Mean Square Displacement Research Articles

Viscoelastic active diffusion governed by nonequilibrium fractional Langevin equations: Underdamped dynamics and ergodicity breaking

In this work, we investigate the active dynamics and ergodicity breaking of a nonequilibrium fractional Langevin equation (FLE) with a power-law memory kernel of the form K(t)∼t−(2−2H), where 1/2<H<1 represents the Hurst exponent. The system is subjected to two distinct noises: a thermal noise satisfying the fluctuation–dissipation theorem and an active noise characterized by an active Ornstein–Uhlenbeck process with a propulsion memory time τA. We provide analytic solutions for the underdamped active fractional Langevin equation, performing both analytical and computational investigations of dynamic observables such as velocity autocorrelation, the two-time position correlation, ensemble- and time-averaged mean-squared displacements (MSDs), and ergodicity-breaking parameters. Our results reveal that the interplay between the active noise and long-time viscoelastic memory effect leads to unusual and complex nonequilibrium dynamics in the active FLE systems. Furthermore, the active FLE displays a new type of discrepancy between ensemble- and time-averaged observables. The active component of the system exhibits ultraweak ergodicity breaking where both ensemble- and time-averaged MSDs have the same functional form with unequal amplitudes. However, the combined dynamics of the active and thermal components of the active FLE system are eventually ergodic in the infinite-time limit. Intriguingly, the system has a long-standing ergodicity-breaking state before recovering the ergodicity. This apparent ergodicity-breaking state becomes exceptionally long-lived as H→1, making it difficult to observe ergodicity within practical measurement times. Our findings provide insight into related problems, such as the transport dynamics for self-propelled particles in crowded or polymeric media.

Run-and-tumble motion in trapping environments

Complex or hostile environments can sometimes inhibit the movement capabilities of diffusive particles or active swimmers, who may thus become stuck in fixed positions. This occurs, for example, in the adhesion of bacteria to surfaces at the initial stage of biofilm formation. Here we analyze the dynamics of active particles in the presence of trapping regions, where irreversible particle immobilization occurs at a fixed rate. By solving the kinetic equations for run-and-tumble motion in one space dimension, we give expressions for probability distribution functions, focusing on stationary distributions of blocked particles, and mean trapping times in terms of physical and geometrical parameters. Different extensions of the trapping region are considered, from infinite to cases of semi-infinite and finite intervals. The mean trapping time turns out to be simply the inverse of the trapping rate for infinitely extended trapping zones, while it has a nontrivial form in the semi-infinite case and is undefined for finite domains, due to the appearance of long tails in the trapping time distribution. Finally, to account for the subdiffusive behavior observed in the adhesion processes of bacteria to surfaces, we extend the model to include anomalous diffusive motion in the trapping region, reporting the exact expression of the mean-square displacement.

Molecular dynamics study on the effect of inorganic salts on the wettability of surfactants on bituminous coal: Sodium dodecyl sulfate and sodium chloride as representatives

To further enhance the wetting ability of surfactants to coal, the mechanism of improving the wetting performance of SDS to bituminous coal by the addition of inorganic salt NaCl was studied through a combination of molecular dynamics (MD) simulation with experimental measurements. In the experiment part, the surface tensions of the mixed NaCl-SDS solutions and the contact angles on the bituminous coal surface were measured. Furthermore, MD simulations were conducted to investigate the adsorption characteristics and wetting mechanism of a mixed NaCl-SDS solution on the coal surface at the atomic scale. In this process, the static potentials of the H2O molecule, coal molecule and SDS molecule were calculated, and the number of hydrogen bonds (H-bonds) formed throughout the whole simulation process, the average H-bond length, the relative concentration distribution (RCD) curve and the mean square displacement (MSD) curve were obtained. The experimental results showed that the surface tension and contact angle were both decreased by the addition of sodium chloride in mixed solutions. When 0.6 mol/L NaCl was added, the surface tension and contact angle reached the minima of 30.45 mN/m and 13.01°, respectively. The MD simulation results showed that, after the addition of NaCl, diffusion and migration of H2O molecules were limited, the number of H-bonds increases, the average bond length decreased, the sorption between H2O molecules and coal molecules was enhanced, and the hydrophilicity of coal surface was improved, which meant that the wetting ability of SDS solution to bituminous coal was enhanced by adding NaCl. The effect of the added NaCl in improving the wettability of SDS on coal was explored from two perspectives with macroscopic experiments and microcosmic simulations, and the added NaCl improved the effects of dust suppressants, and played a key role in preventing dust hazards in coal mines.

