Taxifolin prevents postprandial hyperglycemia by regulating the activity of α-amylase: Evidence from an in vivo and in silico studies

There has been a dramatic increase in the prevalence of diabetes mellitus (DM) and its associated complications globally. The postprandial stage of DM involves prompt elevation in the levels of blood glucose and α-amylase, a carbohydrate-metabolizing enzyme is mainly involved in the regulation of postprandial hyperglycemia. This study was designed to assess the ability of a well-known flavonoid, taxifolin (TFN), against postprandial hyperglycemia and its inhibitory effects on α-amylase activity through the assessment of therapeutic potentials of TFN in an alloxan-induced diabetic animal model. The binding potential TFN with an α-amylase receptor was also investigated through molecular dynamics (MD) simulation and docking of to compare the binding affinities and energies of TFN and standard drug acarbose (ACB) with target enzyme. TFN significantly improved the postprandial hyperglycemia, lipid profile, and serum levels of α-amylase, lipase, and C-reactive protein in a dose-dependent manner when compared with that of either DM-induced and ACB-treated alloxan-induced diabetic rats. Moreover, TFN also enhanced the anti-oxidant status and normal functioning of the liver in alloxan-induced diabetic rats more efficiently as compared to that of ACB-treated alloxan-induced diabetic rats. Therapeutic potentials of TFN were also verified by MD simulation and docking results, which exhibited that the binding energy and affinity of TFN to bind with receptor was significantly higher as compared to that of ACB. Hence, the results of this study signify that TFN might be a potent inhibitor of α-amylase that has the potential to regulate the postprandial hyperglycemia along with its anti-inflammatory and anti-oxidant properties during the treatment of DM.     

Insight into the key active sites of afChiA1 based on molecular dynamics simulations and free energy calculations

In this study, the binding of the enzyme chitinase A1 (afChiA1) from the plant-type Aspergillus fumigatus with four potent inhibitors, allosamidin (ASM), acetazolamide (AZM), 8-chloro-theophylline (CTP) and kinetin (KIT) is investigated by molecular docking, molecular dynamics simulation and binding free energy calculation. The results reveal that the electrostatic interactions play an important role in the stabilisation of the binding of afChiA1 with inhibitors. Based on the binding energy of afChiA1-ligands, the key residues (Gln37 and Trp312) in the active binding pocket of the complex systems are confirmed by molecular mechanics/Poisson–Boltzmann surface area method, and the active inhibitors, ASM and AZM, both could form strong interaction with Gln37 and Trp312, and the non-active ligands, CTP and KIT, could not interact with these two residues, which is consistent with the result of experimental report. Then, it is identified that Gln37 and Trp312 should be one of the important active site residues of afChiA1.     

Molecular dynamics simulation of isothermal crystallisation of polymer chains around single polymer lamella

The isothermal crystallisation of polyethylene (PE) chains around single PE lamella in vacuum is investigated by molecular dynamic simulation. The crystallisation process is analysed in terms of the orientational order parameters, principal moments of inertia for the simulated systems. The effects of charge interactions between the polymer chains and lamella are discussed. It is found that the crystallisation process for uncharged systems can be divided into three stages: (1) adsorption, (2) orientation and (3) arrangement. The single polymer lamella changes a little during the three stages. PE chains are arranged parallel to the chain direction of the stems in the crystalline state. When considering the effect of charge interactions between the polymer chains and lamella, a different crystallisation process appears. The single polymer lamella is affected by the charged polymer chains.     

Molecular level activation insights from a NR2A/NR2B agonist

N-methyl D-aspartate receptors (NMDARs), a subclass of glutamate receptors have broad actions in neural transmission for major brain functions. Overactivation of NMDARs leading to “excitotoxicity” is the underlying mechanism of neuronal death in a number of neurological diseases, especially stroke. Much research effort has been directed toward developing pharmacological agents to modulate NMDAR actions for treating neurological diseases, in particular stroke. Here, we report that Alliin, a sulfoxide in fresh garlic, exhibits affinity toward NR2A as well as NR2B receptors based on virtual screening. Biological activities of Alliin on these two receptors were confirmed in electrophysiological studies. Ligand-binding site closure, a structural change precluding ion channel opening, was observed with Alliin during 100?ns molecular dynamics simulation. Alliin interactions with NR2A and NR2B suggest that residues E/A413, H485, T690, and Y730 may play important roles in the conformation shift. Activation of NR2A and NR2B by Alliin can be differentiated from that caused by glutamate, the endogenous neurotransmitter. These characteristic molecular features in NR2A and NR2B activation provide insight into structural requirements for future development of novel drugs with selective interaction with NR2A and NR2B for treating neurological diseases, particularly stroke.     

