The Binding of Alpinia galanga Oil and Its Nanoemulsion to Mammal GABAA Receptors Using Rat Cortical Membranes and an In Silico Modeling Platform.

The anesthetic effect of Alpinia galanga oil (AGO) has been reported. However, knowledge of its pathway in mammals is limited. In the present study, the binding of AGO and its key compounds, methyl eugenol, 1,8-cineole, and 4-allylphenyl acetate, to gamma-aminobutyric acid type A (GABAA) receptors in rat cortical membranes, was investigated using a [3H]muscimol binding assay and an in silico modeling platform. The results showed that only AGO and methyl eugenol displayed a positive modulation at the highest concentrations, whereas 1,8-cineole and 4-allylphenyl acetate were inactive. The result of AGO correlated well to the amount of methyl eugenol in AGO. Computational docking and dynamics simulations into the GABAA receptor complex model (PDB: 6X3T) showed the stable structure of the GABAA receptor-methyl eugenol complex with the lowest binding energy of -22.16 kcal/mol. This result shows that the anesthetic activity of AGO and methyl eugenol in mammals is associated with GABAA receptor modulation. An oil-in-water nanoemulsion containing 20% w/w AGO (NE-AGO) was formulated. NE-AGO showed a significant increase in specific [3H]muscimol binding, to 179% of the control, with an EC50 of 391 µg/mL. Intracellular studies show that normal human cells are highly tolerant to AGO and the nanoemulsion, indicating that NE-AGO may be useful for human anesthesia.

Potential Anti-Alzheimer Agents from Guanidinyl Tryptophan Derivatives with Activities of Membrane Adhesion and Conformational Transition Inhibitions.

Guanidinyl tryptophan derivatives TGN1, TGN2, TGN3, and TGN4 were synthesized, and these compounds were shown to possess in vitro inhibitory activity for amyloid aggregation in a previous study. Nevertheless, the influence of the TGN series of compounds on the binding and permeation behaviors of an Aß monomer to the cell membranes was not elucidated. In this study, we investigated the effect of compounds in the TGN series on the behavior of an Aß monomer regarding its toxicity toward the bilayer lipid membrane using molecular dynamics (MD) simulation. MD simulations suggest that TGN4 is a potential agent that can interfere with the movement of the Aß monomer into the membrane. The MM-GBSA result demonstrated that TGN4 exhibits the highest affinity to the Aß1-42 monomer but has the lowest affinity to the bilayer. Moreover, TGN4 also contributes to a decrease in the binding affinity between the Aß1-42 monomer and the POPC membrane. Regarding the results of the binding mode and conformational analyses, a high number of amino-acid residues were shown to provide the binding interactions between TGN4 and the Aß1-42 monomer. TGN4 also reduces the conformational transition of the Aß1-42 monomer by means of interacting with the monomer. The present study presents molecular-level insights into how the TGN series of compounds affect the membrane adsorption and the conformational transition of the Aß1-42 monomer, which could be valuable for the further development of new anti-Alzheimer agents.

Molecular modeling for potential cathepsin L inhibitor identification as new anti-photoaging agents from tropical medicinal plants.

Ultraviolet exposure can cause photoaging toward the human skin which is begun by the inflammation on the exposure area, also resulting in activation of a degradative enzyme cathepsin L. This enzyme is one of the interesting novel therapeutic targets for antiaging agents. Three plants, named Kleinhovia hospita, Aleurites moluccana, and Centella asiatica, are well-known in the tropical region as anti-inflammatory herbs. The aims of this study were to predict the antiaging activity of the 31 compounds from these plants via inhibition of cathepsin L. All compounds were minimized their energies and then used in molecular docking. After that, molecular dynamics (MD) simulation was employed for the 5 candidate ligands and the positive control; schinol. Interaction analysis results of the pre-MD and post-MD simulation structures were obtained. Furthermore, a toxicity test was performed using ADMET Predictor 7.1. Based on the molecular docking and the MD simulation results, kleinhospitine A, ß-amyrin, and castiliferol exhibited lower binding free energy than schinol (-27.0925, -28.6813, -26.0037 kcal/mol) and also had interactions with the S´ region binding site. The toxicity test indicated that ß-amyrin is the most potential candidate since it exhibited the lowest binding energy and the high safety level.

Tentative Peptide‒Lipid Bilayer Models Elucidating Molecular Behaviors and Interactions Driving Passive Cellular Uptake of Collagen-Derived Small Peptides.

