Journal of Molecular Modeling最新文献

Context

Human epidermal growth factor receptor (EGFR) controls many key signaling pathways associated with cell growth/survival and is a well-established druggable target of lung cancer. Previous studies have primarily focused on the extracellular ligand-binding domain (LBD) and intracellular kinase domain (KD) of EGFR, while its carboxy-terminal (CT) tail extended from the KD domain still remains largely unexplored to date. Considering that only the first ~ 80 CT residues (termed pkCT-tail) proximal to the KD are important for the kinase autoinhibition, we herein attempted to systematically investigate the structural basis, energetic property, and dynamic behavior of pkCT-tail as well as its role in EGFR activity and function

Methods

A 10-mer hotspot segment (residues 1009–1018) was identified to play an important role in mediating the intramolecular binding event of pkCT-tail to the KD domain, which is partially folded into an ordered, one-rounded helical conformation to tightly pack against the docking site of the KD domain. It is revealed that the Tyr1016 residue is a key anchor in the hotspot; its phosphorylation triggers the unbinding event of the hotspot segment, pkCT-tail, and even the whole CT-tail from the KD domain in a reversible manner. Several chemically stapled peptidic competitors were rationally designed as the potent binders of the KD domain and can compete with the native hotspot segment for the docking site. We demonstrated that both the intra-Tyr1016 phosphorylation and extra-peptidic competitors share a similar effect on EGFR, which can disrupt the native intramolecular interaction between the EGFR KD domain and pkCT-tail, thus unlocking the autoinhibitory state of the EGFR kinase. However, the peptidic competitors were observed to only moderately activate the kinase, imparting that the kinase activity is controlled by multiple factors rather than only the pkCT-tail.

Graphical Abstract

Context

Metal-based complex hydrogen storage materials demonstrate high hydrogen storage density and reversibility, attracting significant attention. This study focuses on analyzing the reaction mechanism of As-doped (LiNH₂)₂ clusters with LiH and NaH. The results indicate that As doping decreases the stability of (LiNH₂)₂, causing minimal changes in the lowest unoccupied molecular orbital while significantly shifting the electron cloud distribution of the highest occupied molecular orbital towards As, concentrating electron deficiency around As. The dehydrogenation process favors the –AsH₂ group, while the –NH₂ group facilitates hydrogen storage. A new hydrogen storage and release mechanism involving hydrogen transfer between –NH₂ and –AsH₂ is proposed, which lowers the energy barrier for hydrogen release and improves the reversibility of hydrogen storage.

Methods

Density functional theory (DFT) was employed to analyze the reaction mechanism. Key stationary points along the reaction path underwent geometric optimization, and their correctness was verified through frequency analysis.

Context

Currently, the study of charge transfer (CT) is significant and has attracted the attention of many researchers. The unique physical and chemical properties and wide range of applications have made charge transfer complexes (CTCs) a popular area of research. Thus, the designation of good components for creating CTCs with stable chemical bonds is very valuable. Quantum theoretical calculations are useful for studying three-centered intramolecular hydrogen bonding in organic molecules. Given that no computational study has been performed on the interaction between p-phenylenediamine (PPD, electron donor) and picric acid (PA, electron acceptor) until now, the UV-visible and IR spectra analysis, parameters such as natural charge (NBO), thermodynamic parameters like interaction energy (∆E°), standard enthalpies (∆H°), entropies (∆S°), Gibbs free energy (∆G°), and frontier molecular orbitals (FMOs) of the hydrogen bond (HB)-CTC were investigated by theoretical calculations (B3LYP method and 6-311G (d, p) basis sets). Molecular properties such as ionization potential (I), electron affinity (A), chemical hardness (η), electronic chemical potential (μ), and electrophilicity (ω) are obtained for the HB-CTC. The investigation focused on understanding intermolecular interactions using the reduced density gradient (RDG) and molecular electrostatic potential (MEP) surfaces. New calculations provide further insight into CTCs, and their potential for new applications is being explored.

Methods

The DFT calculations were performed using the Gaussian09 program package. The molecular structure and the optimum energy were evaluated using the GaussView 6 program. The electronic properties and spectral characteristics of the complex were analyzed using the B3LYP functional with a 6-311G (d, p) basis set. The thermodynamic functions, interaction energy (ΔE°), enthalpy (ΔH°), entropy (ΔS°), Gibbs free energy (ΔG°), and equilibrium constant were investigated via the vibrational frequency calculations. The vibrational frequencies and corresponding IR spectra were analyzed by determining the harmonic vibrational modes of the optimized geometry. The nature of interactions between CTC components was investigated using parameters MEP and NBO methodologies. To evaluate the charge transfer characteristics of the complexes, the analysis of FMOs (HOMO and LUMO) was performed, and their energy levels of HOMO and LUMO were computed. The theoretical UV-visible spectra were obtained by determining the excited states using time-dependent DFT (TD-DFT). The RDG diagrams were generated using the Multiwfn 3.8 program as a multifunctional wave function analyzer from CHK files.

