Surface structural and solar absorptance features of nitrate-based copper-cobalt oxides composite coatings: Experimental studies and molecular dynamic simulation

The copper and cobalt oxides composites coatings on aluminum substrates have been successfully synthesized via sol-gel method using nitrate-based sol precursors. The composites were characterized by X-ray Diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Field Emission Scanning Electron Microscopy (FESEM), Atomic Force Microscopy (AFM), and UV–Vis–NIR spectrophotometry. The sol-gel reactions were discussed and Molecular Dynamics (MD) simulation was integrated into the study to predict molecules assembly properties. The XRD analyses revealed that the CuO and the Co₃O₄ composites were formed after the annealing process with the average difference of the calculated lattice parameters compared to ICDDs was 1.17%. The surface electronic structure was mainly consisted of tetrahedral Cu(I), octahedral Cu(II), tetrahedral Co(II), octahedral Co(III) as well as surface, sub-surface and lattice oxygen O^?. The XRD, XPS and MD simulation results showed that there was minimal (or possibly non-existing) indication of copper-cobalt mixed phase oxides formations. FESEM and AFM surveys revealed that the coating had a porous surface composed of interlinked nanoparticles in the range of ~?10 to ~?40?nm. UV–Vis–NIR reflectance spectra showed that the sol precursors concentration and the dip-drying cycle significantly influenced the absorptance value with optimum absorptance (α) of 88.7% exhibited by coating synthesized using sol concentration of 0.1?M and 10 dip-drying cycles. High absorptance value and simplicity in the synthesis process render the coatings to be very promising candidates for solar selective absorber (SSA) applications.     

Validation of quantitative structure-activity relationship (QSAR) model for photosensitizer activity prediction

Photodynamic therapy is a relatively new treatment method for cancer which utilizes a combination of oxygen, a photosensitizer and light to generate reactive singlet oxygen that eradicates tumors via direct cell-killing, vasculature damage and engagement of the immune system. Most of photosensitizers that are in clinical and pre-clinical assessments, or those that are already approved for clinical use, are mainly based on cyclic tetrapyrroles. In an attempt to discover new effective photosensitizers, we report the use of the quantitative structure-activity relationship (QSAR) method to develop a model that could correlate the structural features of cyclic tetrapyrrole-based compounds with their photodynamic therapy (PDT) activity. In this study, a set of 36 porphyrin derivatives was used in the model development where 24 of these compounds were in the training set and the remaining 12 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA) method. Based on the method, r(2) value, r(2) (CV) value and r(2) prediction value of 0.87, 0.71 and 0.70 were obtained. The QSAR model was also employed to predict the experimental compounds in an external test set. This external test set comprises 20 porphyrin-based compounds with experimental IC(50) values ranging from 0.39 μM to 7.04 μM. Thus the model showed good correlative and predictive ability, with a predictive correlation coefficient (r(2) prediction for external test set) of 0.52. The developed QSAR model was used to discover some compounds as new lead photosensitizers from this external test set.     

Design of new competitive dengue ns2b/ns3 protease inhibitors-a computational approach

Dengue is a serious disease which has become a global health burden in the last decade. Currently, there are no approved vaccines or antiviral therapies to combat the disease. The increasing spread and severity of the dengue virus infection emphasizes the importance of drug discovery strategies that could efficiently and cost-effectively identify antiviral drug leads for development into potent drugs. To this effect, several computational approaches were applied in this work. Initially molecular docking studies of reference ligands to the DEN2 NS2B/NS3 serine protease were carried out. These reference ligands consist of reported competitive inhibitors extracted from Boesenbergia rotunda (i.e., 4-hydroxypanduratin A and panduratin A) and three other synthesized panduratin A derivative compounds (i.e., 246DA, 2446DA and 20H46DA). The design of new lead inhibitors was carried out in two stages. In the first stage, the enzyme complexed to the reference ligands was minimized and their complexation energies (i.e., sum of interaction energy and binding energy) were computed. New compounds as potential dengue inhibitors were then designed by putting various substituents successively on the benzyl ring A of the reference molecule. These substituted benzyl compounds were then computed for their enzyme-ligand complexation energies. New enzyme-ligand complexes, exhibiting the lowest complexation energies and closest to the computed energy for the reference compounds, were then chosen for the next stage manipulation and design, which involved substituting positions 4 and 5 of the benzyl ring A (positions 3 and 4 for 2446DA) with various substituents.