Nonbonded Interactions Research Articles

Martini compatible coarse-grained model of polyethylenimine for pulmonary gene delivery

Pulmonary gene delivery has demonstrated high specificity for respiratory diseases, offering great control on dosage of therapeutics and side effects. On the other hand, intrinsic barriers in pulmonary systems impose new challenges such as crossing the pulmonary surfactant and evading mucus entrapment. Differences in hydrophobicity of plasma membrane and pulmonary surfactant require different chemistries of gene carriers to improve efficacy. Large-scale coarse-grained (CG) molecular dynamics simulations would facilitate the screening of gene carriers and understanding of the molecular mechanisms involved in pulmonary delivery. Among non-viral carriers, polyethyleneimine (PEI) has been a promising candidate that can be synthesized with various molecular weight, degree of branching, and functionalization. In this work, CG models are developed for PEI and its lipid-functionalized form, within the Martini framework, to provide a platform for exploring structure-function relationships of PEI-based pulmonary delivery systems. Special attention is focused on parameterizing the non-bonded interactions associated with CG PEI, to ensure compatibility with Martini proteins, short interfering RNA, and phospholipids that are essential components in pulmonary gene delivery. The non-bonded parameters are validated by comparing all-atom (AA) and CG potential of mean force (PMF) curves, where the root-mean-square deviations between the AA and CG PMF curves are shown to be comparable to or smaller than those reported in Martini literature.

Quantum Mechanics-Calibrated Classical Simulation of Earth-Abundant Divalent Metal Bis(trifluoromethanesulfonyl)imide Molar Conductivity in Organic Cosolvents with Onsager Transport Formalism.

Molar conductivities are one of the fundamental transport properties of electrolytes that reflect the complex and dynamic interactions between ions and solvents comprehensively. The quantitative accuracy of experimental input-free simulations of molar conductivities is strongly influenced by the underlying interaction parameters employed in the model. When validated with experimental molar conductivities, the developed model could be used to reveal further atomistic level details about the solvation structures and correlated ion pair formation, providing in-depth knowledge about solution physical chemistry and shedding light on electrolyte-solvent system design rules. Divalent cations are more challenging to model than monovalent cations due to their higher charge densities and stronger interactions with the environment. Yet, they started attracting significant attention for next-generation energy storage purposes. In this work, we focus on two earth-abundant divalent cation electrolytes, Mg(TFSI)2 and Ca(TFSI)2 in a dimethylacetamide-tetrahydrofuran (DMA-THF) cosolvent system. We used quantum mechanical cluster models to optimize the force field parameters (including the pairwise nonbonded interaction parameters and atomic charges) to be applied in classical simulations. With the reliable force field model, we discussed the importance of including ion correlation explicitly in predicting the molar conductivities via the Onsager formalism and showed that the conventional Nernst-Einstein formula overestimates ionic mobilities due to its intrinsic independent and uncorrelated particle assumption. Further, we investigated the solvation structures and ion pair formations. We concluded that the suitability of the interaction potentials utilized in a classical model for particular systems needs to be assessed not solely by directly comparing the simulated molar conductivities with the measured ones but, more importantly, by using the correct formalism (Onsager) to deduce the simulated result from dynamics trajectories.

Circularly Polarized Luminescence Inversion in AIE‐Active Crystal Enabled by Solvent‐Induced Transition Dipole Moment Regulation

ABSTRACTControl of the dissymmetry of circularly polarized luminescence (CPL) is intriguing and has great potential for applications in the field of optics. The traditional control strategy involves using the opposite enantiomers to achieve reversal of CPL signs. However, regulating CPL reversal by controlling only the transition dipole moments without changing molecular or supramolecular chirality remains a challenge. Herein, we developed a couple of crystal materials based on axially chiral aggregation‐induced emission luminogens (AIEgens). These materials exhibit achiral solvent‐induced CPL sign inversion with identical helical structures and molecular chirality in their crystalline states. (R)‐BPAuCzT displays (+)‐CPL with a dissymmetry factor of luminescence (glum) value of +9.81 × 10−4 (560 nm), while (R)‐BPAuCzC exhibits (−)‐CPL with a glum value of −1.02 × 10−3 (560 nm). Time‐dependent density functional theory calculations show that the magnetic and electric transition dipole moments at S1 → S0 of the (R)‐BPAuCzC unit cell are considerably influenced by the cocrystallized solvent molecules, revealing a solvent‐induced CPL inversion mechanism. The nonbonding interactions between the solvent molecules (i.e., tetrahydrofuran or CDCl3) and AIEgens in the crystal play a crucial role in the manipulation of the transition dipole moment of these crystal materials. Moreover, microrods of (R)‐BPAuCzT, (R)‐BPAuCzC, and (R)‐BPAuCzDCE exhibit optical waveguide properties with relatively low optical‐loss coefficients of 187.3, 567.4, and 65.2 dB/cm, respectively. These findings can help in developing a new strategy toward controlling CPL signals and providing a potential application for future integrated photonic circuits.