Graphical Abstract

Context

As a porous carbon adsorption material, activated carbon (AC) was used widely with the characteristics of large specific surface area, adjustable pore structure and surface chemical properties. This work focuses on elucidating the defect-mediated adsorption mechanisms of smoke-specific high-toxic components (nicotine, a major toxic alkaloid; phenol, a typical carcinogenic aromatic) together with CO and N₂O on activated carbon. It addresses the critical research gap of scarce systematic DFT studies on the atomic-scale adsorption of nicotine and phenol on defective carbon, with an emphasis on deciphering intrinsic electronic mechanisms underlying defect-enhanced adsorption. The study revealed that defective carbon surfaces exhibited significantly higher adsorption capacities than the pristine counterparts, as evidenced by lower adsorption energies for all target molecules. Notably, while defect-enhanced adsorption on carbonaceous materials is well-documented, systematic DFT investigations on nicotine and phenol — two smoke-specific high-toxicity organics — remain scarce. Specifically, defect-induced electron redistribution promoted charge transfer and orbital hybridization, critical for the chemisorption of toxicants. These findings establish a predictive structure–activity relationship between defect electronic properties and adsorption selectivity/capacity, providing targeted guidance for engineering high-efficiency adsorbents to reduce harmful components in cigarette smoke.

Methods

All calculations were performed using the Gaussian 16 software package. Structural optimizations and frequency analyses of calculation configurations were performed at the B3LYP/def2svp level, while single-point energy calculations utilized the B3LYP/def2tzvp basis set. To elucidate the underlying mechanisms, wave function analyses, Mayer bond order (MBO), electrostatic potential (ESP), Frontier molecular orbital (HOMO–LUMO), Hirshfeld atomic charges, and Charge Density Difference (CDD) were conducted. These investigations demonstrated that surface defects enhance local electronegativity and chemical reactivity at adsorption sites, facilitating stronger interactions with polar constituents of cigarette smoke.

Context

Inspired by tetracyclic nitropyrazole-based stable and potential energetic materials, we designed two new C-C and C-N-linked tetrazole-pyrazole-based energetic molecules, with acceptable detonation performance and moderate sensitivity. The heat of formation and performance parameters were analyzed by density functional theory, and the calculations demonstrate that both compounds have a high positive heat of formation (> 930 kJ/mol). The designed compounds, A1 (density: 1.79 g/cm³, detonation velocity: 7.95 km/s, pressure: 25.30 GPa, impact sensitivity: 35 J) and A2 (density: 1.87 g/cm³, detonation velocity: 8.83 km/s, pressure: 33.31 GPa, impact sensitivity: 21 J), exhibit moderate to high detonation performance and low sensitivity to impact stimuli. Further, the analysis of bond strength and Mayer bond order of the C-NO₂ bond and charge on -NO₂ groups suggests the stability of the C-NO₂ bond in designed compounds in comparison with reported tetracyclic energetic compounds. These findings demonstrate that the combination of bistetrazole with nitropyrazole and dinitropyrazole rings holds high potential for developing new high-performing and less sensitive energetic materials.

Methods

The optimization and energy calculations of designed tetracyclic compounds were carried out at the B3LYP/6-311G(d,p) level of theory, utilizing the Gaussian 09 software package. The molecular surface properties were analysed using Multiwfn. The EXPLO5 (V7.01.01) thermochemical code was used to predict the detonation properties.

Graphical abstract

Context

Microstructural damage from freeze-thaw cycles severely undermines the durability of cementitious materials. Although graphene oxide (GO) is known to refine cement microstructures, its molecular mechanism for enhancing frost resistance remains unclear. This study employed molecular dynamics (MD) to investigate the effect of GO on the properties of calcium silicate hydrate (CSH) under freeze-thaw cycles. Simulation results demonstrated that GO forms strong bonds with the CSH matrix, leading to a densified interfacial structure. Atomic-scale analysis revealed that GO stabilizes the hydrogen-bonding network within CSH. Consequently, GO mitigates the degradation of peak compressive stress and elasticity modulus relative to neat CSH under the same freeze–thaw protocol. As a result, the overall damage tolerance of the composite is enhanced. This study elucidates the mechanism behind the enhanced frost resistance of GO–modified cement mortar at the molecular level and provides theoretical support for research on the durability of nano-modified cementitious materials.

