Biomedical subjects
Publications and source records attributed to James L Melville.
A catalyst design methodology, utilizing combinatorial synthesis in parallel with chemometric analysis, is presented, which considers the 3D steric and electrostatic properties of substituents about a constant core structure.
Surfactant adsorption has been shown to have a passivating effect on the electrode surface during anodic stripping voltammetric measurements. In the present work the feasibility of sono-anodic stripping analysis for the determination of copper in aqueous media contaminated with surfactant has been studied at an unmodified bare glassy carbon electrode. We illustrate the deleterious effect of three common surfactants, sodium dodecyl sulfate (SDS), dodecyl pyridinium chloride (DPC) and Triton-X 100 (TX-100) on conventional electroanalysis. The analogous sono-electroanalytical response was investigated for each surfactant at ultrasound intensities above and below the cavitation threshold. The enhancement in the stripping signal observed is attributed to the increased mass transport due to acoustic streaming and above the cavitation threshold the intensity of cavitational events is significantly increased leading to shearing of adsorbed surfactant molecules from the surface. As a result accurate analyses for SDS concentrations up to 100 ppm are possible, with analytical signals visible in solutions of SDS and TX-100 of 1000 ppm. Analysis is reported in high concentration of surfactant with use of sono-solvent double extraction. The power of this technique is clearly illustrated by the ability to obtain accurate measurements of copper concentration from starting solutions containing 1000 ppm SDS or TX-100. This was also exemplified by analysis of the low concentration 0.3 microM Cu(II) solution giving a percentage recovery of 94% in the presence of 1000 ppm SDS or TX-100.
Abrupt, smooth, and box methods for the calculation of electrostatic and steric field values in the comparative molecular field analysis (CoMFA) 3D QSAR technique are assessed on three diverse data sets of medicinal chemistry interest. While the standard CoMFA settings are robust to small changes in the position of the lattice, superior results may sometimes be obtained by use of only one field. However, if only the electrostatic field is used, then sometimes large differences between models are apparent. This appears to be due to a lack of column dropping, and these difficulties can be remedied by use of the box method.
Quantitative Structure-Selectivity Relationships (QSSR) are developed for a library of 40 phase-transfer asymmetric catalysts, based around quaternary ammonium salts, using Comparative Molecular Field Analysis (CoMFA) and closely related variants. Due to the flexibility of these catalysts, we use molecular dynamics (MD) with an implicit Generalized Born solvent model to explore their conformational space. Comparison with crystal data indicates that relevant conformations are obtained and that, furthermore, the correct biphenyl twist conformation is predicted, as illustrated by the superiority of the resulting model (leave-one-out q(2) = 0.78) compared to a random choice of low-energy conformations for each catalyst (average q(2) = 0.22). We extend this model by incorporating the MD trajectory directly into a 4D QSSR and by Boltzmann-weighting the contribution of selected minimized conformations, which we refer to as '3.5D' QSSR. The latter method improves on the predictive ability of the 3D QSSR (leave-one-out q(2) = 0.83), as confirmed by repeated training/test splits.