HypothesisSynthetic sugar alcohol mono-behenates with high melting points, surface activity and resistance to enzymatic lipolysis, are expected to form stable single-component solid lipid nanocarriers (SC-SLNs). The preparation methods and the polar head group of the molecules should affect the size and drug encapsulation efficiency.ExperimentsSC-SLNs of sugar alcohol mono-behenates with varied polar heads were prepared using emulsification-diffusion method and melting-probe sonication method. Model lipophilic drug fenofibrate was formulated into nanocarriers. The drug release was assessed using the lipolysis model. The structure and drug distribution of the nanocarriers were studied using AFM and TEM.FindingsBoth the polar head group of the molecules and the preparation methods affect the particle size and size distribution. Nanocarriers prepared with sorbitol mono-behenates showed the smallest mean size (∼100 nm with PdI of 0.26). In addition, they displayed high entrapment efficiency of fenofibrate (95%) and long term drug release. Nanocarriers prepared by emulsification-diffusion method entrapped fenofibrate into lipid bilayers. In contrast, Nanocarriers prepared by melting-probe sonication method had a micelle structure with fenofibrate incorporated into a lipid monolayer. This study provides an insight into the systematic development of novel amphiphilic lipids for solid lipid-based drug delivery system.A group of synthetic behenic acyl based amphiphilic lipids was studied as novel excipients for formation of solid lipid nanocarriers, affording around 100 nm, high encapsulation efficiency of lipophilic drug and long-term drug release.Download high-res image (108KB)Download full-size image

Six synthetic phosphopeptides (SPP) and casein phosphopeptides (CPP) were obtained to investigate the relationship between the molecular structure of phosphopeptides and their calcium-binding property. SPP1, SPP2, SPP3, SPP4, SPP5, and SPP6 were synthesized with 0-3 continuous or discontinuous phosphorylated serines based on a core structure of casein phosphopeptides, respectively. CPP were acquired by pancreatin hydrolysis of casein and subsequent purification. The ranking of calcium-binding ability of the six synthetic phosphopeptides was SPP5 > SPP6 > SPP4 > SPP3 > SPP1 ~ SPP2. SPP4 was found to release calcium more easily in a simulated intestinal environment. CPP, contained various fragments ranged from 1 to 4 Ser(P)s, bound calcium slightly weaker than SPP6 that contained same amount of phosphorus with the CPP solution. The number and the position of phosphoserine residue are important factors for calcium-binding activities. SPP4, the phosphopeptide with two discontinuous phosphorylated serines, has the best calcium adsorption efficiency in a simulated intestinal environment among all the tested phosphopeptides.

Fatty acids and derivatives (FADs) are resources for natural antimicrobials. In order to screen for additional potent antimicrobial agents, the antimicrobial activities of FADs against Staphylococcus aureus were examined using a microplate assay. Monoglycerides of fatty acids were the most potent class of fatty acids, among which monotridecanoin possessed the most potent antimicrobial activity. The conventional quantitative structure-activity relationship (QSAR) and comparative molecular field analysis (CoMFA) were performed to establish two statistically reliable models (conventional QSAR: R2=0.942, Q2LOO=0.910; CoMFA: R2=0.979, Q2=0.588, respectively). Improved forecasting can be achieved by the combination of these two models that provide a good insight into the structure-activity relationships of the FADs and that may be useful to design new FADs as antimicrobial agents.

A validated 3D pharmacophore model was generated for a series of ACE inhibitory peptides, which consisted of five features (two hydrophobic functions, two hydrogen bond acceptors, and a negative ionizable function). The built model was able to correctly predict the activity of known ACE inhibitors. The model was then used as query to search 3D databases of peptides. Three novel peptides (I, II and III) were synthesized and biologically evaluated in vitro. It appears that the in vitro activity of peptides I, II and III was consistent with their molecular modeling results. Our results provided confidence for the utility of the pharmacophore model to retrieve novel ACE inhibitory peptides with desired biological activity by virtual screening.3D pharmacophore model for ACE inhibitory peptides was generated.Highlights► A validated 3D pharmacophore model was generated for ACE inhibitory peptides. ► The pharmacophore model was able to correctly predict the activity of known ACE inhibitors. ► The pharmacophore model can be used to retrieve novel ACE inhibitory peptides with desired biological activity.

This paper proposes an analytical method for simultaneous near-infrared (NIR) spectrometric determination of α-linolenic and linoleic acid in eight types of edible vegetable oils and their blending. For this purpose, a combination of spectral wavelength selection by wavelet transform (WT) and elimination of uninformative variables (UVE) was proposed to obtain simple partial least square (PLS) models based on a small subset of wavelengths. WT was firstly utilized to compress full NIR spectra which contain 1413 redundant variables, and 42 wavelet approximate coefficients were obtained. UVE was then carried out to further select the informative variables. Finally, 27 and 19 wavelet approximate coefficients were selected by UVE for α-linolenic and linoleic acid, respectively. The selected variables were used as inputs of PLS model. Due to original spectra were compressed, and irrelevant variables were eliminated, more parsimonious and efficient model based on WT-UVE was obtained compared with the conventional PLS model with full spectra data. The coefficient of determination (r2) and root mean square error prediction set (RMSEP) for prediction set were 0.9345 and 0.0123 for α-linolenic acid prediction by WT-UVE-PLS model. The r2 and RMSEP were 0.9054, 0.0437 for linoleic acid prediction. The good performance showed a potential application using WT-UVE to select NIR effective variables. WT-UVE can both speed up the calculation and improve the predicted results. The results indicated that it was feasible to fast determine α-linolenic acid and linoleic acid content in edible oils using NIR spectroscopy.