Mechanism of High Hydrocarbon-Fuel-Gelation Performance of Ultralow-Concentration Bis-urea-Based Gellants.

Bis-urea-based gellants have garnered considerable attention due to their capacity to form all kinds of gels in solvents for multiple applications. Nevertheless, the range of applicable solvents is limited, and the synthesis process is complicated. Herein, we report a one-step synthesis process of bis-urea-based gellants (Bu(n)) for gelling nonpolar organic solvents, including high-energy fuels. Importantly, the critical gelation concentration (CGC) of Bu(n) decreases with the increase of alkyl chain length, and that of Bu18 is lower than 0.1 wt % in various hydrocarbon fuels. The discrepant gelation performance of gellants in solvents was investigated by molecular dynamics simulation and spectral characterizations. The results indicate that the electrostatic interaction between urea groups is vital to constructing a gellant framework, and the wide van der Waals (vdW) surface provided by alkyl groups helps to immobilize solvents. The nonbonding interactions between gellant molecules facilitate the formation of a 3D fibrous network structure, which further accumulates into a cambium layer structure. Due to the excellent gelation performance of gellants in fuels, the gel fuels perform the rheological characteristics of shear thinning and thixotropic recovering with calorific value remaining, thus demonstrating potential for application.

Drug delivery potential of γ-graphyne, 6,6,12-graphyne and γ-graphdiyne for 5-Fluorouracil: insights from DFT calculations

ABSTRACT The present work aims to investigate the potential of γ-Graphyne, 6,6,12-Graphyne and γ-Graphdiyne as nanocarriers for the anti-cancer drug 5-Fluorouracil (5FU) using density functional theory (DFT). The 5FU drug is effective in treating various cancers. However, 5FU results in severe toxicological damage to the gastrointestinal (GI) system and blood factors, which necessitates the development of promising drug delivery systems to achieve a better therapeutic effect with fewer side effects. To proceed with the aim, the drug and selected carriers were optimized using the DFT/B3LYP/6–31 G(d,p) method. The optimized drug was adsorbed on the surface of carriers and the existence of non-bonding interactions validated the adsorption process. The adsorption energies incorporating the basis set superposition error (BSSE) were calculated and analyzed. The solvent effect on the complexes was studied, and corresponding solvation energies were calculated. The interaction behavior of the drug-nanocarrier complexes has been analyzed at different pH values representative of the physiological range, including acidic, neutral and slightly basic conditions. The results suggest the capability of γ-Graphyne, 6,6,12-Graphyne and γ-Graphdiyne as carriers for 5-Fluorouracil drug in drug delivery system.

Aggregation Behavior of Asphaltenes in Heavy Oil and Its Influencing Factors: A Multiscale Study Based on Molecular Dynamics Simulations and Quantum Chemical Calculations

Summary Asphaltenes and resins are important and complex components of heavy oils, and their self-aggregation behavior has a profound effect on the oil and gas industry. In this study, based on three classical molecular models of asphaltenes, the aggregation laws of asphaltenes with different structures and their influencing factors were investigated using molecular dynamics (MD) simulations and quantum chemical calculations. By analyzing the equilibrium conformations, interaction energy, radial distribution functions (RDFs), mean square displacements (MSDs), diffusion coefficients, cluster analyses, radii of gyration, electrostatic potentials, and nonbonding interactions, we found that archipelago-type asphaltenes have the strongest interactions, the highest probability of occurrence, and the best stability. In contrast, continental asphaltenes have the strongest diffusion ability in the heavy oil model. Quantum chemical calculations show that the asphaltene association is mainly driven by van der Waals forces initiated by the aromatic core and electrostatic attraction around the heteroatoms, whereas the aggregation behavior is influenced by a variety of factors, such as intermolecular van der Waals forces, hydrogen bonding, and π-π interactions. In addition, external conditions, such as temperature and pressure, considerably affect the aggregation behavior of asphaltenes. This study provides a theoretical basis for exploring the viscosity mechanism of heavy oils and scientific support for the efficient development of oil and gas fields.

