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Nucleation is a fundamental and general process at the initial stage of first-order phase transition. Although various models based on the classical nucleation theory (CNT) have been proposed to explain the energetics and kinetics of nucleation, detailed understanding at nanoscale is still required. Here, in view of the homogeneous bubble nucleation, we focus on cavity formation, in which evaluation of the size dependence of free energy change is the key issue. We propose the application of a formula in stochastic thermodynamics, the Jarzynski equality, for data analysis of molecular dynamics (MD) simulation to evaluate the free energy of cavity formation. As a test case, we performed a series of MD simulations with a Lennard-Jones (LJ) fluid system. By applying an external spherical force field to equilibrated LJ liquid, we evaluated the free energy change during cavity growth as the Jarzynski's ensemble average of required works. A fairly smooth free energy curve was obtained as a function of bubble radius in metastable liquid of mildly negative pressure conditions.

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The mechanism by which algal organic matter (AOM) affects the clogging of ceramic emitters remains unclear, which partially reduces the operational life of agricultural water distribution systems. This paper systematically investigated the clogging phenomenon of ceramic emitters under three different AOM concentrations. The results of irrigation tests revealed that the AOM significantly affects the degree of clogging of ceramic emitters, with higher AOM concentrations leading to faster flow reduction. By analyzing the original irrigation water and effluent and characterizing the clogged emitter surface, it was demonstrated that AOM was intercepted by the ceramic emitter, forming a dense biofilm. Infrared spectroscopy analysis revealed that polysaccharides and humic substances were the main clogging components. The clogging kinetics showed that as the AOM concentration increased, the clogging of the filter cake layer gradually become dominant. Further, the mechanism of interaction between AOM and silica ceramic emitters was explored from a microscopic perspective using molecular dynamics (MD) simulation with bovine serum albumin (BSA), sodium alginate (SA), and humic acid (HA) as model clogging substances in AOM. The simulation results indicated a strong interaction between AOM molecules and silica molecules dominated by electrostatic attraction, with the strength of the interaction as SA > HA > BSA. It was hypothesized that early clogging was mainly formed by polysaccharides and humic substances combining with silica molecules, while BSA was retained later by combining with organics on the clogging layer or through size exclusion. This study provides insights into bio-clogging in microporous ceramic emitters and may offer a theoretical basis for developing measures to control emitter clogging.

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Introduction: In clinical practice, phosphodiesterase 5 (PDE5) inhibitors are commonly used to treat erectile dysfunction and pulmonary arterial hypertension. However, due to the high structural similarity between PDE5 and Phosphodiesterase 6 (PDE6), there is a risk that existing drugs will cause off-target effects on PDE6 resulting in visual disorders such as low visual acuity and color blindness. Previous research on the selectivity of PDE5 inhibitors focused on marketed drugs such as sildenafil and tadalafil. Methods: In this study, a highly selective PDE5 inhibitor, ligand3, was used as the subject, and molecular docking, molecular dynamics simulations, MM-GBSA, alanine scanning, and independent gradient model analysis were employed to investigate the biological mechanism underlying the selectivity of PDE5 inhibitors. Results and Discussion: The present work revealed that the binding mode of ligand3 to the PDE5A and PDE6C targets was distinctly different. Ligand3 exhibited stronger coulombic forces when binding to PDE5A, while showing stronger van der waals forces when binding to PDE6C. Ligand3 binds more deeply at the active site of PDE5A than at PDE6C, allowing its side chains to effectively bind to the critical TYR612, whereas in the case of the shallow binding to PDE6C, ligand3 lacks a similar effect. Mechanism investigations of highly selective inhibitors through computational simulation might provide an insight into potent treatment of drugs.

