Radius Of Gyration Research Articles

Investigation of Cellulose-Based Materials Applied in Life Sciences Using Laser Light Scattering Methods.

This review emphasizes the practical importance of laser light scattering methods for characterizing cellulose and its derivatives. The physicochemical parameters like molecular weights, the radius of gyration, hydrodynamic radius, and conformation will be considered when the reproducibility of polymer behavior in solution is necessary for the subsequent optimization of the property profile of a designed product. Since there are various sources of cellulose, and the methods of cellulose extraction and chemical modification have variable yields, materials with variable molecular weights, and size polydispersity will often result. Later, the molecular masses will influence other physicochemical properties of cellulosic materials, both in solution and solid state. Consequently, the most rigorous determination of these quantities is imperative. In this regard, the following are presented and discussed in this review: the theoretical foundations of the light scattering phenomenon, the evolution of the specific instrumentation and detectors, the development of the detector-coupling techniques which include a light scattering detector, and finally, the importance of the specific parameters of polymers in solution, resulting from the data analysis of light scattering signals. All these aspects are summarized according to the chemical classification of the materials: celluloses, esters of cellulose, co-esters of cellulose, alkyl esters of cellulose, ethers of cellulose, and other heterogeneous cellulose derivatives with applications in life sciences.

Comprehensive analysis of colloid formation, distribution, and properties of monovarietal red wines using asymmetrical flow field-flow fractionation with online multidetection

Red wine colloids, crucial in determining wine quality and stability, are understudied due to inadequate techniques for studying them effectively in the natural wine environment. Recently, Asymmetrical Flow Field-flow Fractionation (AF4) with online multidetection has emerged as a novel analytical tool for quantifying, fractionating, and characterizing red wine colloids in their native state. This study aimed to characterize the colloidal composition of 24 monovarietal Italian wines produced without filtration, oak contact, fining treatments, malolactic fermentation, macerating enzymes or ageing on yeast lees. AF4 analysis allowed quantification and characterization of wine colloids based on light scattering signal (MALS; gyration radius − Rg), size (hydrodynamic radius – Rh) and absorbance (A280 & A520 nm).The results showed that each wine contained up to five distinct colloids’ populations, varying in size and gyration radii. Despite possessing very similar Rh, most colloids exhibited great differences in compactness, as indicated by their varying Rg values. Comparing the A280 signal of whole wines to those of wines containing only species larger than 5 kDa (considered colloids) allowed to calculate the percentage of molecules involved in colloidal particles assembly, ranging from 1 to 44 % of the total A280 absorbing compounds, reflecting the diversity among wines. The A520 signal indicated the presence of polymeric pigments in the colloidal fraction. Notably, colored colloids all had Rg > 20 nm, indicating their association with other colloidal-forming compounds. This observation led to the conclusion that, apart from free anthocyanins and polymeric pigments, the color of red wines is also due to colloidal particles formed by the latter bound to proteins, with their quantity being highly variable across wines of different origin. These findings, which highlight the fundamental role of proteins in shaping the colloidal status of red wines, were utilized to propose an updated hypothetical model for colloidal aggregation in red wine.

Green synthesis, density functional theory (DFT), molecular docking, molecular dynamics simulation and biological activity of 1,2,3,4-tetrahydropyrimidine-5-carbonitrile derivatives as PLA2 and proteinase K inhibitors

