Metallo-β-lactamases (MβLs) hydrolyze and inactivate β-lactam antibiotics, are a pivotal mechanism conferring resistance against bacterial infections. SMB-1, a novel B3 subclass of MβLs from Serratia marcescens could deactivate almost all β-lactam antibiotics including ampicillin (AMP), which has posed a serious threat to public health. To illuminate the mechanism of recognition and interaction between SMB-1 and AMP, various fluorescence spectroscopy techniques and molecular dynamics simulation were employed. The results of quenching spectroscopy unraveled that AMP could make SMB-1 fluorescence quenching that mechanism was the static quenching; the synchronous and three-dimensional fluorescence spectra validated that the microenvironment and conformation of SMB-1 were altered after interaction with AMP. The molecular dynamics results demonstrated that the whole AMP enters the binding pocket of SMB-1, even though with a relatively bulky R1 side chain. Loop1 and loop2 in SMB-1 undergo significant fluctuations, and α2 (71-73) and local α5 (186-188) were turned into random coils, promoting zinc ion exposure consistent with circular dichroism spectroscopy results. The binding between them was driven by a combination of enthalpy and entropy changes, which was dominated by electrostatic force in agreement with the fluorescence observations. The present study brings structural insights and solid foundations for the design of new substrates for β-lactamases and the development of effective antibiotics that are resistant to superbugs.

BACKGROUND: Mycotoxin contamination of food has been gaining increasing attention. Hidden mycotoxins that interact with biological macromolecules in food could make the detection of mycotoxins less accurate, potentially leading to the underestimation of the total exposure risk. Interactions of the mycotoxins alternariol (AOH) and alternariol monomethyl ether (AME) with high-molecular glutenin were explored in this study.
RESULTS: The recovery rates of AOH and AME (1, 2, and 10 μg kg-1) in three types of grains (rice, corn, and wheat) were relatively low. Molecular dynamics (MD) simulations indicated that AOH and AME bound to glutenin spontaneously. Hydrogen bonds and π-π stacking were the primary interaction forces at the binding sites. Alternariol with one additional hydroxyl group exhibited stronger binding affinity to glutenin than AME when analyzing average local ionization energy. The average interaction energy between AOH and glutenin was -80.68 KJ mol-1, whereas that of AME was -67.11 KJ mol-1.
CONCLUSIONS: This study revealed the mechanisms of the interactions between AOH (or AME) and high-molecular glutenin using MD and molecular docking. This could be useful in the development of effective methods to detect pollution levels. These results could also play an important role in the evaluation of the toxicological properties of bound altertoxins. © 2024 Society of Chemical Industry.

To address the ongoing challenges posed by the SARS-CoV-2 and potentially stronger viruses in the future, the development of effective methods to fabricate patterned graphene (PG) and other precisely functional products has become a new research frontier. Herein, we modeled the \"checkerboard\" graphene (CG) and stripped graphene (SG) as representatives of PG, and studied their interaction mechanism with the target protein (Mpro) by molecular dynamics simulation. The calculation results on the binding strength and the root mean square deviation values of the active pocket revealed that PG is an effective platform for adsorption, immobilization, and destruction of Mpro. Specifically, CG is found to promote disruption of the active pocket for Mpro, but the presence of \"checkerboard\" oxidized regions inhibits the adsorption of Mpro. Meanwhile, the SG can effectively confine Mpro within the non-oxidized strips and enhances their binding strength, but doesn\'t play well on disrupting the active pocket. Our work not only elucidates the biological effects of PGs, but also provides guidance for their targeted and precise utilization in combating the SARS-CoV-2.

In this work, the hierarchical topology ring (HTR+) algorithm, an extension of the HTR algorithm, was developed for identifying gas hydrate types, cage structures, and grain boundaries (GBs) within polycrystalline structures. Utilizing molecular dynamics trajectories of polycrystalline hydrates, the accuracy of the HTR+ algorithm is validated in identifying sI, sII and sH hydrate types, hydrate grains, and GBs in multi-hydrate polycrystals, as well as clathrate cages at GBs. Additionally, during the hydrate nucleation and growth processes, clathrate cages, hydrate type, hydrate grains and ice structures are accurately recognized. Significantly, this algorithm demonstrates high efficiency, particularly for large hydrate systems. HTR+ algorithm emerges a powerful tool for identifying micro/mesoscopic structures of gas hydrates, enabling an in-depth understanding of the formation mechanisms and properties of gas hydrates.

The rise of pyrazinamide (PZA)-resistant strains of Mycobacterium tuberculosis (MTB) poses a major challenge to conventional tuberculosis (TB) treatments. PZA, a cornerstone of TB therapy, must be activated by the mycobacterial enzyme pyrazinamidase (PZase) to convert its active form, pyrazinoic acid, which targets the ribosomal protein S1. Resistance, often associated with mutations in the RpsA protein, complicates treatment and highlights a critical gap in the understanding of structural dynamics and mechanisms of resistance, particularly in the context of the G97D mutation. This study utilizes a novel integration of computational techniques, including multiscale biomolecular and molecular dynamics simulations, physicochemical and medicinal chemistry predictions, quantum computations and virtual screening from the ZINC and Chembridge databases, to elucidate the resistance mechanism and identify lead compounds that have the potential to improve treatment outcomes for PZA-resistant MTB, namely ZINC15913786, ZINC20735155, Chem10269711, Chem10279789 and Chem10295790. These computational methods offer a cost-effective, rapid alternative to traditional drug trials by bypassing the need for organic subjects while providing highly accurate insight into the binding sites and efficacy of new drug candidates. The need for rapid and appropriate drug development emphasizes the need for robust computational analysis to justify further validation through in vitro and in vivo experiments.