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RNase H-dependent antisense oligonucleotides (gapmer ASOs) represent a class of nucleic acid therapeutics that bind to target RNA to facilitate RNase H-mediated RNA cleavage, thereby regulating the expression of disease-associated proteins. Integrating artificial nucleic acids into gapmer ASOs enhances their therapeutic efficacy. Among these, amido-bridged nucleic acid (AmNA) stands out for its potential to confer high affinity and stability to ASOs. However, a significant challenge in the design of gapmer ASOs incorporating artificial nucleic acids, such as AmNA, is the accurate prediction of their melting temperature (T m ) values. The T m is a critical parameter for designing effective gapmer ASOs to ensure proper functioning. However, predicting accurate T m values for oligonucleotides containing artificial nucleic acids remains problematic. We developed a T m prediction model using a library of AmNA-containing ASOs to address this issue. We measured the T m values of 157 oligonucleotides through differential scanning calorimetry, enabling the construction of an accurate prediction model. Additionally, molecular dynamics simulations were used to elucidate the molecular mechanisms by which AmNA modifications elevate T m , thereby informing the design strategies of gapmer ASOs.

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Acinetobacter baumannii is a gram-negative bacillus prevalent in nature, capable of thriving under various environmental conditions. As an opportunistic pathogen, it frequently causes nosocomial infections such as urinary tract infections, bacteremia, and pneumonia, contributing to increased morbidity and mortality in clinical settings. Consequently, developing novel vaccines against Acinetobacter baumannii is of utmost importance. In our study, we identified 10 highly conserved antigenic proteins from the NCBI and UniProt databases for epitope mapping. We subsequently screened and selected 8 CTL, HTL, and LBL epitopes, integrating them into three distinct vaccines constructed with adjuvants. Following comprehensive evaluations of immunological and physicochemical parameters, we conducted molecular docking and molecular dynamics simulations to assess the efficacy and stability of these vaccines. Our findings indicate that all three multi-epitope mRNA vaccines designed against Acinetobacter baumannii are promising; however, further animal studies are required to confirm their reliability and effectiveness.

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This study aims to fine-tune the plasma composition with a particular emphasis on reactive nitrogen species (RNS) including nitrogen dioxide (NO2), dinitrogen pentoxide (N2O5), and nitrous oxide (N2O), produced by a self-constructed cylindrical dielectric barrier discharge (CDBD). We demonstrated the effective manipulation of the plasma chemical profile by optimizing electrical properties, including the applied voltage and frequency, and by adjusting the nitrogen and oxygen ratios in the gas mixture. Additionally, quantification of these active species was achieved using Fourier transform infrared spectroscopy. The study further extends to exploring the aerosol polymerization of acrylamide (AM) into polyacrylamide (PAM), serving as a model reaction to evaluate the reactivity of different plasma-generated species, highlighting the significant role of NO2 in achieving high polymerization yields. Complementing our experimental data, molecular dynamics (MD) simulations, based on the ReaxFF reactive force field potential, explored the interactions between reactive oxygen species, specifically hydroxyl radicals (OH) and hydrogen peroxide (H2O2), with water molecules. Understanding these interactions, combined with the optimization of plasma chemistry, is crucial for enhancing the effectiveness of DBD plasma in environmental applications like air purification and water treatment.

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Cryptococcus neoformans is a widely distributed opportunistic pathogenic fungus. While C. neoformans commonly infects immunocompromised individuals, it can also affect those who are immunocompetent. Transmission of C. neoformans primarily occurs through the respiratory tract, leading to the development of meningitis. The mortality rate of Cryptococcal meningitis is high, and treatment options are limited. Cryptococcus neoformans infections pose a significant public health threat and currently lack targeted and effective response strategies. This study aimed to screen T lymphocyte (cytotoxic T lymphocyte and helper T lymphocyte) and B lymphocyte epitopes derived from four C. neoformans antigens and develop two multi-epitope vaccines by combining them with various adjuvants. Molecular docking results demonstrated that the vaccines bind stably to Toll-like receptor 4 ( and induce innate immunity. The credibility of the molecular docking results was validated through subsequent molecular dynamics simulations. Furthermore, the results of immune simulation analyses underscored the multi-epitope vaccine's capability to effectively induce robust humoral and cellular immune responses within the host organism. These two vaccines have demonstrated theoretical efficacy against C. neoformans infection as indicated by computer analysis. Nevertheless, additional experimental validation is essential to substantiate the protective efficacy of the vaccines.

A multi-epitope Cryptococcus neoformans vaccine covering the most common A and D phenotypes was designed using bioinformatics methods.