DFT Study of Interaction between Teriflunomide and β-cyclodextrin

Introduction: This study employs Density Functional Theory (DFT) to investigate the interactions between Teriflunomide and β-cyclodextrin in the gas phase. Method:: The non-bonded interaction effects of the Teriflunomide compound with β- cyclodextrin on the chemical shift tensors, electronic properties, and natural charge were also observed. An analysis of the natural bond orbital (NBO) indicated that the molecule β-cyclodextrin as an electron donor functions while Teriflunomide functions as an electron acceptor in the complex β-cyclodextrin/Teriflunomide. Result:: The electronic spectra of the Teriflunomide drug and complex β-cyclodextrin/ Teriflunomide were calculated by Time-Dependent Density Functional Theory (TDDFT) to investigate the adsorption effects of the Teriflunomide drug over β-cyclodextrin on maximum wavelength. Conclusion:: As a result, the possibility of the use of β-cyclodextrin for Teriflunomide delivery to the diseased cells has been established.

Thermal properties and non-bonded interactions in human PMP2 variants: A molecular dynamics study

Charcot-Marie-Tooth disease has been known for a long time, affecting population worldwide. Many studies on this disease have been conducted, including clinical as well as computational, but no effective medical cure has yet been found. This disease is caused due to mutation in the human peripheral myelin protein 2 (PMP2) responsible for myelin formation and maintenance. In this research work, we have done a comparative molecular dynamics study on the PMP2 protein and its M114T mutant variant, focusing on non-bonded interactions and thermal properties in a biologically relevant environment. The primary objective was to explore the structural differences between the two proteins at temperatures of 305 K, 310 K, and 315 K. Using the NAMD software for molecular dynamics simulations, various analyses were performed, including RMSD estimation, counting number of hydrogen bond formation, salt bridge occupancy assessment, estimation of vdW and electrostatic interaction energies in the system, and estimation of thermal diffusivity of the proteins as well as specific heat capacity (Cv) of the system. The results suggested slight difference between the structure of the two proteins. In the mutant, a slight increase in RMSD values was observed, suggesting a minor reduction in structural stability compared to the wild-type protein. The number of hydrogen bonds formed was generally higher in the wild-type protein, with slightly more differences observed at 305 K and 315 K than at 310 K. Analysis of salt bridge occupancy revealed notable differences in the formation patterns between the two proteins. The mutation was found to have a greater impact on salt bridge formation. In addition to this, the vdW and electrostatic interaction energies were found to be lower in the system with mutant variant, with both energies decreasing gradually as temperature increased, indicating a more robust interaction profile in the system with wild-type protein. Also, the estimated value of thermal diffusivity indicated that the mutant was slightly more efficient at conducting heat than the wild-type protein; the thermal diffusivity of both proteins was much lower than that of water. Finally, a non-linear (concave nature) change in Cv with temperature was observed in both protein systems. The work was further extended to verify the Maxwell-Boltzmann distribution law which confirmed the proper distribution of kinetic energy among particles, and the temperature fluctuation was found to follow a Gaussian distribution during the NVE simulation, which was as expected.

Influence of π-π interactions on organic photocatalytic materials and their performance.

Currently, organic photocatalyst-based photocatalysis has garnered significant attention as an environmentally friendly and sustainable reaction system due to the preferable structural flexibility and adjustable optoelectronic features of organic photocatalysts. In addition, π-π interactions, as one of the common non-bonded interactions, play an important role in the structure and property adjustments of organic photocatalysts due to their unique advantages in modulating the electronic structure, facilitating charge migration, and influencing interfacial reactions. However, studies summarizing the relationship between the π-π interactions of organic photocatalysts and their photocatalytic performance are still rare. Therefore, in this review, we introduced the types of π-π interactions, characterization techniques, and different types of organic photocatalytic materials. Then, the influence of π-π interactions on photocatalysis and the modification strategies of π-π interactions were summarized. Finally, we discussed their influence on photocatalytic performance in different photocatalytic systems and analyzed the challenges and prospects associated with harnessing π-π interactions in photocatalysis. The review provides a clear map for understanding π-π interaction formation mechanism and its application in organic photocatalysts, offering useful guidance for researchers in this field.