Using NMR diffusion data to validate MD models of disordered proteins: Test case of N-terminal tail of histone H4

MD simulations can provide uniquely detailed models of intrinsically disordered proteins (IDPs). However, these models need careful experimental validation. The coefficient of translational diffusion Dtr, measurable by pulsed field gradient NMR, offers a potentially useful piece of experimental information related to the compactness of the IDP’s conformational ensemble. Here, we investigate, both experimentally and via the MD modeling, the translational diffusion of a 25-residue N-terminal fragment from histone H4 (N-H4). We found that the predicted values of Dtr, as obtained from mean-square displacement of the peptide in the MD simulations, are largely determined by the viscosity of the MD water (which has been reinvestigated as a part of our study). Beyond that, our analysis of the diffusion data indicates that MD simulations of N-H4 in the TIP4P-Ew water give rise to an overly compact conformational ensemble for this peptide. In contrast, TIP4P-D and OPC simulations produce the ensembles that are consistent with the experimental Dtr result. These observations are supported by the analyses of the 15N spin relaxation rates. We also tested a number of empirical methods to predict Dtr based on IDP’s coordinates extracted from the MD snapshots. In particular, we show that the popular approach involving the program HYDROPRO can produce misleading results. This happens because HYDROPRO is not intended to predict the diffusion properties of highly flexible biopolymers such as IDPs. Likewise, recent empirical schemes that exploit the relationship between the small-angle x-ray scattering-informed conformational ensembles of IDPs and the respective experimental Dtr values also prove to be problematic. In this sense, the first-principle calculations of Dtr from the MD simulations, such as demonstrated in this work, should provide a useful benchmark for future efforts in this area.

Uncovering dissolution behavior and thermodynamic properties of metronidazole benzoate in twelve mono-solvents by experiments and molecular simulation

In this study, metronidazole benzoate (MBZ), a nitroimidazole antibiotic, was selected to measure the solubility in 12 solvents by the gravimetric method in the temperature range of 278.15 K to 323.15 K. The intermolecular interactions dominated by H···H and O···H contacts in the solid phase were determined using Hirshfeld surface analysis (HS). Subsequently, molecular simulations involving molecular electrostatic potential surface (MEPs), hydrogen binding energy (EHB) and mean square displacement (MSD) revealed the effect of the solvent polarity, hydrogen bonding and diffusion process on the dissolution behavior of MBZ. Furthermore, six thermodynamic models, all with values of ARDs less than 5 %, were successfully correlated with the experimental solubility results. The Apelblat model achieved the best fitting. Based on the NRTL models, relevant thermodynamic parameters were obtained, indicating that the dissolution process of MBZ in various solvents is spontaneous and entropy-driven. In the measured temperature range, the solubility of MBZ in different solvents increased from 4-times to 25-times as the temperature changed, which provided an important theoretical basis for the industrial production of MBZ.

Molecular dynamics simulation of Sc2O3-Gd2O3-Y2O3 dopant effect on the crystal structure and thermophysical properties of zirconia-based ceramic materials

This paper aims to provide an insight into the effects of different doping ratios on the crystal structure, thermal conductivity, ion diffusion, and high-temperature thermal expansion coefficient of Sc2O3-Gd2O3-Y2O3 co-doped ZrO2 (ScGdYSZ) materials. They were investigated by a non-equilibrium molecular dynamics method. The results show that with Gd2O3-Sc2O3-Y2O3 co-doping, the thermal expansion of the resulting materials is all relatively close to that of 8YSZ materials and linear with temperature. At 1473 K, 1 mol%Sc2O3–3 mol%Gd2O3–4 mol%Y2O3 stabilized ZrO2 (1Sc3Gd4YSZ) coating material has the smallest thermal conductivity, with a thermal conductivity of 5.66 W·(m·K)−1. The mean square displacement (MSD) of O2− was linear with the time when the sum of the doping ratio of Sc2O3 and Gd2O3 was 4 mol%, and the MSD of O2− in the material increased with the doping ratio of Sc2O3. increases, the MSD of O2− in the material increases, and the migration diffusion rate is accelerated.