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Glyphodes pyloalis Walker (Lepidoptera: Pyralidae) is the most destructive pest, causing severe damage to mulberry production in China's sericulture industry. The insecticide application in mulberry orchards poses a significant risk of poisoning to Bombyx mori. Shifting from insecticides to odor attractants is a beneficial alternative, but not much data is available on the olfactory system of G. pyloalis. We identified 114 chemosensory genes from the antennal transcriptome database of G. pyloalis, with 18 odorant-binding protein (OBP) and 17 chemosensory protein (CSP) genes significantly expressed in the antennae. Ligand-binding assays for two antennae-biased expressed general odorant-binding proteins (GOBPs) showed high binding affinities of GOBP1 to hexadecanal, ß-ionone, and 2-ethylhexyl acrylate, while GOBP2 exhibited binding to 4-tert-octylphenol, benzyl benzoate, ß-ionone, and farnesol. Computational simulations indicated that van der Waal forces predominantly contributed to the binding free energy in the binding processes of complexes. Among them, Phe12 of GOBP1 and Phe19 of GOBP2 were demonstrated to play crucial roles in their bindings to plant volatiles using site-directed mutagenesis experiments. Moreover, hexadecanal and ß-ionone attracted G. pyloalis male moths in the behavioral assays, while none of the candidate plant volatiles significantly affected female moths. Our findings provide a comprehensive understanding of the molecular mechanisms underlying olfactory recognition in G. pyloalis, setting the groundwork for novel mulberry pests control strategies based on insect olfaction.

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CONTEXT: Molecularly imprinted polymers (MIPs) have promising applications as synthetic antibodies for protein and peptide recognition. A critical aspect of MIP design is the selection of functional monomers and their adequate proportions to achieve materials with high recognition capacity toward their targets. To contribute to this goal, we calibrated a molecular dynamics protocol to reproduce the experimental trends in peptide recognition of 13 pre-polymerization mixtures reported in the literature for the peptide toxin melittin. METHODS: Three simulation conditions were tested for each mixture by changing the box size and the number of monomers and cross-linkers surrounding the template in a solvent-explicit environment. Fully atomistic MD simulations of 350 ns were conducted with the AMBER20 software, with ff19SB parameters for the peptide, gaff2 parameters for the monomers and cross-linkers, and the OPC water model. Template-monomer interaction energies under the LIE approach showed significant differences between high-affinity and low-affinity mixtures. Simulation systems containing 100 monomers plus cross-linkers in a cubic box of 90 Å3 successfully ranked the mixtures according to their experimental performance. Systems with higher monomer densities resulted in non-specific intermolecular contacts that could not account for the experimental trends in melittin recognition. The mixture with the best recognition capacity showed preferential binding to the 13-26-α-helix, suggesting a relevant role for this segment in melittin imprinting and recognition. Our findings provide insightful information to assist the computational design of molecularly imprinted materials with a validated protocol that can be easily extended to other templates.

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The research focused on the distinctive empty cup aroma, with the aim of identifying the key aroma compounds and the formation mechanism of empty cup aroma in soy sauce aroma type baijiu (SSB). The lasting times of SSB is significantly longer than that of other types of baijiu, with an average duration of 28 days. Key compounds such as 2,3-dimethyl-5-ethylpyrazine, phenylethyl alcohol, p-cresol, sotolon, benzeneacetic acid were identified in empty cup aroma due to their highest flavor dilution factor. Molecular dynamics (MD) simulation was performed to study the mechanism of empty cup aroma on the liquid-gas interface and solid-gas interface. The results revealed the existence of hydrogen bonding and van der Waals forces between sotolon and lactic acid, a representative nonvolatile compound, which are speculated to be an important reason for the empty cup aroma.