Nonbonded Molecular Interaction Controls Aggregation Kinetics of Hydrophobic Molecules in Water.

Molecular aggregation frequently occurs during material synthesis, cellular processes, and drug delivery systems, often resulting in decreased performance and efficiency. One major reason for such aggregation in an aqueous solution is hydrophobicity. While the basic understanding of the aggregation process of hydrophobic molecules from a thermodynamic standpoint is known, the present literature lacks a connection between the aggregation kinetics and the molecular basis of hydrophobicity. This study explores how various fluorescent probes (rhodamine dyes) aggregate in an aqueous solution due to their hydrophobicity. The method employs a combination of modeling and characterization to comprehend the aggregation process by examining the nonbonded intermolecular interactions. The aggregation kinetics was analyzed by measuring the average diffusivity of the molecules using fluorescent correlation spectroscopy and NMR diffusion measurements. Through all-atom molecular dynamics (MD) simulations, it has been observed that the level of hydrophobicity is strongly correlated to the total number of hydrogen bonds between water molecules and dyes. In addition, the aggregation frequency of colliding species, which depends on the concentration, is inversely related to hydrogen bonding and the diffusivity of the molecules. This study of small molecules was applied to predict protein aggregation rates, demonstrating strong alignment with the existing literature. The study has also helped to identify and understand the concentration at which a hydrophobic molecule does not aggregate in an aqueous solution. The method developed here could help investigate the aggregation process and its root causes at the molecular level in aqueous systems to develop strategies to control it.

Accurate Force Field for Carbon Dioxide-Silica Interactions Based on Density Functional Theory.

Fluid-silica interfaces are ubiquitous in chemistry, occurring in both natural geochemical environments and practical applications ranging from separations to catalysis. Simulations of these interfaces have been, and continue to be, a significant avenue for understanding their behavior. A constraining factor, however, is the availability of accurate force fields. Most simulations use traditional "mixing rules" to determine nonbonded dispersion interactions, an approach that has not been critically examined. Here, we present Lennard-Jones parameters for the interaction of carbon dioxide with silica interfaces that are optimized to reproduce density functional theory (DFT)-based binding energies. The modeling is based on the recently developed silica-DDEC force field, whose atomic charges are consistent with DFT calculations. Standard mixing rules are found to predict weaker CO2 binding to silica than that obtained from DFT, an effect corrected by the optimized parameters given here. This behavior extends to other silica force fields (Clayff and Gulmen-Thompson), and the present Lennard-Jones parameters improve their performance as well. The effects of improved Lennard-Jones parameters on the structural and dynamical properties of condensed CO2 in silica slit pores are also examined.

Meta-Learning Enables Complex Cluster-Specific Few-Shot Binding Affinity Prediction for Protein-Protein Interactions.

Predicting protein-protein interaction (PPI) binding affinities in unseen protein complex clusters is essential for elucidating complex protein interactions and for the targeted screening of peptide- or protein-based drugs. We introduce MCGLPPI++, a meta-learning framework designed to improve the adaptability of pretrained geometric models in such scenarios. To effectively boost the meta-learning optimization by injecting prior intersample distribution knowledge, three specially designed training sample cluster splitting patterns based on protein interaction interfaces are introduced. Additionally, MCGLPPI++ is equipped with an independent energy component which explicitly models interface nonbonded interaction energies closely related to the strengths of PPIs. To validate our approach, we curate a new data set featuring a challenging test cluster of T-cell receptors binding to antigenic peptide-MHC molecules (TCR-pMHC). Experimental results show that geometric models enhanced by the MCGLPPI++ framework achieve significantly more robust binding affinity predictions after fine-tuning on a few samples from this novel cluster compared to their vanilla counterparts, which demonstrates the effectiveness of the framework.