The effect of composite curing agent ratio on the photooxidative aging behavior of epoxy asphalt based on molecular dynamics simulation

In order to explore the effect of composite curing agent ratio on the photooxidative aging behavior of epoxy asphalt with an acidic composite curing system, three curing agent ratios of epoxy asphalt were prepared to obtain different cross-linking network densities. The prepared epoxy asphalt was subjected to photooxidation aging for 240 h at 60 ℃. Fourier transform infrared (FTIR) and elemental analysis tests were conducted to determine the evolution of chemical components during photooxidative aging. Based on the chemical components before and after aging, molecular models of photooxidation aged epoxy asphalt with different curing agent ratios were constructed. The mean square displacement (MSD) of oxygen atoms and the oxygen uptake of each component were calculated to study the diffusion behavior of oxygen atoms and the oxidation degree of each component under various cross-linking networks. Glass transition temperature (Tg) and interaction energy were determined to characterize the thermodynamic properties and interaction between asphalt phase and epoxy resin phase of epoxy asphalt before and after aging. The radial distribution function (RDF) was determined to simulate the distribution of asphaltene and epoxy resin crosslinked networks in different cross-linking networks. The results show that the formation of carbonyl groups, alcohol hydroxyl groups, and the fracture of methylene groups was observed during the photooxidative aging process of epoxy asphalt. The rise in the proportion of anhydride curing agents improved the stability of the chemical components in epoxy asphalt under photooxidation aging. High cross-linking density and methylene fracture weakened the diffusion ability of oxygen atoms in epoxy asphalt due to a reduction in free volume. In addition, photooxidation aging had a negative impact on the low-temperature performance and interaction between asphalt phase and epoxy resin phase of epoxy asphalt. However, a high content of acid anhydride alleviated the damage of photooxidation aging to low-temperature performance. Photooxidation aging developed the polar functional groups of epoxy asphalt, promoting the stacking of asphaltene under a high content of dicarboxylic acid curing agent, while breaking the stacking of asphaltene under a high content of acid anhydride curing agent.

Assessment of the Binding of Pseudallecin A to Human Serum Albumin with Multi-Spectroscopic Analysis, Molecular Docking and Molecular Dynamic Simulation.

The binding of pseudallecin A (PA), a potential antibiotic with strong inhibitory activities against Gram-positive Escherichia coli and Gram-negative Staphylococcus aureus, to human serum albumin (HSA) was explored. The interaction between them was assessed by multi-spectroscopic analysis, binding site competitive analysis, molecular docking and molecular dynamic simulation, showing the results as follows: PA effectively quenched the innate fluorescence of HSA by a static quenching process, formed a complex at a molar ratio of approximately 1 : 1 and performed an effective non-radiative energy transfer; the binding of PA to HSA was a spontaneous exothermic reaction driven by enthalpy with strong affinity and had a slight effect on the conformation of HSA; PA bound at site III of HSA and hydrogen bonds were the major binding forces to maintain the stability of the PA-HSA complex. Molecular dynamic simulation was performed to calculate the root mean square deviation (RMSD), root mean square fluctuation (RMSF) and radius of gyration (Rg) for this complex and effectively supported the spectroscopic outcome. These results meant that the delivery and distribution of PA as a water-insoluble molecule can be efficiently accomplished via HSA in human blood and, it has a good potential for future drug application and pharmacological development.

Molecular dynamics-based study of the modification mechanism of asphalt by graphene oxide.