In diseases like atherosclerosis, rheumatoid arthritis, and sepsis, phospholipase A2 (PLA2) and proteinase K play a role in inflammation by releasing arachidonic acid (AA). The crucial step in the inflammatory process is believed to be the release of prostaglandins after PLA2 mobilizes AA. Drugs obstructing the COX and LOX pathways in the arachidonic acid cascade, drugs that inhibit these enzymes can treat inflammatory processes. To combat against these inflammatory promoters,the authors herein report an effective method for the synthesis of a series of 1,2,3,4-tetrahydropyrimidine-5-carbonitrile derivatives (4a–h) under the effect of TiO2 as a photocatalyst in ethanolic medium, and their effect against phospholipase A2, as well as proteinase K, was evaluated. The results confirmed that using TiO2 (20 mg) as a photocatalyst exhibits excellent performance in terms of yield and reaction time. The yield of all the synthesized compounds is between 79 and 91 % in just 60 min. After closely evaluating the SAR of the examined compounds against both enzymes, it was discovered that compounds (4b, 4f) with electron-donating substituents have higher PLA2 inhibitory (%) activity than those with electron-removing substituents (4a, 4e). Compounds (4c, 4d) containing heterocyclic rings showed significantly higher proteinase inhibitory (%) activity when compared to other electron-donating or withdrawing compounds. It was further confirmed that studied compounds against both enzymes exhibited dose-dependent behavior. We studied the intermolecular interactions of the compounds by molecular docking with human non-pancreatic secretory phospholipase A2 and proteinase K. We evaluated the dynamical stability of the docked complexes using a 100 ns molecular dynamics simulation, which revealed stable interactions based on root mean square deviation/fluctuation (RMSD/RMSF), radius of gyration, Gibbs free energy landscapes, and principal component analyses (PCA). Moreover, the ADME properties of the compounds align with Lipinski’s rule of five, suggesting their potential as viable candidates for the development of therapies against inflammatory diseases. All compounds tested inhibited PLA2 more than proteinase K. However, compounds 4b and 4f better inhibited phospholipase A2, whereas compounds 4c and 4d showed better activity against proteinase K.

Degradation of molecular structure and residual strength of polycarbonate under cyclic loading: Insights from coarse-grained molecular dynamics simulation

Coarse-grained molecular dynamics simulations have been employed to provide insights into the molecular behavior and degradation of monodisperse polycarbonate subjected to cyclic loading with varying molecular structures characterized by two distinct parameters: radius of gyration and molecular entanglement. The fatigued polycarbonate structures were subjected to monotonic deformation in order to assess their residual strength. Our findings reveal that structures characterized by a higher degree of molecular entanglement exhibit a more significant loss of residual strength, attributable to the disentanglement induced by cyclic deformation. Furthermore, an increase in the radius of gyration contributes to greater resilience against cyclic loading, resulting in a higher level of residual strength compared to the impact of molecular entanglement.

Inactivation of polyphenol oxidase by low intensity DC field: Experiment and mechanism analysis via molecular dynamics simulation and molecular docking

In this study, inactivation of mushroom polyphenol oxidase (PPO) by low intensity direct current (DC) electric field and its molecular mechanism were investigated. In the experiments under 3 V/cm, 5 V/cm, 7 V/cm and 9 V/cm electric fields, PPOs were all completely inactivated after different exposure times. Under 1 V/cm, a residual activity of 11.88 % remained. The inactivation kinetics confirms to Weibull model. Under 1–7 V/cm, n value closes to a constant about 1.3. The structural analysis of PPO under 3 V/cm and 5 V/cm by fluorescence emission spectroscopy and molecular dynamics (MD) simulation showed that the tertiary structure was slightly changed with increased radius of gyration, higher potential energy and rate of C-alpha fluctuation. After exposure to the electric field, most of the hydrophobic tryptophan (TRP) residues turned to the hydrophilic surface, resulting the fluorescence red-shifted and quenched. Molecular docking indicated that the receptor binding domain of catechol in PPO was changed. PPO under electric field was MD simulated the first time, revealing the changing mechanism of the electric field itself on PPO, a binuclear copper enzyme, which has a metallic center. All these suggest that the low intensity DC electric field would be a promising option for enzymatic browning inhibition or even enzyme activity inactivation.