Discovery of novel insomnia leads from screening traditional Chinese medicine database

Insomnia is a prominent modern disease that affects an increasing population. Undesirable side effects of commercial drugs highlight the need to develop novel insomnia drugs. Virtual screening of traditional chinese medicine Database@Taiwan (TCM Database@Taiwan) identified 2-O-Caffeoyl tartaric acid (1), 2-O-Feruloyl tartaric acid (2), and Mumefural (3) as potential agonists for both gamma-amino butyric acid (GABA) or benzodiazepine (BZ) binding sites. The TCM candidates exhibited higher affinity than GABA and Zolpidem, a phenomenon that could be attributed to higher quantity of stabilizing H-bonds. Efficacy profiles using support vector machines and pharmacophore contour also suggest drug potential of the TCM candidates. Fragments added to the de novo derivatives 3a, 3b, 3c for GABA binding site, and 1a, 2a, and 3d for BZ binding site contributed to new binding sites and structural stability, further optimizing binding to GABA or BZ binding sites. Increased opening of the ion channel by candidate ligands provide strong support for their potential biological functions. The dual binding properties of the TCM candidates present a unique opportunity to develop twin-targeting drugs with less side effects. Derivative structures can be used as starting points for developing high affinity GABA_A receptor agonists with specificity towards GABA binding site and BZ binding site.     

Mechanism of the Atomic Intermixing Process in Crystalline Microclusters

Abstract

The Mechanism of atomic intermixing process in crystalline microclusters is studied by molecular dynamics simulation for a two-dimensional system with the Lennard-Jones potential. Temperature is chosen so that a cluster consists of solid-like core region and the region of surface melting. It is found that atomic intermixing in the solid-like core region is caused by the motion of a dislocation through the cluster as well as the random walk of a vacancy in the cluster. Generation of a dislocation or a vacancy occurs at the interfacial region between the liquid-like surface and the solid-like core regions due to large scale fluctuation of the configuration of atoms in the region of surface melting and the opportune collective motion of atoms in the solid-like core region. The rate per atom of atomic intermixing, the basic quantity of our interest (for the definition see the text), in the solid-like core of the microcluster is three to four orders of magnitude larger than that in the bulk crystal.     

Molecular modelling of the mass density of single proteins

Using molecular dynamics (MD) simulations, the density of single proteins and its temperature dependence was modelled starting from the experimentally determined protein structure and a generic, transferable force field, without the need of prior parameterization. Although all proteins consist of the same 20 amino acids, their density in aqueous solution varies up to 10% and the thermal expansion coefficient up to twofold. To model the protein density, systematic MD simulations were carried out for 10 proteins with a broad range of densities (1.32–1.43?g/cm³) and molecular weights (7–97?kDa). The simulated densities deviated by less than 1.4% from their experimental values that were available for four proteins. Further analyses of protein density showed that it can be essentially described as a consequence of amino acid composition. For five proteins, the density was simulated at different temperatures. The simulated thermal expansion coefficients ranged between 4.3 and 7.1?×?10^?4?K^?1 and were similar to the experimentally determined values of ribonuclease-A and lysozyme (deviations of 2.4 and 14.6%, respectively). Further analyses indicated that the thermal expansion coefficient is linked to the temperature dependence of atomic fluctuations: proteins with a high thermal expansion coefficient show a low increase in flexibility at increasing temperature. A low increase in atomic fluctuations with temperature has been previously described as a possible mechanism of thermostability. Thus, a high thermal expansion coefficient might contribute to protein thermostability.     

Effective prediction model and determination of binding residues influential for inhibitors targeting HIV-1 integrase-LEDGF/p75 interface by employing solvent accessible surface area energy as key determinant

Abstract

Development of a highly accurate prediction model for protein–ligand inhibition has been a major challenge in drug discovery. Herein, we describe a novel predictive model for the inhibition of HIV-1 integrase (IN)-LEDGF/p75 protein-protein interaction. The model was constructed using energy parameters approximated from molecular dynamics (MD) simulations and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. Chemometric analysis using partial least squares (PLS) regression revealed that solvent accessible surface area energy (ΔG_SASA) is the major determinant parameter contributing greatly to the prediction accuracy. PLS prediction model on the ΔG_SASA values collected from 41 complexes yielded a strong correlation between the predicted and the actual inhibitory activities (R² = 0.9666, RMSEC of pIC₅₀ values = 0.0890). Additionally, for the test set of 14 complexes, the model performed satisfactorily with very low pIC₅₀ errors (Q² = 0.5168, RMSEP = 0.3325). A strong correlation between the buried surface areas on the IN protein, when bound with IN-LEDGF/p75 inhibitors, and the respective ΔG_SASA values was also obtained. Furthermore, the current method could identify ‘hot spots’of amino acid residues highly influential to the inhibitory activity prediction. This could present fruitful implications in binding site determination and future inhibitor developments targeting protein-protein interactions.

Communicated by Ramaswamy H. Sarma