Graphene oxide(GO) has been widely used in asphalt modification due to its excellent properties. To reveal the interaction effect between GO and asphalt materials, the microscopic behavior and molecular structure changes of asphalt and GO/asphalt were investigated by molecular dynamics (MD) simulations. Mean square displacement (MSD) results showed that GO significantly inhibited the diffusion of molecules of asphalt components. Radial distribution function (RDF) results that GO destroys the original sol-type structure of asphalt. Simultaneously, GO adsorbed resins at low-temperature, adsorbed asphaltenes at high-temperature, and dispersed as a dispersed phase in the light components. The concentration of the dispersed phase in the asphalt colloidal structure was increased and the mutual attraction was enhanced. This improves the deformation resistance at high temperature, but weakens the ductility at low temperatures. To investigate the mechanism of action of GO-modified asphalt, the asphalt model and the GO/asphalt composite system model were constructed using the Amorphous Cell module in Materials Studio 2020 software. Subsequently, molecular dynamics simulations of the GO/asphalt composite system were performed using the Forcite module, while the interactions between atoms and molecules were described using the COMPASS II force field.

Fluctuations of Mean-Square Displacement in Presence of Traps: Non-Self-Averaging versus Ensemble Averaging

We consider nonstationary diffusion in a medium with random traps-sinks. We study the self-averaging of the mean-square displacement (MSD) of the ensemble of N particles in the fluctuational long-time limit. We demonstrate that MSD of survivors is self-averaging with respect to the number of engaged particles N and is strongly non-self-averaging with respect to time t . To measure MSD of survivors with required accuracy at the required time of observation t 0 , the initial number of particles N 0 must be exponentially large in t 0 . Any N 0 , whatever large, will be insufficient at long enough time. In the formulation, when all particles, both survivors and trapped ones, contribute to MSD, we find self-averaging in N and non-strong non-self-averaging over t .

A novel erucic acid derived surfactant: Experimental and theoretical study

Erucic acid is still a difficulty to utilize efficiently as a byproduct of grease processing. An effective strategy is to develop novel surfactants derived from erucic acid. Adamantyl trimethyl ammonium erucate, (AdEr) is an ionic liquid anionic surfactant derived from erucic acid. In this study, a combination of experimental and theoretical calculations was used to compare its physical characteristics and aggregation behaviors with the previously reported choline erucate (ChEr). The physical chemical properties were evaluated by differential scanning calorimetry (DSC), thermogravimetric analysis, surface tension and dynamic light scattering (DLS). The introduction of adamantane enhanced thermal stability and increased the melting point, while maintaining the excellent water-solubility. In comparison with ChEr, AdEr has a lower critical micelle concentration (CMC) and lager micellar aggregation sizes, exhibiting better micellization ability. Density functional theory (DFT) calculations suggests that AdEr has less intramolecular activity and a more stable molecular structure. Molecular dynamic (MD) simulations verified that AdEr preferred to aggregate to form micelles and had a larger aggregation size than ChEr using parameters such as conformation snapshots, radius of gyration (Rg) and mean square displacement (MSD). According to radial distribution function (RDF) analysis, this is owing to the smaller occupied area due to lower hydration of COO− groups of AdEr, and the difference hydration extent of the cations (Ad+ and Cho+). These findings clearly suggest that AdEr can be used as a potential alternative to conventional surfactant derived from erucic acid for various applications.

Exploring the potential of fluoro‐flavonoid derivatives as anti‐lung cancer agents: DFT, molecular docking, and molecular dynamics techniques

AbstractThe present investigation utilized in silico methodologies to explore the diverse pharmacological activities, toxicity profiles, and chemical reactivity of a series of fluoro‐flavonoid compounds (1–14), which are secondary metabolites of plants known for their broad range of biological effects. A comprehensive strategy is utilized, incorporating methods such as prediction of activity spectra for substances (PASS) prediction, absorption, distribution, metabolism, excretion, and toxicity (ADMET) assessments, and density functional theory (B3LYP) calculations using three basis sets: 6‐31G(d,p), 6‐311G(d,p), and 6‐311++G(d,p). Furthermore, the study employed molecular docking technique to identify target proteins, including HER2 (7JXH), EGFR (4UV7), FPPS (1YQ7), HPGDS (1V40), DCK (1P60), and KEAP1 on Nrf2 (1X2J), for the investigated compounds, with cianidanol and genistein serving as reference drugs for the docking process. The investigated fluoro‐flavonoid compounds exhibited significantly greater binding affinities (ranging from −8.3 to −10.6 kcal mol−1) toward HER2, HPGDS, and KEAP1 compared to the reference drugs, cianidanol and genistein, which displayed binding affinities ranging from −8.4 to −9.4 kcal mol−1. Furthermore, molecular dynamics simulations were conducted to assess the stability of the protein‐ligand interaction, using the root‐mean‐square deviation (RMSD), root‐mean‐square fluctuation (RMSF), Radius of gyration (Rg) parameters and principle component analysis (PCA). Among the tested fluoro‐flavonoid analogs, analog 11 showed a RMSD value of .15 nm with the HER2 protein target, indicating a stable interaction. Based on in silico results, it appears that the fluoro‐flavonoid compound 11 has the potential to serve as a targeted anti‐lung cancer drug. However, additional in vivo and in vitro studies are necessary to confirm this hypothesis.