Unlocking enhanced thermal conductivity in polymer blends through active learning

Polymers play an integral role in various applications, from everyday use to advanced technologies. In the era of machine learning (ML), polymer informatics has become a vital field for efficiently designing and developing polymeric materials. However, the focus of polymer informatics has predominantly centered on single-component polymers, leaving the vast chemical space of polymer blends relatively unexplored. This study employs a high-throughput molecular dynamics (MD) simulation combined with active learning (AL) to uncover polymer blends with enhanced thermal conductivity (TC) compared to the constituent single-component polymers. Initially, the TC of about 600 amorphous single-component polymers and 200 amorphous polymer blends with varying blending ratios are determined through MD simulations. The optimal representation method for polymer blends is identified, which involves a weighted sum approach that extends existing polymer representation from single-component polymers to polymer blends. An AL framework, combining MD simulation and ML, is employed to explore the TC of approximately 550,000 unlabeled polymer blends. The AL framework proves highly effective in accelerating the discovery of high-performance polymer blends for thermal transport. Additionally, we delve into the relationship between TC, radius of gyration (Rg), and hydrogen bonding, highlighting the roles of inter- and intra-chain interactions in thermal transport in amorphous polymer blends. A significant positive association between TC and Rg improvement and an indirect contribution from H-bond interaction to TC enhancement are revealed through a log-linear model and an odds ratio calculation, emphasizing the impact of increasing Rg and H-bond interactions on enhancing polymer blend TC.

Predicting optimal chain lengths in atomistic simulations of solvated polymers

ABSTRACT Currently, clear guidance is not available for determining the minimum practical chain lengths needed for achieving reasonable convergence when performing atomistic simulations of common synthetic polymers. Here, we analyze a collection of polymers, including polypropylene (PP), polyethylene naphthalate (PEN), polyethylene terephthalate (PET), polyethylene glycol (PEG), poly(methyl methacrylate) (PMMA), polystyrene (PS), and polyvinyl chloride (PVC), with chain lengths varying from 5 to 240 repeat units. We exclusively focus on solvated polymer systems, and we report the convergence of several characteristic properties, such as radial distribution functions (RDFs), surface area per repeat unit (SASA/N), ratio of mean squared end-to-end distance to mean squared radius of gyration ( 〈 R 2 〉 〈 R g 2 〉 ), and surface electrostatic potential distributions. Based on these data, we propose a general relationship for identifying minimum practical chain lengths for performing atomistic simulations of solvated linear synthetic polymers, which is based on the SASA/N.

The influence of anions in the ionic liquid-water mixtures on the conformational structures of emeraldine base and emeraldine salt form of polyaniline

The development of antifouling membranes for water filtration applications is challenging. Conducting polymers can show enhanced antifouling characteristics by blending with various polymers, nanomaterials, and Ionic liquids (ILs). In this paper, we perform an all-atom molecular dynamics simulation on a conducting polymer polyaniline (PANI) immersed in IL-water mixtures. Two forms of PANI were considered, namely Emeraldine base (EB) and Emeraldine salt (ES) as well as two different water-mixed ILs are considered namely (a) 1-ethyl-3-methyl imidazolium [EMIM]+ hexafluorophosphate [PF6]- and (b) 1-ethyl-3-methyl imidazolium [EMIM]+ tetra-fluoroborate [BF4]-. We present various intra- and inter-molecular structural properties, solvation thermodynamics, and dynamic properties. We observe that with an increase in IL concentration, the radius of gyration (Rg) value shows a decrease for ES in pure state in both ILs; on the other hand, we see a minimal increase in the Rg values of EB in both ILs. The dihedral angle distribution analysis shows a combination of gauche and trans state for ES, whereas trans state is more pronounced for the case of EB in both water-IL mixtures. The radial distribution function (RDF) analysis between the ortho, meta carbons of the benzene rings, and the amine groups on ES with [BF4]- and [PF6]- show significant structural peaks. On the other hand, EB and ES show lower interaction with the water molecules. The number of hydrogen bonds (h-bonds) between polymer and water is higher for EB than ES in both IL-water mixtures. The hydrogen bond lifetime (τ) values show one-fold higher values for EB than ES. The self-diffusion coefficient (D) values of water show a decrease with an increase in IL concentration. The thermodynamic properties solvation enthalpy (ΔH) and excess molar volume (VmE) for both ES and EB show a more favorable solvation in [EMIM]+[BF4]- when compared to [EMIM]+[PF6]- with an increase in IL concentration. These observations are crucial for selecting ILs and designing sustainable polymers for antifouling membranes.