Concurrent targeted delivery of doxorubicin and curcumin to the cancer cells using simple and versatile ligand-installed multifaceted chitosan-based nanoconjugates.

Existing chemotherapeutic approaches against refractory cancers are ineffective due to off-target effects, inefficient delivery, and inadequate accumulation of anticancer drugs at the tumor site, which causes limited efficiency of drug treatment and toxicity to neighboring healthy cells. The development of nano-based drug delivery systems (DDSs) with the goal of delivering desired therapeutic doses to the diseased cells and has already proven to be a promising strategy to address these challenges. Our study focuses on achieving an efficient tumor-targeted delivery of a combination of drugs for therapeutic benefits by developing a versatile DDS by following a simple one-step chemical approach. We used low-molecular-weight chitosan and modified its primary amine groups with reactive forms of cholesterol and folic acid by simple chemical tools and thus prepared folic acid-chitosan-cholesterol graft copolymer. The polymer contains numerous residual primary amine groups, which offer enough water solubility and positive charge to its polymeric backbone to foster the interaction of negatively charged and/or hydrophobic drugs to load and encapsulate a wide variety of drugs within it via various non-bonding interactions. We used curcumin and doxorubicin as the combination of drugs and thus finally prepared targeted nanoconjugates (targeted NCs). In vitro cellular experiments show that our developed targeted NCs demonstrate 3-5 times higher cellular uptake than non-targeted NCs at various incubation times (2 h, 8 h, and 12 h) in KB cells where folate receptors are overexpressed. This enhanced cellular uptake of targeted NCs and the following delivery of drugs in the cytosol and its disposition to the nucleus exhibit a substantial amount of toxicity to KB cells towards an effective therapeutic strategy for treatment.

Chiral recognition of amino acids through homochiral metallacycle [ZnCl2L]2.

Chiral recognition holds tremendous significance in both life science and chemistry. The ability to differentiate between enantiomers is crucial because one enantiomer typically holds greater biological relevance while its counterpart is often not only unnecessary but also potentially harmful. In this regard, homochiral metallacycle [ZnCl2L]2 is used in this study to understand and differentiate between the R and S enantiomers of amino acids (alanine, proline, serine, and valine). The electronic, geometric, and thermodynamic stabilities of the amino acid enantiomers inside the metallacycle are determined through various analyses. The greater interaction energy (Eint) is obtained for the ser@metallacycle complexes i.e., -33.03 and -30.75 kcal mol-1, respectively for the S and R enantiomers. The highest chiral discrimination energy of 3.11 kcal mol-1 is achieved for ala@metallacycle complexes. Regarding the electronic properties, the frontier molecular orbital (FMO) analysis indicates that the energy gap decreases after complexation, which is confirmed through density of states (DOS) analysis. Moreover, natural bond orbital (NBO) analysis determines the amount and direction of charge transfer i.e., from metallacycle towards amino acids. The maximum NBO charge transfer is observed for S-pro@metallacycle complex i.e., -0.291 |e|. Electron density difference (EDD) analysis further proves the direction of charge transfer. Noncovalent interaction index (NCI) and quantum theory of atoms in molecules (QTAIM) analyses demonstrate that the noncovalent interactions present between the host and guest are the weak van der Waals forces and hydrogen bonding. The results of NCI and QTAIM analyses for all the complexes are in alignment with those of the interaction energy (Eint) and chiral discrimination energy (Echir) analyses, i.e., significantly greater non-bonding interactions are observed for the complexes with greater Echir, i.e., for ala@metallacycle. Overall, our analyses demonstrate the excellent chiral discrimination ability of metallacycle towards chiral molecules, i.e., for enantiomers of amino acids through host-guest supramolecular chemistry.