Discovery of Potential Natural STAT3 Inhibitors: An in silico Molecular Docking and Molecular Dynamics Study

Cancer is a mechanistically complex and diverse disease with a plethora of fundamental genetic and epigenetic factors. Signal transducer and activator of transcription-3 (STAT3) is a transcription factor, and its constitutive activation executes promotion of cellular proliferation, cell cycle, angiogenesis, metastasis, immunosuppression, and chemo-resistance in cancer cells. Here, we aimed to design natural potential STAT3 inhibitors. For this purpose, we investigated 92 phytochemical compounds by molecular docking studies because they are diversified, multitargeted, affordable, easily available, and less- or non-toxic. We selected only 6 compounds such as sarsasapogenin (L3), peiminine (L9), solasodine (L10), tormentic acid (L23), obacunone (L29), and echinocystic acid (L34) due to their greater binding affinity than reference STAT3 inhibitor (S3I-201) with STAT3. The study was further continued by molecular dynamic (MD) simulations and ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis. The results of molecular docking showed that all selected ligands exhibited binding affinity range from -9.3 Kcal/mol to -7.9 Kcal/mol and predicted inhibition constant ([Formula: see text].) values range from 0.14 [Formula: see text]M to 1.5 [Formula: see text]M. These compounds showed effective hydrogen bonding and hydrophobic interactions with DNA binding domain as well as SH2-domain of STAT3. The MD simulations performed by nanoscale molecular dynamics (NAMD) calculated root mean square deviations (RMSD), root mean square fluctuations (RMSF), radius of gyration ([Formula: see text]), solvent accessible surface area (SASA) and number of hydrogen bond dynamics. All selected ligands with protein exhibited stability over 120 ns by MD simulation. Moreover, these ligands showed favorable ADMET profiling and drug likeness. So, our current computational investigations showed that these novel drug candidates can be potential STAT3 inhibitors and evoke the scientific interest for their further verification by in vitro and in vivo studies.

The repurposing of FDA-approved drugs to stop viral replication in COVID-19 treatment: a comprehensive molecular docking and dynamics analysis

Amidst a public health crisis such as the SARS-CoV-2 induced COVID-19 pandemic, the urgency to develop and provide access to novel drugs becomes paramount. In these scenarios, repurposing existing drugs emerges as an appealing strategy due to their established safety profiles and prior regulatory approvals, potentially streamlining their adoption for new therapeutic purposes. There has been a notable interest in investigating the repurposing potential of FDA-approved drugs to combat the disease triggered by the SARS-CoV-2 virus. This investigation was conducted with the objective of identifying FDA-approved antiviral drugs that could target both the original and mutant forms of the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) protein, given the escalating prevalence of SARS-CoV-2 mutations that undermined vaccine efficacy and underscored the need for alternative treatment avenues. Despite ongoing clinical trials, the selection of drugs specifically designed to combat SARS-CoV-2 remains limited. The present study aimed to assess the inhibitory potential of eight approved antiviral drugs. The wild-type and mutant (P323L) RdRp protein (PDB ID: 7BV2). By utilizing molecular docking techniques, the selected drugs were evaluated based on their binding affinities with both the mutant and wild-type RdRp protein. Subsequently, the protein-ligand complexes exhibiting the highest binding affinities were subjected to a 150 ns molecular dynamics simulation to evaluate their stability. The outcomes of the molecular docking analysis pinpointed Dolutegravir and Beclabuvir as possessing the most robust binding affinities for both mutant and wild-type RdRp systems. These findings prompted the selection of these drugs for an in-depth molecular dynamic simulation (MDS) investigation. The comprehensive analysis of Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), Radius of Gyration (Rg), Solvent Accessible Surface Area (SASA) and Secondary Structure Dynamics confirmed that Dolutegravir and Beclabuvir are potent inhibitors of the NSP12 protein. Collectively, the computational assessments put forth two potential contenders: Dolutegravir and Beclabuvir as promising inhibitors against both the wild-type and mutant RdRp proteins. To further validate these drug candidates, rigorous in vitro and in vivo investigations are warranted which could eventually position them as valuable therapeutic agents in the fight against COVID-19.