Molten slag has different properties depending on its composition. The relationship between its composition, structure, and properties has been the focus of attention in industrial manufacturing processes. This review describes the atomistic scale mechanisms by which oxides of different compositions affect the properties and structure of slag, and depicts the current state of research in the atomic simulation of molten slag. At present, the research on the macroscopic properties of molten slag mainly focuses on viscosity, free-running temperature, melting point, and desulphurization capacity. Regulating the composition has become the most direct and effective way to control slag properties. Analysis of the microevolution mechanism is the fundamental way to grasp the macroscopic properties. The microstructural evolution mechanism, especially at the atomic and nanoscale of molten slag, is reviewed from three aspects: basic oxides, acidic oxides, and amphoteric oxides. The evolution of macroscopic properties is analyzed in depth through the evolution of the atomic structure. Resolution of the macroscopic properties of molten slag by the atomic structure plays a crucial role in the development of fundamental theories of physicochemistry.

Bioproduction of chiral amines is limited by low transaminase (TA) activity on nonnatural substrates, leading to the need for protein engineering. To address the challenge of quickly and precisely identifying the engineering targets, a strategy was proposed based on analyzing the mode changes in the high-energy intermediate state (H-state) of the substrate-enzyme complex during catalysis. By substituting the residues with minimal structural changes in catalytically active mode (A-mode) and distance-free mode (F-mode) of the H-state complex with more conserved ones to stabilize it, a TA mutant M5(T295C/L387A/V436A) with 121.9-fold higher activity for synthesizing the (S)-Rivastigmine precursor (S)-1-(3-methoxyphenyl)ethylamine was created. The applicability of this strategy was also validated by engineering another TA for 1.52-fold higher activity and >99% selectivity toward (R)-3-amino-1-butanol biopreparation. The much higher stereoselectivity of the mutant compared with the wild type (28.3%) demonstrated that this strategy is not only advantageous in engineering enzyme activity but also applicable for modulating stereoselectivity.

NF-kappaB-Inducing Kinase (NIK) is a key kinase in the activation of the NF-κB non-classical signalling pathway, which has been shown to be over-activated in patients with inflammatory diseases, immune disorders and malignancies and solid tumours inducing activation of the NF-κB non-classical signalling pathway. The design of ATP-competitive small molecule inhibitors against NIK has been a hot topic in the last decade, and many efficient NIK inhibitors have been identified. In this work, I aim to unravel the mechanism of NIK inhibition by different representative NIK type I 1/2 kinase inhibitors, using ADME, molecular docking, molecular dynamics simulation, MM-PBSA analysis and 3D-QSAR analysis. This work contributes to the understanding of the efficiency of NIK inhibitor binding by revealing the basis of the efficiency of NIK inhibitors, the difference in binding modes between different inhibitors and the overall effect on NIK.Communicated by Ramaswamy H. Sarma.

The major pathological feature of Alzheimer\'s disease (AD) is the aggregation of amyloid β peptide (Aβ) in the brain. Inhibition of Aβ42 aggregation may prevent the advancement of AD. This study employed molecular dynamics, molecular docking, electron microscopy, circular dichroism, staining of aggregated Aβ with ThT, cell viability, and flow cytometry for the detection of reactive oxygen species (ROS) and apoptosis. Aβ42 polymerizes into fibrils due to hydrophobic interactions to minimize free energy, adopting a β-strand structure and forming three hydrophobic areas. Eight dipeptides were screened by molecular docking from a structural database of 20 L-α-amino acids, and the docking was validated by molecular dynamics (MD) analysis of binding stability and interaction potential energy. Among the dipeptides, arginine dipeptide (RR) inhibited Aβ42 aggregation the most. The ThT assay and EM revealed that RR reduced Aβ42 aggregation, whereas the circular dichroism spectroscopy analysis showed a 62.8% decrease in β-sheet conformation and a 39.3% increase in random coiling of Aβ42 in the presence of RR. RR also significantly reduced the toxicity of Aβ42 secreted by SH-SY5Y cells, including cell death, ROS production, and apoptosis. The formation of three hydrophobic regions and polymerization of Aβ42 reduced the Gibbs free energy, and RR was the most effective dipeptide at interfering with polymerization.

As the critical component of automotive engine coolant, ethylene glycol (E.G.) significantly matters in heat dissipation. In this study, the key aim is to investigate the heat transfer behaviour of E.G. as nano-additives base fluid. The heat transfer capability of E.G./SiC nanofluid (N.F.) was experimentally and theoretically evaluated via transient hot wire methods and equilibrium molecular dynamics (EMD) simulation, respectively. M.D. simulation exhibited a great ability to accurately forecast the thermal conductivity of N.F. compared with the experiment results. The results confirmed that the thermal stability of N.F. is relatively greater than that of E.G. base fluids. An improvement mechanism of thermal conductivity and thermal stability under an atomic scale via the analysis of mean square displacement (MSD) and radial distribution function (RDF) calculation was elaborately presented. Ultimately, the results indicated that the diffusion effect and the increasing transition rate of liquid atoms are responsible for thermal conductivity enhancement.