In-vitro and In-silico Anti-inflammatory Activity of a Common Bangladeshi Fruit: An Approach to Find Selective COX-2 Inhibitors

Background: From the ancient time, medicinal plants are utilized to mitigate different disease. In Ayurveda and Siddha indigenous medicinal systems, the bark of Syzygium cumini (L.) (Myrtaceae) is used for sore bronchitis, asthma, throat, dysentery, seasickness and ulcers. Objectives: The present experiment was executed to explore the anti-inflammatory property of Syzygium cumini fruit from it’s methanolic extract through phytochemical screening as well as the in-silico approach. Methods: In this experiment, standard method such as human red blood cell (HRBC) membrane stabilizing method was utilized to discover the phytochemical responsible for anti-inflammatory activity present in methanolic crude extract of Syzygium cumini fruits. In-silico ADME/T and molecular docking study was performed to assess the potential of stated phytochemicals against Cyclooxygenase-II enzyme. Findings: The presence of flavonoids, alkaloids, glycosides, tannins and saponins were confirmed by phytochemical screening. In membrane stabilizing method, the extract showed a maximum membrane stabilizing effect on HRBC with 62.381% at 1000 µg/mL in hypotonic solution 37.619% hemolysis were found when compared with standard drug Diclofenac sodium exhibited 87.143% protection. Twenty-three phytochemicals exhibit notable pharmacokinetics properties and passed drug likeness screening test in silico. In molecular docking study, Dihydromyricetin showed docking score (-9.1 kJ/mol) near as high as standard drug Celecoxib (-9.5 kJ/mol) with significant non-bonding interactions with target enzyme. Conclusions: The result of the present study demonstrates a favorable baseline in progression for the possible use of fruit of Syzygium cumini to treat inflammation.

Unusual Endotaxy Growth of Hexagonal Nanosheets by the Self-Assembly of a Homopolymer.

A classical crystallization usually grows epitaxially from a crystal nucleus. Presented in this study is an unusual endotaxy growth manner of a crystalline homopolymer to form hexagonal nanosheets. The amphiphilic homopolymer, poly(3-(4-(phenyldiazenyl)phenoxy)propyl methacrylate) (PAzoPMA), is first annealed in isopropanol to afford a hexagonal nut-like structure. Then, the PAzoPMA crystallizes from the inner wall to the center to form a thin bottom, which grows upwards along the bottom, leading to the formation of the evenly hexagonal nanosheets. The energy fluctuation by Molecular Dynamics (MD) simulation during self-assembly confirms the packing state of PAzoPMA chains in different solvents. In isopropanol, the total energy is the lowest, demonstrating the tight regular arrangement of polymer chains. In addition, the non-bonding interaction energy is the lowest, leading to the favorable contact with solvent molecules and the formation of hexagonal nanosheets. Otherwise, nanowires and giant large compound micelles are formed in ethanol and n-butanol. Overall, an unusual endotaxy crystallization manner of an amphiphilic homopolymer is observed during the preparation of hexagonal nanosheets, which brings fresh insight for understanding crystallization behavior of polymers and preparing functional soft nanomaterials.

Design, Synthesis, and Antibacterial Activities of Multi-Functional C2-Functionalized 1,4-Naphthoquinonyl Organoseleniums.

A practical and efficient reaction for C2-selenylation of 1,4-naphthoquinones has been explored. This coupling reaction of two redox structural motifs, such as 2-bromo-1,4-naphthoquinone with diaryldiselenide/ebselen has been achieved by using sodium borohydride reducing agent at room temperature. Using this approach, several 2-selenylated-1,4-naphthoquinones were obtained in moderate to good yields and thoroughly characterized by multinuclear (1H, 13C, and 77Se) NMR, cyclic voltammetry, and mass spectrometry. Further, light-irradiated thiolation of the synthesized selenazinone was also performed to show the utility of the synthesized compound for post-functionalization. Several 2-selenylated-1,4-naphthoquinones were studied by SC-XRD in which intramolecular Se⋅⋅⋅N (from quinolinyl ligand) non-bonded interactions were observed. Photophysical studies (UV-visible, emission, solvatochromism, and quantum yield) were also performed on selected C2-selenylated naphthoquinones. The naphthoquinonyl organoseleniums were also screened for their antibacterial properties and quinonyl organoselenium 5 d shows good antibacterial potential against S. aureus ATCC 29213 with MIC 0.5 μg/mL and a Selectivity Index of >200. Moreover, it also exhibited equipotent activity against various strains of S. aureus and Enterococcus faecium, including strains resistant to vancomycin and meropenem. From structure-activity correlation, it seems that nice blend of oxidant properties from quinone and antioxidant properties from selenium moiety makes it better candidate for antibacterial activity.