Molecular hybrids based on 1,2,3-triazole and 1,3,4-thiadiazole cores: Synthesis, characterization, anticancer activity and in silico study

One sets of 1,3,4-thiadiazole analogs 14a-c and 15a-c were synthesized by the incorporation of two heterocyclic nuclei (1,2,3-triazole & 1,3,4-thiadiazoles) in objective of developing multifunctional molecules for anticancer disease. (R)-Carvone was used as precursors for the synthesis of new heterocycles. The 1,2,3-triazole-1,3,4-thiadiazoles 14a-c and 15a-c were synthesized in good yields from the precursors using simple procedures. The chemical structures of all the newly synthesized hybrids were established using (1H and 13C) NMR and HRMS analysis. The in vitro assessment of the activity of the resultant 1,2,3-triazole-1,3,4-thiadiazoles against human cancer cells, namely fibrosarcoma (HT-1080), lung carcinoma (A-549) and breast carcinoma (MCF-7 and MDA-MB-231) was performed using viability testing (MTT). Compound 14a was the most active heterocycle, and its cytotoxic activity was three times less actives comparable to that obtained for Doxorubicin (6 µM) as a reference. The 1,3,4-thiadiazoles 15a-c showed moderate cytotoxic activities with IC50 values ranging from 25.56 ± 1.13 to 61.81 ± 2.21 μM. Molecular docking studies were conducted against two antiapoptotic proteins namely Bcl-2, and Bcl-XL to elucidate the potential mechanisms of action. The results indicate that compounds interact favorably (binding energy = −7.6 to −9.8 kcal/mol) with the target proteins through hydrophobic, electrostatic interactions, and hydrogen bonding. The negative binding energy indicate the spontaneous nature of the interaction. Further, molecular dynamics simulation parameters such as root mean square deviation, root mean square fluctuation, radius of gyration, and solvent accessible surface area provided insights into the stability and dynamics of the protein-ligand complexes.

Molecular dynamics simulations of the solubility of chitosan grafted polyacrylamide and its adsorption mechanism with kaolinite: Impact of length and distribution of branched‐chain

AbstractGraft modification can effectively improve the flocculation performance of chitosan. In this work, molecular dynamics simulations were employed to investigate the water solubility of chitosan‐grafted polyacrylamide (CTS‐g‐PAM) and its adsorption mechanism with kaolinite, focusing on the effects of branched‐chain length and distribution. The solubility parameters obtained from the simulations align better with those calculated using the group contribution method. The radius of gyration (Rg), solvation free energy (∆GSFE), mean square displacement and diffusion coefficient were utilized to analyze changes in solubility of these CTS‐g‐PAM in aqueous solution. The adsorption interaction between CTS‐g‐PAM and kaolinite was investigated using interaction energy and diffusion coefficients. The water solubility of CTS‐g‐PAM initially increased, followed by a subsequent decrease as the length of branched‐chain increased along with a decrease in their number. Similarly, the adsorption interaction between CTS‐g‐PAM and kaolinite increased firstly followed by a decrease with increasing branched‐chain length. The magnitude of interaction energy with kaolinite (0 0 1) followed the order of CA10‐12 (−826.227 kcal/mol) >CA8‐15 (−744.583 kcal/mol) >CA6‐20 (−637.366 kcal/mol) >CA12‐10 (−598.109 kcal/mol). These trends align with the findings of flocculation tests. Our work provides a theoretical basis for designing chitosan‐based flocculants with enhanced water solubility and improved flocculation efficiency.