Characterization of nano-silica vegetable grease with diffusing wave spectroscopy DWS and Raman spectroscopy

The diffusing wave spectroscopy (DWS) method made it possible to identify changes in the dynamics of the free movement of particles in the grease under the influence of temperature, which changed the viscoelastic properties of the grease. Changes in the parameters determined by DWS method influenced changes in the chemical structure, which was confirmed by Raman spectroscopy, determining the integral intensity of the unsaturated to saturated bond bands found in the grease. The article presents the results of the influence of temperature on changes in the viscoelastic states of vegetable grease evaluated on the basis of properties determined by DWS (diffusing wave spectroscopy). The following parameters were used to evaluate the viscoelastic states: the intensity correlation function (ICF), the correlation function of mean square displacement (MSD), the elastic modulus G′ and the viscosity modulus G″. A significant effect of temperature on changes in the microstructure of vegetable grease was observed, which was reflected in the viscoelastic parameters. The dynamics of the free movement of molecules in the grease was changed, which affected the elasticity of the system and the displacement of the G′ and G″ modules towards higher frequencies.

Nonergodicity of confined superdiffusive fractional Brownian motion.

Using stochastic simulations supported by analytics we determine the degree of nonergodicity of box-confined fractional Brownian motion for both sub- and superdiffusive Hurst exponents H. At H>1/2 the nonequivalence of the ensemble- and time-averaged mean-squared displacements (TAMSDs) is found to be most pronounced (with a giant spread of individual TAMSDs at H→1), with two distinct short-lag-time TAMSD exponents.

Lysozyme stability in various deep eutectic solvents using molecular dynamics simulations

The ability of neat deep eutectic solvents (DESs) to influence protein structure and function has gained considerable interest due to the unstable nature of enzymes or therapeutic proteins, which are often exposed to thermal, chemical, or mechanical stresses when handled at an industrial scale. In this study, we simulated a model globular protein, lysozyme, in water and six choline chloride-based DES using molecular dynamics simulations, to investigate the structural changes in various solvent environments, giving insights into the overall stability of lysozyme. Root mean square deviation (RMSD) and root mean square fluctuations (RMSF) of the C-α backbone indicated that most DESs induced a less flexible and rigid lysozyme structure compared to water. The radius of gyration and end-to-end distance calculations pointed towards higher structural compactness in reline and levuline, while the structure of lysozyme considerably expanded in oxaline. Protein-solvent interactions were further analysed by hydrogen bonding interactions and radial distribution functions (RDF), which indicated a higher degree of lysozyme-hydrogen bond donor (HBD) interactions compared to lysozyme-choline hydrogen bonding. Surface area analysis revealed an overall % increase in total positive, negative, donor, and acceptor surface areas in malicine and oxaline compared to water and other DESs, indicating the exposure of a larger number of residues to interactions with the solvent. Reline, levuline, and polyol-based DESs comparatively stabilized lysozyme, even though changes in the secondary/tertiary structures were observed. Communicated by Ramaswamy H. Sarma

Natural Phosphodiesterase-4 Inhibitors with Potential Anti-Inflammatory Activities from Millettia dielsiana.