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Activation of G proteins through nucleotide exchange initiates intracellular signaling cascades essential for life processes. Under normal conditions, nucleotide exchange is regulated by the formation of G protein-G protein-coupled receptor complexes. Single point mutations in the Gα subunit of G proteins bypass this interaction, leading to loss of function or constitutive gain of function, which is closely linked with the onset of multiple diseases. Despite the recognized significance of Gα mutations in disease pathology, structural information for most variants is lacking, potentially due to inherent protein dynamics that pose challenges for crystallography. To address this, we leveraged an integrative spectroscopic and computational approach to structurally characterize seven of the most frequently observed and clinically relevant mutations in the stimulatory Gα subunit, GαS. A previously proposed allosteric model of Gα activation linked structural changes in the nucleotide-binding pocket with functionally important changes in interactions between switch regions. We investigated this allosteric connection in GαS by integrating data from variable temperature CD spectroscopy, which measured changes in global protein structure and stability, and molecular dynamics simulations, which observed changes in interaction networks between GαS switch regions. Additionally, saturation-transfer difference NMR spectroscopy was applied to observe changes in nucleotide interactions with residues within the nucleotide binding site. These data have enabled testing of predictions regarding how mutations in GαS result in loss or gain of function and evaluation of proposed structural mechanisms. The integration of experimental and computational data allowed us to propose a more nuanced classification of mechanisms underlying GαS gain-of-function and loss-of-function mutations.

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The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, is a highly contagious respiratory disease with widespread societal impact. The symptoms range from cough, fever, and pneumonia to complications affecting various organs, including the heart, kidneys, and nervous system. Despite various ongoing efforts, no effective drug has been developed to stop the spread of the virus. Although various types of medications used to treat bacterial and viral diseases have previously been employed to treat COVID-19 patients, their side effects have also been observed. The way SARS-CoV-2 infects the human body is very specific, as its spike protein plays an important role. The S subunit of virus spike protein cleaved by human proteases, such as furin protein, is an initial and important step for its internalization into a human host. Keeping this context, we attempted to inhibit the furin using phytochemicals that could produce minimal side effects. For this, we screened 408 natural phytochemicals from various plants having antiviral properties, against furin protein, and molecular docking and dynamics simulations were performed. Based on the binding score, the top three compounds (robustaflavone, withanolide, and amentoflavone) were selected for further validation. MM/GBSA energy calculations revealed that withanolide has the lowest binding energy of -57.2 kcal/mol followed by robustaflavone and amentoflavone with a binding energy of -45.2 kcal/mol and -39.68 kcal/mol, respectively. Additionally, ADME analysis showed drug-like properties for these three lead compounds. Hence, these natural compounds robustaflavone, withanolide, and amentoflavone, may have therapeutic potential for the management of SARS-CoV-2 by targeting furin.

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CONTEXT: To estimate the influence of temperature on properties of 2,4,6,8,10,12-hexanitro- 2,4,6,8,10,12-hexaazaisowurtzitane/1,4-dinitroimidazole (CL-20/1,4-DNI) cocrystal explosive, the supercell crystal of CL-20/1,4-DNI cocrystal model was established. The mechanical properties, sensitivity, and stability of cocrystal model under different temperatures (T = 225 K, 250 K, 275 K, 300 K, 325 K, 350 K) were predicted. Results show that mechanical parameters, including bulk modulus, tensile modulus and shear modulus are the lowest when temperature is 300 K, while Cauchy pressure is the highest, indicating that CL-20/1,4-DNI cocrystal model has better mechanical properties at 300 K. Cohesive energy density (CED) and its components energies decrease monotonically with the increase of temperature, illustrating that the CL-20 and 1,4-DNI molecules are activated and the safety of cocrystal explosive is worsened with the increase of temperature. Cocrystal model has relatively higher binding energy when the temperature is 300 K, implying that the CL-20/1,4-DNI cocrystal explosive is more stable under this condition. METHODS: The CL-20/1,4-DNI cocrystal model was optimized and the properties were predicted through molecular dynamics (MD) method. The MD simulation was performed with COMPASS force field and the ensemble was set as NPT, external pressure was set as 0.0001 GPa.

