Abstract: Naproxen-Gelucire Nanoformulations (NFs) in terms of their phase solubility behavior, physico-chemical characteristics, cytotoxicity and morphology and dissolution enhancement has been studied using the poorly water soluble drug, naproxen. The NFs were prepared via wet milling using a conventional Retsch Planetary ball mill in various ratios of drug to polymer (1:1, 1:2, 1:3, 1:4). The release rate of naproxen from various ratios of drug/polymer nanoparticles was investigated using USP paddle apparatus (type II). A comparative phase solubility of naproxen was performed in different carrier concentrations of simulated gastric fluid (pH 1.2) and simulated intestinal fluid (pH 6.8). The highest dissolution enhancement was achieved for the formulation with ratio of 1:4. This is a 160% enhancement when compared to that of the pure drug. The ability of amphiphillic surfactant carriers to accelerate in vitro dissolution of poorly water-soluble drugs has been attributed to wetting, micellar solubilization, and/or deflocculation. The Korsemeyer–Peppas model most aptly fits the in vitro dissolution data and gives an insight into the possible drug release mechanisms predominated by anamolous non-Fickian diffusion. Thus, the nanoformulations studied can help improve the physicochemical characteristics of naproxen towards its dissolution enhancement and possibly will increase the oral bioavailability of the drug without any adverse cytotoxic consequences.Abstract: Naproxen-Gelucire Nanoformulations (NFs) in terms of their phase solubility behavior, physico-chemical characteristics, cytotoxicity and morphology and dissolution enhancement has been studied using the poorly water soluble drug, naproxen. The NFs were prepared via wet milling using a conventional Retsch Planetary ball mill in various ratios of dru...Show More
Abstract: We virtually design here new subnanomolar range antimalarials, inhibitors of plasmodium falciparum M17 Aminopeptidase (pfA-M17), by means of structure-based molecular design. Complexation QSAR models were elaborated for two training sets (6 methylphosphonic acids (APP) resp. 13 Hydroxamic Acid derivatives (AHO): QSARAPP. resp. QSARAHO) and a linear correlation was established between the computed Gibbs free energies of binding (GFE: DDGcom) and observed enzyme inhibition constants (Kiexp) for each training set: QSARAPP: pKiexp=−0.1665´DDGcom+7.9581, R2=0.97 resp. QSARAHO: pKiexp=−0.4626´DDGcom+8.1842, R2=0.98. The predictive power of the QSAR models was validated with 3D-QSAR pharmacophore generation (PH4): PH4APP: pKiexp=0.99677´pKipred– 0.00457, R2=0.99 resp. PH4AHO: pKiexp =1.02016´pKipred–0.10478, R2=0.99. Breakdown of computed pfA-M17:APPs resp. pfA-M17:AHOs interaction energy into each active site residue’s contribution provided additional helpful structural information to design new APP and AHO analogues in a consistent way. In a first step we designed a virtual library (VLAPP resp. VLAHO) from P1 and P’ 1 substitutions to explore both S1 and S’ 1 pockets. Further the VLs screened with the 3D-QSAR PH4s and the Kipred of the best fit hits virtually evaluated with QSARAPP resp. QSARAHO models. This approach combining use of molecular modeling, PH4 and in silico VL screening helpfully provided valuable structural information for the synthesis of novel pfA-M17 inhibitors.Abstract: We virtually design here new subnanomolar range antimalarials, inhibitors of plasmodium falciparum M17 Aminopeptidase (pfA-M17), by means of structure-based molecular design. Complexation QSAR models were elaborated for two training sets (6 methylphosphonic acids (APP) resp. 13 Hydroxamic Acid derivatives (AHO): QSARAPP. resp. QSARAHO) and a linear...Show More