Methods

All MD simulations were conducted using LAMMPS. The models employed ReaxFF force field. To simulate the freeze-thaw damage mechanism in cementitious materials, a cyclic strain with a maximum amplitude of 0.15 was applied along the Z-axis of the CSH model.

Context

Existence of bistability for carbon nanobracelets (cyclic molecules with alternating polycyclic regions and double carbon chains) is predicted using calculations based on density functional theory (DFT). It was found that two stable states have the same topological structure of covalent bonds, but different symmetries, with the total energy of the low-symmetry state lower by 1.0 and 0.8 eV than the energy of the high-symmetry state for the nanobracelets consisting of 4 and 5 monomers, respectively. On the basis of the calculated structural characteristics and electronic properties, we propose that the bistability of the carbon nanobracelets is related to the competition between the electron structure energy and the energy of interaction between the adjacent chains.

Methods

Structure optimization of carbon nanobracelets was performed using spin-polarized all-electron DFT calculations with the PBE functional implemented in the Priroda code. Due to chain flexibility, a multi-step procedure was employed. The initial coordinates, derived from molecular mechanics and hand-made designs, were refined via PM3 (MOPAC2016) to generate starting points for high- and low-symmetry states. The final optimization was performed in the Priroda code without symmetry restrictions. Energies included zero-point corrections. Extended triple-n Gaussian basis sets, with kinetically balanced small components, were employed. Molecular symmetry was determined using WebMO algorithms. Positive vibrational frequencies confirmed true energy minima. The GFN-xTB method with van der Waals correction D4 was used to verify DFT-PBE calculations. To investigate the stability of the local minima, we performed ab initio molecular dynamics simulations. The molecular electrostatic potential was visualized using Jmol.

Context

Polyimide (PI) is a key arc-resistant material, yet its molecular-level degradation under fault-arc plasma remains unclear. Here, arc-ablation experiments were combined with multi-scale simulations to elucidate its decomposition pathways. FTIR results indicate that high-energy plasma particles exceed the maximum bond dissociation energy of PI, causing highly disordered scission distinct from thermal decomposition. Bond-order and BDE analyses were used to identify vulnerable sites, followed by ReaxFF/ZBL molecular dynamics and Fukui function analysis to probe reaction pathways. The results show that C–C and N–C bonds between imide and phenyl rings, as well as aromatic ether C–O–C linkages, are the most susceptible to cleavage. Nitrogen atoms display strong nucleophilicity, inducing C–N bond rupture and ring opening; the resulting formation of additional N–H groups explains the intensified and broadened N–H bands in the FTIR spectra. In contrast, electrophilic oxygen preferentially attacks aromatic ether bonds, generating short-chain fragments that drive rapid mass loss. These consistent experimental and computational insights establish an atomic-scale path of PI degradation under arc plasma.

Methods

The modeling process was carried out using BIOVIA Materials Studio. Lmp2arc was used to convert .car files to .data files. The calculations for the polyimide bond order were performed using the DMol3 module of Materials Studio, with LDA-PWC selected for the generalization. This paper employs a hybrid ReaxFF and ZBL force field in LAMMPS to simulate ion bombardment of the PI surface (including the atoms) in an electric arc. Gaussian 16.0 was utilized to optimize the geometry at the B3LYP/6-31G(d,p) level. Fukui function calculations were performed for polyimide using Multiwfn, based on the electron wave function generated by Gaussian 16.0.

Context

The access to the molecular assemblage on the melting transition is fundamental to phase-change material’s design, particularly when applied to renewable and intermittent energy sources, and the investigation of physical/chemical/biological processes. The development of new methods to obtain this information is, consequently, highly desired. This framework is fertile ground for the establishment of machine learning–based models with both predictive and interpretable profiles. However, such models are difficult to establish. This work describes the implementation of a Random Forest interpretable approach set on the specific tree paths followed by a given chemical system (molecule) for the relationship between its descriptors/melting point value. The descriptors involve all combinations of atom pairs of a generical molecular chemical system. The combined use of Random Forest molecule’s specific tree paths and descriptor concept enables the built model the capacity to highlight the most important combinations of pairs of atoms/interactions inherent to molecular assembly on melting stage. As proof of concept, this procedure was applied to investigate the organization of 2-(2,4-dichlorophenoxy)acetic acid (2,4-D) molecules at their melting point, with the results validated with thermo-regulated FTIR and computational chemistry approaches.

Method

This approach combines the Random Forest algorithm and atom-pair-based descriptor’s pattern, set for a generical molecule, in order to find a straightforward structure–property relationship. The unique tree paths followed by a given molecule highlight new specific measures addressing a causality relationship involving its descriptors and the melting point profile. This machine learning approach was validated with thermo-regulated FTIR, interaction energies, and molecular dynamics techniques.