Map conformational landscapes of intrinsically disordered proteins with polymer physics quantities

Disordered proteins are conformationally flexible proteins that are biologically important and have been implicated in devastating diseases such as Alzheimer’s disease and cancer. Unlike stably folded structured proteins, disordered proteins sample a range of different conformations that needs to be accounted for. Here, we treat disordered proteins as polymer chains, and compute a dimensionless quantity called instantaneous shape ratio (Rs), as Rs = Ree2/Rg2, where Ree is end-to-end distance and Rg is radius of gyration. Extended protein conformations tend to have high Ree compared with Rg, and thus have high Rs values, whereas compact conformations have smaller Rs values. We use a scatter plot of Rs (representing shape) against Rg (representing size) as a simple map of conformational landscapes. We first examine the conformational landscape of simple polymer models such as Random Walk, Self-Avoiding Walk, and Gaussian Walk (GW), and we notice that all protein/polymer maps lie within the boundaries of the GW map. We thus use the GW map as a reference and, to assess conformational diversity, we compute the fraction of the GW conformations (fC) covered by each protein/polymer. Disordered proteins all have high fC scores, consistent with their disordered nature. Each disordered protein accesses a different region of the reference map, revealing differences in their conformational ensembles. We additionally examine the conformational maps of the nonviral gene delivery vector polyethyleneimine at various protonation states, and find that they resemble disordered proteins, with coverage of the reference map decreasing with increasing protonation state, indicating decreasing conformational diversity. We propose that our method of combining Rs and Rg in a scatter plot generates a simple, meaningful map of the conformational landscape of a disordered protein, which in turn can be used to assess conformational diversity of disordered proteins.

A Structure Independent Molecular Fragment Interfuse Model for Mesoscale Dissipative Particle Dynamics Simulation of Peptides.

There is a need to develop robust computational models for mesoscale simulation of the structure of peptides over large length scales toward the discovery of novel peptides for medical applications to address the issues of peptide aggregation, enzymatic degradation, and short half-life. The primary objective was to predict the structure and conformation of peptides whose native structures are not known. This work presents a new model for computation of interaction parameters between the beads in coarse-grained dissipative particle dynamics (DPD) simulation that is properly calibrated for amino acids, supports compressibility requirement of water molecules, and accounts for subtle differences in the structure of amino acids and the charge in the side chain of charged amino acids. This new model is referred to as Structure Independent Molecular Fragment Interfuse Model, abbreviated as SIMFIM, because it accounts for specific interactions between different beads, which represent molecular fragments of the amino acids, in calculating nonbonded interaction parameters in the absence of knowing the actual peptide structure. The electrostatic interactions are incorporated in this model by using a normal distribution of charges around the center of the beads to prevent the collapse of oppositely charged soft beads. The uniquely parameterized DPD force field in the SIMFIM model is optimized for a given peptide with respect to the degree of coarse-grained graining for simulating the peptide over long times and length scales. The SIMFIM model was tested in this work using four peptides, namely, TrpZip2, Rubrivinodin, Lihuanodin, and IC3-CB1/Gai peptides, whose structures were sourced from the Protein Data Bank. The SIMFIM model predicted radius of gyration (Rg) values for the peptides closer to the actual structures as compared to the conventional model, and there was less deviation between the predicted and actual structures of the peptides.

Depletion-Induced Self-Assembly of Colloidal Particles on a Solid Substrate.

We investigate the depletion contributions to the self-assembly of microcolloids on solid substrates. The assembly is driven by the exclusion of nanoparticles and nonadsorbing polymers from the depletion zone between the microcolloids in the liquid and the underlying substrate. The model system consists of 1 μm polystyrene particles that we deposit on a flat glass slab in an electrolyte solution. Using polystyrene nanoparticles and poly(acrylic acid) polymers as depleting agents, we demonstrate in our experiments that nanoparticle concentrations of 0.5% (w/v) support well-ordered packing of microcolloids on glass, while the presence of polymers leads to irregular aggregate deposition structures. A mixture of nanoparticles and polymers enhances the formation of colloidal aggregate and particulate surface coverage compared to using the polymers alone as a depletion agent. Moreover, tuning the polymer ionization state from pH 4 to 9 modifies the polymer conformational state and radius of gyration, which in turn alters the microcolloid deposition from compact multilayers to flocculated structures. Our study provides entropic strategies for manipulating particulate assembly on substrates from dispersed to continuous coatings.