Molecular docking and ADMET profiling of Carbazole-rhodanine hybrid as anticancer agent

Drug resistance and lack of specificity of currently available chemotherapeutics for cancer cells contribute to the failure of cancer chemotherapy. This highlights the pressing need to develop novel anticancer agents. This research aims to investigate the inhibiting potential of Carbazole and rhodanine derivatives against Human papillomaviruses (HPVs) and Breakpoint Cluster Region (BCR), with Abelson murine leukemia (ABL) tyrosine kinase to manage human cervical cancer and human chronic myeloid leukemia (CML), respectively. Some carbazole-rhodanine hybrids were evaluated in silico against human cervical cancer (Hela) and human CML (K562) cells. In this study, Molecular docking was used to determine binding affinity, bonding, and nonbonding interaction between the studied compounds and the target. Additionally, in-silico ADMET (adsorption, distribution, metabolism, excretion, and toxicity) screening was performed to explore the bioavailability, pharmacokinetic properties, and toxicity of the carbazole-rhodanine hybrids. The structure of the compounds was also discussed relative to their bioactivity. The molecular docking revealed that the test compounds except D, E, and L demonstrated better binding affinity, hence better inhibition efficiency towards Hela and K562 cell lines than the reference drug (etoposide). Compound G with a cyano substituent showed the highest binding affinity with the two receptors used, with a binding energy of -7.9 kcal mol-1 against hela (6HKS) and -10.0 against K562 (5HU9). This was in accordance with the experimental result. The SAR illustrated that a strong electron-withdrawing substituent attached to the para-position of the phenyl ring increased the activity. The ADMET profiling showed that compounds E, G, and J had superior drug-likeness, pharmacokinetic, and toxicity properties. Based on the results, compound G may be a good candidate to be developed further into a therapeutic agent to treat chronic myeloid leukemia and cervical cancer.

Encoding Anticancer Potential of Zingerone: Bioinformatic and Molecular Docking Analysis Targeting Liver Cancer

Liver cancer is the third-leading cause of cancer death globally, requiring research on molecular mechanisms for sustainable prevention and treatment. With expensive conventional drugs and severe side effects, novel medications are needed. Therefore, in the current investigation employing a bioinformatic approach, we explored the bioactive phytocompound zingerone for its anticancer efficacy targeting liver cancer. The study analyzed phytocompounds’ drug-like nature using SWISS ADME, finding them orally available and meeting Lipinski, Ghose, Veber, Egan, and Muegge rules. They showed good ADMET properties and strong interactions with apoptotic regulator target proteins, making them safe for commercial anticancer drugs. hGLUT, DDEFL1, HBx, BCl2 , AFP, NF kappa, and Heat Shock Protein 70 Shows good binding affinity in the range of -5.3 to -6.0 kcal/mol. The phytocompound zingerone shows good binding affinity with all target proteins (-5.8 to -6.0 kcal/mol), thereby possessing appreciable bonded and non-bonded interactions with the binding pockets of target proteins. This study’s findings could lead to the development of promising drug candidates for liver cancer, laying the foundation for the development of novel anticancer therapeutics.

Key Role of Cross-Linking Homogeneity in Polyurethane Mechanical Properties: Insights from Molecular Dynamics.

Polyurethane (PU) grouting materials play a crucial role in trenchless rehabilitation with their mechanical properties significantly influenced by the cross-linking degree and cross-linking uniformity. This study investigates the effects of inhomogeneous cross-linking on the mechanical behavior of PU, an area that remains underexplored. We developed PU molecular models with varying cross-linking degrees and cross-linking uniformity, quantitatively described by the parameter J. A series-parallel spring network model was proposed to analyze their micromechanical responses under tensile stress. Our results indicate that cross-linking homogeneity, compared to the cross-linking degree, has a more significant impact on the mechanical properties of PU due to weaker parallel effects in specific series directions within the elastic network. Additionally, this defective network leads to larger free volume, stronger nonbonded interactions, smaller elastic variation, and weaker bonding contributions. Interestingly, this influence has an upper limit; under normal circumstances, J increases as the cross-linking degree increases. When J reaches a certain value, its effect diminishes, as indicated by the disappearance of network slippage during tensile testing. Therefore, PU with more uniform cross-linking exhibits a higher yield strength. These findings provide new insights into how cross-linking networks affect the mechanical properties of PU.