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Nonenveloped virus-like particles (VLPs) are self-assembled oligomeric structures composed of one or more proteins that originate from diverse viruses. Because these VLPs have similar antigenicity to the parental virus, they are successfully used as vaccines against cognate virus infection. Furthermore, after foreign antigenic sequences are inserted in their protein components (chimVLPs), some VLPs are also amenable to producing vaccines against pathogens other than the virus it originates from (these VLPs are named platform or epitope carrier). Designing chimVLP vaccines is challenging because the immunogenic response must be oriented against a given antigen without altering stimulant properties inherent to the VLP. An important step in this process is choosing the location of the sequence modifications because this must be performed without compromising the assembly and stability of the original VLP. Currently, many immunogenic data and computational tools can help guide the design of chimVLPs, thus reducing experimental costs and work. In this study, we analyze the structure of a novel VLP that originate from an insect virus and describe the putative regions of its three structural proteins amenable to insertion. For this purpose, we employed molecular dynamics (MD) simulations to assess chimVLP stability by comparing mutated and wild-type (WT) VLP protein trajectories. We applied this procedure to design a chimVLP that can serve as a prophylactic vaccine against the SARS-CoV-2 virus. The methodology described in this work is generally applicable for VLP-based vaccine development.

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There are many genes that produce proteins related to diseases and these proteins can be targeted with drugs as a potential therapeutic approach. Recent advancement in drug discovery techniques have created new opportunities for treating variety of diseases by targeting disease-related proteins. Structure-based drug discovery is a faster and more cost-effective approach than traditional methods. SHP2 phosphatase, encoded by the PTPN11 gene, has been the focus of much attention due to its involvement in many types of diseases. The biological function of SHP2 is enabled mostly by protein-protein interaction through its SH2 domains. In this study, we report the identification of a potential small molecule inhibitor for the N-SH2 domain of SHP2 by structure-based drug discovery approach. We utilized molecular docking studies, followed by molecular dynamics simulations and MM/PBSA calculations, to analyze compounds retrieved from the Broad's Drug Repurposing Hub and ZINC15 databases. We selected 10 hit compounds with the best docking scores from the libraries and examined their binding properties in the N-SH2 domain. We found that compound CID 60838 (Irinotecan) was the most suitable compound with a binding free energy value of - 64.45 kcal/mol and significant interactions with the target residues in the domain.

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Clostridioides difficile (C. difficile), as the major pathogen of diarrhea in healthcare settings, has become increasingly prevalent within community populations, resulting in significant morbidity and mortality. However, the therapeutic options for Clostridioides difficile infection (CDI) remain limited, and as of now, no authorized vaccine is available to combat this disease. Therefore, the development of a novel vaccine against C. difficile is of paramount importance. In our study, the complete proteome sequences of 118 strains of C. difficile were downloaded and analyzed. We found four antigenic proteins that were highly conserved and can be used for epitope identification. We designed two vaccines, WLcd1 and WLcd2, that contain the ideal T-cell and B-cell epitopes, adjuvants, and the pan HLA DR-binding epitope (PADRE) sequences. The biophysical and chemical assessments of these vaccine candidates indicated that they were suitable for immunogenic applications. Molecular docking analyses revealed that WLcd1 bonded with higher affinity to Toll-like receptors (TLRs) than WLcd2. Furthermore, molecular dynamics (MD) simulations, performed using Gmx_MMPBSA v1.56, confirmed the binding stability of WLcd1 with TLR2 and TLR4. The preliminary findings suggested that this multi-epitope vaccine could be a promising candidate for protection against CDI; however, experimental studies are necessary to confirm these predictions.

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Alginate is an important polysaccharide that is abundant in the marine environments, including the Polar Regions, and bacterial alginate lyases play key roles in its degradation. Many reported alginate lyases show characteristics of cold-adapted enzymes, including relatively low temperature optimum of activities (Topt) and low thermal stabilities. However, the cold-adaption mechanisms of alginate lyases remain unclear. Here, we studied the cold-adaptation mechanisms of alginate lyases by comparing four members of the PL7 family from different environments: AlyC3 from the Arctic ocean (Psychromonas sp. C-3), AlyA1 from the temperate ocean (Zobellia galactanivorans), PA1167 from the human pathogen (Pseudomonas aeruginosa PAO1), and AlyQ from the tropic ocean (Persicobacter sp. CCB-QB2). Sequence comparison and comparative molecular dynamics (MD) simulations revealed two main strategies of cold adaptation. First, the Arctic AlyC3 and temperate AlyA1 increased the flexibility of the loops close to the catalytic center by introducing insertions at these loops. Second, the Arctic AlyC3 increased the electrostatic attractions with the negatively charged substrate by introducing a high portion of positively charged lysine at three of the insertions mentioned above. Furthermore, our study also revealed that the root mean square fluctuation (RMSF) increased greatly when the temperature was increased to Topt or higher, suggesting the RMSF increase temperature as a potential indicator of the cold adaptation level of the PL7 family. This study provided new insights into the cold-adaptation mechanisms of bacterial alginate lyases and the marine carbon cycling at low temperatures.

