behavior of silk fibroin, contributing to a deeper understanding of its potential for applications in environments where mechanical or thermal stress is a factor. The study underscores the importance of computational approaches in exploring protein stability and supports the continued development of silk fibroin for biomedical and engineering applications. Full article

GTP-binding proteins are essential molecular switches that regulate a wide range of cellular processes. Their function relies on the specific recognition and binding of guanine within their binding pockets. This study aims to elucidate the molecular determinants underlying this recognition. A large-scale data mining of the Protein Data Bank yielded 298 GTP-binding protein complexes, which provided a structural foundation for a systematic analysis of the intermolecular interactions that are responsible for the molecular recognition of guanine in proteins. It was found that multiple modes of non-bonded interactions including hydrogen bonding, cation–π interactions, and π–π stacking interactions are employed by GTP-binding proteins for binding. Subsequently, the strengths of non-bonded interaction energies between guanine and its surrounding protein residues were quantified by means of the double-hybrid DFT method B2PLYP-D3/cc-pVDZ. Hydrogen bonds, particularly those involving the N2 and O6 atoms of guanine, confer specificity to guanine recognition. Cation–π interactions between the guanine ring and basic residues (Lys and Arg) provide significant electrostatic stabilization. π–π stacking interactions with aromatic residues (Phe, Tyr, and Trp) further contribute to the overall binding affinity. This synergistic interplay of multiple interaction modes enables GTP-binding proteins to achieve high specificity and stability in guanine recognition, ultimately underpinning their crucial roles in cellular signaling and regulation. Notably, the NKXD motif, while historically considered crucial for guanine binding in GTP-binding proteins, is not universally required. Our study revealed significant variability in hydrogen bonding patterns, with many proteins lacking the NKXD motif but still effectively binding guanine through alternative arrangements of interacting residues. Full article

A systematic simulation study was performed to investigate the interlayer interactions in a 1:1 layered phyllosilicate clay, kaolinite. Atomistic simulations with classical realistic force fields (INTERFACE and ClayFF) were used to examine the influence of the individual non-bonded interactions on the interlayer binding in the kaolinite model system. By switching off selected pairwise interactions in the applied force fields (leaving the intralayer interactions intact), it was confirmed that the tetrahedral–octahedral-type pairwise interactions held the kaolinite plates together and that interlayer hydrogen bonding, modeled by Coulombic forces, played a dominant role in this. Furthermore, it was observed that the number of hydrogen bonds formed had a significant influence on the basal spacing, and thus there was a striking change in the layer–layer interaction strength when there were only two kaolinite plates in the system, rather than several plates, as in real kaolinite particles. Contrary to expectations, the dispersion forces of the studied force fields alone were found to be strong enough to hold the kaolinite plates together. Full article

Recently, the accumulation of Amyloid Beta (Aβ) in the brain has been linked to the development of Alzheimer’s disease (AD) through the formation of aggregated plaques and neurofibrillary tangles (NFTs). Although carbon nanoparticles were previously shown as having a potential to address AD, the interactions of Aβ with such nanoparticles have not been studied extensively. In this work, molecular dynamic simulations are utilized to simulate the interactions between a single atomic layer of graphene oxide (GO) and a 12-monomer Aβ fibril. These interactions are further compared to those between GO and five individual monomers of Aβ to further understand the conformational changes in Aβ as an individual monomer and as a component of the Aβ fibril. It was found that out of the 42 residues of the Aβ monomers, residues 27–42 are the most affected by the presence of GO. Furthermore, stability analysis through RMSD, conformational energies and salt bridges, along with nonbonding energy, illustrate that Aβ–Aβ interactions were successfully interrupted and dismantled by GO. Overall, the differences in the interactions between monomeric Aβ consisting of five monomers with GO, an Aβ fibril with GO, and control Aβ monomers among themselves, helped elucidate the potential that GO has to disentangle the Aβ tangles, both in case of individual monomers forming a cluster and as part of the Aβ fibril. Full article