Design, synthesis, and bioevaluation of novel unsaturated cyanoacetamide derivatives: In vitro and in silico exploration

In this study, we synthesized novel α,β-unsaturated 2-cyanoacetamide derivatives (1–5) using microwave-assisted Knoevenagel condensation. Characterization of these compounds was carried out using FTIR and 1H NMR spectroscopy. We then evaluated their in vitro antibacterial activity against both gram-positive and gram-negative pathogenic bacteria. Additionally, we employed in silico methods, including ADMET prediction and density functional theory (DFT) calculations of molecular orbital properties, to investigate these cyanoacetamide derivatives (1–5). Molecular docking was used to assess the binding interactions of these derivatives (1–5) with seven target proteins (5MM8, 4NZZ, 7FEQ, 5NIJ, ITM2, 6SE1, and 5GVZ) and compared them to the reference standard tyrphostin AG99. Notably, derivative 5 exhibited the most favorable binding affinity, with a binding energy of -7.7 kcal mol−1 when interacting with the staphylococcus aureus (PDB:5MM8), while also meeting all drug-likeness criteria. Additionally, molecular dynamics simulations were carried out to evaluate the stability of the interaction between the protein and ligand, utilizing parameters such as Root-Mean-Square Deviation (RMSD), Root-Mean-Square Fluctuation (RMSF), Radius of Gyration (Rg), and Principal Component Analysis (PCA). A 50 nanosecond molecular dynamics (MD) simulation was performed to investigate stability further, incorporating RMSD and RMSF analyses on compound 5 within the active binding site of the modeled protein across different temperatures (300, 305, 310, and 320 K). Among these temperatures, compound 5 exhibited an RMSD value ranging from approximately 0.2 to 0.3 nm at 310 K (body temperature) with the 5MM8 target, which differed from the other temperature conditions. The in silico results suggest that compound 5 maintained significant conformational stability throughout the 50 ns simulation period. It is consistent with its low docking energy and in vitro findings concerning α,β-unsaturated cyanoacetamides.Key insights from this study include:•The creation of innovative α,β-unsaturated 2-cyanoacetamide derivatives (1–5) employing cost-effective, licensed, versatile, and efficient software for both in silico and in vitro assessment of antibacterial activity.•Utilization of FTIR and NMR techniques for characterizing compounds 1–5.

Molecular Simulation Study of the Kinetics and Mechanism of Micellization of Charged and Uncharged Block Copolymer in Aqueous Solution: Polystyrene-Block-Poly(acrylic acid) PS-b-PAA

The micellization kinetics, dynamics, and diffusional properties of poly(styrene)-block-poly(acrylic acid) copolymer chains in salt-free aqueous solution have been investigated as a function of the copolymer composition (XPS ) for the cases of un-ionized (charge density f = 0) and ionized PAA blocks (charge density f = 1), for the first time to our knowledge via atomistic molecular dynamic simulations. The micelle formation mechanism was inspected by tracking the population of unimers and clusters across the simulation trajectory; it confirmed that the asymmetric copolymer micelle formation followed a combined approach of unimer insertion and cluster fusion mechanisms, while symmetric micelle formation followed the unimer insertion method exclusively. Micelle formation took a longer time for copolymers having charged (ionized) PAA blocks (f > 0) and relatively short PS blocks (number fraction of PS repeat units in copolymer XPS < 0.5) due to the presence of a greater number of hydrophobic groups, in agreement with the micellization kinetics observed for model copolymer micelles via DPD (Dissipative Particle Dynamics) simulation studies in literature. The conformational dynamics were studied using the relaxation of backbone dihedral angles and radius of gyration, for the core and corona blocks, respectively, showed that the PS blocks relaxed slower as compared to the soluble PAA blocks in solution due to their hydrophobic nature. The conformational relaxation time increased linearly for the PS blocks and was invariant for the PAA blocks with respect to XPS. The interaction dynamics of the PS-b-PAA copolymer micelles studied via the relaxation times of the PAA-PAA inter-chain (τHB,PP) and PAA-water inter-molecular hydrogen bonds (τHB,PW) showed the increase of τHB,PP, and the decrease of τHB,PW in solution with the increase in XPS. The PAA-water H-bond relaxes slower at f = 1 than that at f = 0 due to the stronger affinity of ionized PAA units with water molecules. The diffusivity of the copolymer chains decreased exponentially with an increase in XPS value, which is in agreement with the theoretical and experimental observations described in the literature.