Collagen contains hydroxyproline (Hyp), which is a unique amino acid. Three collagen-derived small peptides (Gly-Pro-Hyp, Pro-Hyp, and Gly-Hyp) interacting across a lipid bilayer (POPC model membrane) for cellular uptakes of these collagen-derived small peptides were studied using accelerated molecular dynamics simulation. The ligands were investigated for their binding modes, hydrogen bonds in each coordinate frame, and mean square displacement (MSD) in the Z direction. The lipid bilayers were evaluated for mass and electron density profiles of the lipid molecules, surface area of the head groups, and root mean square deviation (RMSD). The simulation results show that hydrogen bonding between the small collagen peptides and plasma membrane plays a significant role in their internalization. The translocation of the small collagen peptides across the cell membranes was shown. Pro-Hyp laterally condensed the membrane, resulting in an increase in the bilayer thickness and rigidity. Perception regarding molecular behaviors of collagen-derived peptides within the cell membrane, including their interactions, provides the novel design of specific bioactive collagen peptides for their applications.

Molecular modeling investigation of the potential mechanism for phytochemical-induced skin collagen biosynthesis by inhibition of the protein phosphatase 1 holoenzyme.

The most prominent feature of UV-induced photoaged skin is decreased type 1 procollagen. Increase of the TGF-ß/Smad signaling through inhibition of the TßRI dephosphorylation by the GADD34-PP1c phosphatase complex represents a promising strategy for the increase in type 1 collagen production and prevention of UV-induced skin photoaging. In this study, the molecular docking and dynamics simulations, and pharmacophore modeling method were run to investigate a possible binding site as well as binding modes between apigenin, daidzein, asiaticoside, obovatol, and astragaloside IV and PP1c. Through docking study, the possible binding site for these phytochemicals was predicted as the hydrophobic (PP1-substrate binding) groove. The result indicates that PP1 is the significant target of these compounds. Moreover, the 20,000-ps MD simulations present that the binding locations and modes predicted by the docking have been slightly changed considering that the MD simulations proffer more reliable details upon the protein-ligand recognition. The MM-GBSA binding free energy calculations and pharmacophore modeling rationally identify that the highly hydrophobic surfaces/pockets at close proximity of the catalytic core are the most favorable binding locations of the herbal compounds, and that some experimental facts upon a possible mechanism of increase in collagen biosynthesis can be explained. The present study theoretically offers the reliable binding target of the herbal compounds, and therefore helps to understanding the action mechanism for natural small molecules that enhance collagen production.

An integrated molecular modeling approach for the tryptase monomer-curcuminoid recognition analysis: conformational and bioenergetic features.

Human mast cell tryptase has been shown as an activating enzyme in matrix degradation process. The previous study suggest that tryptase either alone or in joining with activation of metalloproteinases, can associate in extra cellular matrix damage and the possible destruction of the basement membrane resulting in photoaging. Therefore the inhibition of tryptase activity is one of the most important therapeutic strategies against the photoaging. Curcumin has been shown to be a potential agent for preventing and/or treating the photoaging induced by UV radiation. However, the protective effect of curcumin against the photoaging through the tryptase inhibition is still inadequately understood. In this work, computational methods to characterize the structural framework and define the atomistic details of the determinants for the tryptase inhibition mechanism by curcuminoids were performed. By molecular docking, three putative binding models able to efficiently bind all curcuminoids were identified. Analysis of molecular dynamics simulations revealed that cyclocurcumin, curcumin glucuronide, and curcumin, the most effective inhibitors from the three models, modified significant tryptase monomer rigidity by binding in all the possible sites. The result of these binding events is the suppression of the functional enzymatic motions involving the binding of substrates to the catalytic site. On the basis of this finding may thus be beneficial for the development of new natural inhibitors for the therapeutic remedy of photoaging, targeting and modulating the activity of tryptase.

Molecular modeling of non-covalent binding of Ligustrum lucidum secoiridoid glucosides to AP-1/matrix metalloproteinase pathway components.

Ligustrum lucidum secoiridoid glucosides have been demonstrated to treat various types of diseases such as inflammation, pain, hepatotoxicity and hyperlipidermic as well as tonic for liver and kidney. Matrix metalloproteinases (MMPs) play a key role upon the pathology of photoaging. The present computational study showed that among the six secoiridoid glucosides (ligustroside, lucidumoside A, lucidumoside C, neonuezhenide, oleoside dimethylester, and oleuropein), ligustroside and lucidumoside A competitively inhibit all MMP-1, MMP-3, and MMP-9 activities in the docking models. The molecular docking analysis revealed a network of interactions between MMP-1, MMP-3, and MMP-9 and the ligands; ligustroside and lucidumoside A, and oxygen-containing and hydrophobic functional groups appear to be responsible for these enhanced interactions. The effect of ligustroside and lucidumoside A on the transcription factor AP-1 action was also investigated using molecular docking and dynamics simulations. The experiments suggested that inhibition of an AP-1-DNA complex formation could be on account of the direct interference of AP-1 binding onto the DNA binding sequence by ligustroside and lucidumoside A. The results suggest that both compounds have the highest potential for application as an anti-aging agent with the MMP inhibitory and anti-transcriptional activities.

A significant mechanism of molecular recognition between bioflavonoids and P-glycoprotein leading to herb-drug interactions.