The results of in silico screening of the 50 isolated compounds from Millettia dielsiana against the target proteins PDE4 (PDE4A, PDE4B, and PDE4D) showed binding affinity ranges from -5.81 to -11.56, -5.27 to -13.01, and -5.80 to -12.12 kcal mol-1, respectively, with median values of -8.83, -8.84, and -8.645 kcal mol-1, respectively. Among these compounds, Millesianin F was identified as the most promising PDE4A inhibitor due to its strongest binding affinity with the target protein PDE4A. (-11.56 kcal mol-1). This was followed by the compound 5,7,4'-trihydroxyisoflavone 7-O-β-d-apiofuranosyl-(1→6)-β-d-glucopyranoside (D50) with the binding affinity value of -11.35 kcal mol-1. For the target protein PDE4B, compound D50 exhibited the strongest binding affinity value of -13.01 kcal mol-1, while showing poorer inhibition ability for PDE4D. The 100 ns MD simulation examination (radius of gyration, Solvent Accessible Surface Area (SASA), Root-Mean-Square Deviation (RMSD), Root-Mean-Square Fluctuation (RMSF), and hydrogen bonding) was carried out to examine the overall stability and binding efficiency of the protein-ligand complex between compounds (Millesianin F, Millesianin G, Claclrastin-7-O-β-d-glucopyranoside, 7-hydroxy-4',6 dimethoxyisoflavone-7-O-β-d-apiofuranosyl-(1→6)-β-d-glucopyranoside, 7-hydroxy-4',8-dimethoxyisoflavone 7-O-β-d-apiofuranosyl-(1→6)-β-d-glucopyranoside, Odoratin-7-O-β-d-glucopyranoside, and 5,7,4'-trihydroxyisoflavone 7-O-β-d-apiofuranosyl-(1→6)-β-d-glucopyranoside) and PDE4 (A, B) subtype proteins. Compound D50 has shown strong anti-inflammatory activity, as evidenced by experimental results. It effectively inhibits PDE4B and PDE4D, with IC50 values of 6.56 ± 0.7 µM and 11.74 ± 1.3 µM, respectively. Additionally, it reduces NO production, with an IC50 value of 5.40 ± 0.9 µM. Based on these findings, it is promising and considered a potential novel anti-inflammatory drug for future development.

Confined Dynamics in Spherical Polymer Brushes.

We investigate the dynamics of polymers grafted to spherical nanoparticles in solution using hybrid molecular dynamics simulations with a coarse-grained solvent modeled via the multiparticle collision dynamics algorithm. The mean-square displacements of monomers near the surface of the nanoparticle exhibit a plateau on intermediate time scales, indicating confined dynamics reminiscent of those reported in neutron spin-echo experiments. The confined dynamics vanish beyond a specific radial distance from the nanoparticle surface that depends on the polymer grafting density. We show that this dynamical confinement transition follows theoretical predictions for the critical distance associated with the structural transition from confined to semidilute brush regimes. These findings suggest the existence of a hitherto unreported dynamic length scale connected with theoretically predicted static fluctuations in spherical polymer brushes and provide new insights into recent experimental observations.

Molecular dynamics simulation of RAC1 protein and its de novo variants related to developmental disorders

Neurodevelopmental disorders (NDDs) are conceptualized as childhood disability, but it has increasingly been recognized as lifelong neurological conditions that could notably impact adult functioning and quality of life. About 1%-3% of the general population suffers from NDDs including ADHD, ASD, IDD, communication disorders, motor disorders, etc. Studies suggest that Rho GTPases are key in neuronal development, highlighting the importance of altered GTPase signaling in NDDs. RAC1, a member of the Rho GTPase family, plays a critical role in neurogenesis, migration, synapse formation, axon growth, and regulation of actin cytoskeleton dynamics. We performed 6µs all-atom molecular dynamics simulation of native RAC1 (PDB: 3TH5) and three-point mutations (C18Y, N39S, and Y64D) related to developmental disorders to understand the impact of mutations on protein stability and functional dynamics. Our analysis, which included root mean square deviation (RMSD), root mean square fluctuation (RMSF), solvent accessible surface area (SASA), radius of gyration (Rg), free energy landscape (FEL), and principal component analysis (PCA), revealed that the N39S and Y64D mutations induced significant structural changes in RAC1. These alterations primarily occurred in the functional region adjacent to switch II, a region crucial for complex conformational rearrangements during the GDP and GTP exchange cycle. Communicated by Ramaswamy H. Sarma