TrajSGAN: A Semantic-Guiding Adversarial Network for Urban Trajectory Generation

Simulating human mobility contributes to city behavior discovery and decision-making. Although the sequence-based and image-based approaches have made impressive achievements, they still suffer from respective deficiencies such as omitting the depiction of spatial properties or ordinal dependency in trajectory. In this article, we take advantage of the above two paradigms and propose a semantic-guiding adversarial network (TrajSGAN) for generating human trajectories. Specifically, we first devise an attention-based generator to yield trajectory locations in a sequence-to-sequence manner. The encoded historical visits are queried with semantic knowledge (e.g., travel modes and trip purposes) and their important features are enhanced by the multihead attention mechanism. Then, we designate a rollout module to complete the unfinished trajectory sequence and transform it into an image that can depict its spatial structure. Finally, a convolutional neural network (CNN)-based discriminator signifies how “real” the trajectory image looks, and its output is regarded as a reward signal to update the generator by the policy gradient. Experimental results show that the proposed TrajSGAN model significantly outperforms the benchmarks under the MTL-Trajet mobility dataset, with the divergence of spatial-related metrics such as radius of gyration and travel distance reduced by 10%–27%. Furthermore, we apply the real and synthetic trajectories, respectively, to simulate the COVID-19 epidemic spreading under three preventive actions. The coefficient of determination metric between real and synthetic results achieves 91%–98%, indicating that the synthesized data from TrajSGAN can be leveraged to study the epidemic diffusion with an acceptable difference. All of these results verify the superiority and utility of our proposed method.

Study on the interaction mechanism between (−)-epigallocatechin-3-gallate and myoglobin: Multi-spectroscopies and molecular simulation

(−)-Epigallocatechin-3-gallate (EGCG) is remarkably efficacious in inhibiting the browning of red meat. We therefore propose a hypothesis that EGCG forms complexes with myoglobin, thereby stabilizing its structure and thus preventing browning. This study investigated the interaction mechanism between EGCG and myoglobin. EGCG induced static quenching of myoglobin. Noncovalent forces, including hydrogen bonds and van der Waals, primarily governing the interactions between myoglobin and EGCG. The interactions primarily disrupted myoglobin's secondary structure, thus significantly reducing surface hydrophobicity by 53% (P < 0.05). The modification augmented the solubility and thermal stability of myoglobin. The radius of gyration (Rg) value fluctuated between 1.47 and 1.54 nm, and the hydroxyl groups in EGCG formed an average of 2.93 hydrogen bonds with myoglobin. Our findings elucidated the formation of stable myoglobin–EGCG complexes and the myoglobin–EGCG interaction, thus confirming our initial hypothesis.

Investigating with molecular dynamics, self-assembly of enantiomeric forms of PLA/functionalized-PLA in different solvent conditions

Poly-lactic acid is a versatile biopolymer with excellent mechanical and biological properties, making it suitable for various industrial applications. Enantiomeric forms of PLA can self-assemble into macromolecular nanoparticles with tunable functionalities, further enhancing their potential applications. In this study, the solvated behavior of single and multiple chains of enantiomeric forms of native and functionalized PLA chains in different solvents is investigated via MD simulations to understand the molecular level interactions between them. Self-assembled polymeric structures are analyzed based on the evaluation of their radius of gyration and solvent accessible surface area. Molecular interactions between PLA-PLA and PLA-solvent are explored by examining the number of inter-molecular h-bonds, radial distribution functions and PLA-solvent vdW/coulombic interactions. Outcomes provide insights into the comparative stability of PLA enantiomeric forms in different solvents, the role of solvents in self-assembly, the anticipated impact of functionalization on the self-assembly process and the favorability of stereocomplexation in different solvents.