Inhibition of P-glycoprotein (P-gp)'s function may conduct significant changes in the prescription drugs' pharmacokinetic profiles and escalate potential risks in taking place of drug/herb-drug interactions. Computational modeling was advanced to scrutinize some bioflavonoids which play roles in herb-drug interactions as P-gp inhibitors utilizing molecular docking and pharmacophore analyses. Twenty-five flavonoids were utilized as ligands for the modeling. The mouse P-gp (code: 4Q9H) was acquired from the PDB. The docking was operated utilizing AutoDock version 4.2.6 (Scripps Research Institute, La Jolla, CA) against the NBD2 of 4Q9H. The result illustrated the high correlation between the docking scores and observed activities of the flavonoids and the putative binding site of these flavonoids was proposed and compared with the site for ATP. To evaluate hotspot amino acid residues within the NBD2, Binding modes for the ligands were achieved using LigandScout to originate the NBD2-flavonoid pharmacophore models. The results asserted that these inhibitors competed with ATP for binding site in the NBD2 (as competitive inhibitors) including the hotspot residues which associated with electrostatic and van der Waals interactions with the flavonoids. In MD simulation of eight delegated complexes selected from the analyzed flavonoid subclasses, RMSD analysis of the trajectories indicated the residues were stable throughout the duration of simulations.

Molecular modeling elucidates the cellular mechanism of synaptotagmin-SNARE inhibition: a novel plausible route to anti-wrinkle activity of botox-like cosmetic active molecules.

Synaptotagmin 1 (Syt1) is the Ca2+ sensor protein with an essential role in neurotransmitter release. Since the wrinkle formation is due to the excessive muscle fiber stimulation in the face, a helpful stratagem to diminish the wrinkle line intenseness is to weaken the innervating neuron activity through Syt1 inhibition which is one of the possible therapeutic strategies against wrinkles. Recently, experimental evidence showed that botox-like peptides, which are typically used as SNARE modulators, may inhibit Syt1. In this work, we applied molecular modeling to (1) characterize the structural framework and (2) define the atomistic information of the factors for the inhibition mechanism. The modeling identified the plausible binding cleft able to efficiently bind all botox-like peptides. The MD simulations revealed that all peptides induced significant Syt1 rigidity by binding in the cleft of the C2A-C2B interface. The consequence of this binding event is the suppression of the protein motion associated with conformational change of Syt1 from the closed form to the open form. On this basis, this finding may therefore be of subservience for the advancement of novel botox-like molecules for the therapeutic treatment of wrinkle, targeting and modulating the function of Syt1.

Insight into the molecular mechanism of P-glycoprotein mediated drug toxicity induced by bioflavonoids: an integrated computational approach.

In this work, molecular docking, pharmacophore modeling and molecular dynamics (MD) simulation were rendered for the mouse P-glycoprotein (P-gp) (code: 4Q9H) and bioflavonoids; amorphigenin, chrysin, epigallocatechin, formononetin and rotenone including a positive control; verapamil to identify protein-ligand interaction features including binding affinities, interaction characteristics, hot-spot amino acid residues and complex stabilities. These flavonoids occupied the same binding site with high binding affinities and shared the same key residues for their binding interactions and the binding region of the flavonoids was revealed that overlapped the ATP binding region with hydrophobic and hydrophilic interactions suggesting a competitive inhibition mechanism of the compounds. Root mean square deviations (RMSDs) analysis of MD trajectories of the protein-ligand complexes and NBD2 residues, and ligands pointed out these residues were stable throughout the duration of MD simulations. Thus, the applied preliminary structure-based molecular modeling approach of interactions between NBD2 and flavonoids may be gainful to realize the intimate inhibition mechanism of P-gp at NBD2 level and on the basis of the obtained data, it can be concluded that these bioflavonoids have the potential to cause herb-drug interactions or be used as lead molecules for the inhibition of P-gp (as anti-multidrug resistance agents) via the NBD2 blocking mechanism in future.

3D-QSAR modelling dataset of bioflavonoids for predicting the potential modulatory effect on P-glycoprotein activity.

The data is obtained from exploring the modulatory activities of bioflavonoids on P-glycoprotein function by ligand-based approaches. Multivariate Linear-QSAR models for predicting the induced/inhibitory activities of the flavonoids were created. Molecular descriptors were initially used as independent variables and a dependent variable was expressed as pFAR. The variables were then used in MLR analysis by stepwise regression calculation to build the linear QSAR data. The entire dataset consisted of 23 bioflavonoids was used as a training set. Regarding the obtained MLR QSAR model, R of 0.963, R (2)=0.927, [Formula: see text], SEE=0.197, F=33.849 and q (2)=0.927 were achieved. The true predictabilities of QSAR model were justified by evaluation with the external dataset (Table 4). The pFARs of representative flavonoids were predicted by MLR QSAR modelling. The data showed that internal and external validations may generate the same conclusion.