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Sodium-glucose co-transporter 2 (SGLT2) is one of the important targets against type II diabetes mellitus. A typical SGLT2 inhibitor acts by inhibiting glucose reabsorption, thus lowering the blood glucose level. Unlike SGLT1, SGLT2 is responsible for almost 90% glucose reabsorption from glomerular filtrate. The current SGLT2 inhibitors include gliflozins, often prescribed as second or third-line agents in diabetes mellitus. The SGLT2 inhibitors also benefit patients with heart and kidney disease. Due to instability issues with the natural O-aryl glycoside analogues C-glycoside analogues were developed and showed improved stability. Despite enhanced bioavailability and selectivity of newer derivatives, some serious side effects are associated with gliflozin analogues. At the present study, we applied in-silico approaches to find new glycomimetic compounds as potent SGLT2 inhibitors that could show improvement in side effects associated with current analogues. This work applied both ligand-based and structure-based drug approaches to find potential compounds. We developed a 3D-QSAR method to screen potential inhibitors from a library of ten thousand compounds and performed docking studies. The compounds were ranked based on predicted pIC50 and docking score. An initial screening of five thousand compounds was conducted, and the subsequently selected top 12 compounds were based on binding free energy calculations. These selected compounds were subjected to molecular dynamics (MD) simulations. Remarkably, our simulations identified nine compounds that exhibited significant and sustained binding affinity compared to the co-crystallized Empagliflozin. Collectively, considering the anticipated pharmacokinetic profiles and toxicity assessments, several of these compounds emerged as promising candidates for further in-depth evaluation.

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With the rapid emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb), various levels of resistance against existing anti-tuberculosis (TB) drugs have developed. Consequently, the identification of new anti-TB targets and drugs is critically urgent. DNA gyrase subunit B (GyrB) has been identified as a potential anti-TB target, with novobiocin and SPR719 proposed as inhibitors targeting GyrB. Therefore, elucidating the molecular interactions between GyrB and its inhibitors is crucial for the discovery and design of efficient GyrB inhibitors for combating multidrug-resistant TB. In this study, we revealed the detailed binding mechanisms and dissociation processes of the representative inhibitors, novobiocin and SPR719, with GyrB using classical molecular dynamics (MD) simulations, tau-random acceleration molecular dynamics (τ-RAMD) simulations, and steered molecular dynamics (SMD) simulations. Our simulation results demonstrate that both electrostatic and van der Waals interactions contribute favorably to the inhibitors' binding to GyrB, with Asn52, Asp79, Arg82, Lys108, Tyr114, and Arg141 being key residues for the inhibitors' attachment to GyrB. The τ-RAMD simulations indicate that the inhibitors primarily dissociate from the ATP channel. The SMD simulation results reveal that both inhibitors follow a similar dissociation mechanism, requiring the overcoming of hydrophobic interactions and hydrogen bonding interactions formed with the ATP active site. The binding and dissociation mechanisms of GyrB with inhibitors novobiocin and SPR719 obtained in our work will provide new insights for the development of promising GyrB inhibitors.

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The widespread use and impervious nature of per- and polyfluorinated alkyl substances (PFASs) is leading to potentially harmful exposure in numerous environments. One avenue to explore remediation of PFAS-contaminated environments involves investigating how well PFASs adsorb onto various substrates. In the current review, we focus on summarizing recent computational research, largely involving density functional theory (DFT) and molecular dynamics (MD), into the adsorption and interaction of PFASs with a variety of substrates with an aim to provide insight and inspire further research that may lead to solutions to this critical problem that impacts the environment and human health.

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