Synthesis, Molecular Docking, Molecular Dynamic Simulation Studies, and Antitubercular Activity Evaluation of Substituted Benzimidazole Derivatives.

Tuberculosis, also known as TB, is a widespread bacterial infection that remains a significant global health issue. This study focuses on conducting a thorough investigation into the synthesis, evaluation of anti-Tb activity, molecular docking, and molecular dynamic simulation of substituted benzimidazole derivatives. A series of twelve substituted benzimidazole derivatives (1-12) were successfully synthesized, employing a scaffold consisting of electron-withdrawing and electron-donating groups. The newly synthesized compounds were defined by their FTIR, 1H NMR, and mass spectra. The microplate Alamar blue assay (MABA) was used to evaluate the antimycobacterial activity of the synthesized compound against Mycobacterium tuberculosis (Mtb). Compounds 7 (MIC = 0.8 g/mL) and 8 (MIC = 0.8 g/mL) demonstrated exceptional potential to inhibit M. tuberculosis compared to the standard drug (isoniazid). In addition, the synthesized compounds were docked with the Mtb KasA protein (PDB ID: 6P9K), and the results of molecular docking and molecular dynamic simulation confirmed the experimental results, as compounds 7 and 8 exhibited the highest binding energy of -7.36 and -7.17 kcal/mol, respectively. The simulation results such as the RMSD value, RMSF value, radius of gyration, and hydrogen bond analysis illustrated the optimum potential of compounds 7 and 8 to inhibit the M. tuberculosis strain. Hydrogen bond analysis suggested that compound 7 has greater stability and affinity towards the KasA protein compared to compound 8. Moreover, both compounds (7 and 8) were safe for acute inhalation and cutaneous sensitization. These two compounds have the potential to be potent M. tuberculosis inhibitors.

Insights into the structure–function relationship of missense mutations in the human TOP2A protein in ovarian cancer

Topoisomerase 2-alpha (TOP2A) is a nuclear protein that is responsible for the maintenance of the topological state of DNA. TOP2A is highly upregulated in ovarian cancer, and its copy number is an important prognosis factor. A large number of single-nucleotide polymorphism (SNP), insertion, and deletion mutations have been reported in TOP2A. Thus, a structural and functional study of missense SNPs was carried out to screen potentially damaging mutations. The 193 non-synonymous SNPs in the coding region of TOP2A in the dbSNP database were selected for in silico analysis. The deleterious SNPs were screened using sorting intolerant from tolerant (SIFT), PolyPhen-2, SNAP2, and SNPs&amp;amp;Go, and we obtained four possibly damaging SNPs at the end (Y481C, N7741, E922K, and R1514W). Mutants Y481C and E922K were predicted to be highly deleterious and showed decreased protein stability compared with native proteins, as predicted by I-Mutant 3. We used the SWISS-MODEL to model the structure of these two mutants, and the structural attributes of modeled mutants were studied using Hope Project, solvent accessibility-based protein–protein interface identification and recognition (SPPIDER), SRide, and HBAT, which predicted small variations from the native protein. Molecular dynamics simulation demonstrated a decrease in root mean square deviation (RMSD) and the radius of gyration of two mutants, which is relative to the native protein. The molecular docking of TOP2A with etoposide suggests that mutations may lead to resistance to TOP2A-targeted chemotherapy. In addition, the relative expression analysis performed by qRT-PCR also reveals that there is a three-fold increase in the expression levels of the TOP2A protein in ovarian adenoma cancer cell lines. Our analysis reveals that Y481C and E922K are highly damaging variants of TOP2A, which alter the protein dynamics and may be implicated in causing ovarian cancer.