A New Approach to the Prediction of Partition Coefficients in Water/Organic Interfaces

In the present work, a new approach for the determination of the partition coefficient in different interfaces based on the density function theory is proposed. Our results for log P(ow) considering a n-octanol/water interface for a large super cell for acetone -0.30 (-0.24) and methane 0.95 (0.78) are comparable with the experimental data given in parenthesis. We believe that these differences are mainly related to the absence of van der Walls interactions and the limited number of molecules considered in the super cell. The numerical deviations are smaller than that observed for interpolation based tools. As the proposed model is parameter free, it is not limited to the n-octanol/water interface.

Application of Microelectrode Voltammetry to Study the Properties of Surfactant Solutions: Alkyltrimethylammonium Bromides

Microelectrode cyclic voltammetry (MV) has been employed to investigate the micellar properties of solutions of homologous alkyltrimethylammonium bromides, RMe(3)ABr, R = C(10), C(12), and C(14), in water and in the presence of added NaBr. The micellar self-diffusion coefficient was calculated from the limiting current for the reversible electron transfer of micelle-bound ferrocene. From the values of this property, other parameters were calculated, including the micellar hydrodynamic radius, RH, and aggregation number, N(agg); the latter was also theoretically calculated. We determined the values of the diffusion coefficient as a function of various experimental variables and observed the following trends: The diffusion coefficient decreases as a function of increasing surfactant concentration (no additional electrolyte added); it decreases as a function of increasing surfactant concentration at fixed NaBr concentration; and it shows a complex dependence (increase then decrease) on the NaBr concentration at a fixed RMe(3)ABr concentration. The value of the intermicellar interaction parameter decreases and then increases as a function of increasing NaBr concentration. These results are discussed in terms of intermicellar,interactions and the effect of NaBr on the micellar surface charge density and sphere-to-rod geometry change. The NaBr concentration required to induce the latter change increases rapidly as a function of decreasing the length of R: no geometry change was detected for C(10)Me(3)ABr. Values of N(agg) increase as I function of increasing the length of R and are in good agreement with both literature values and values that were calculated theoretically. Thus, MV is a convenient and simple technique for obtaining fundamental properties of surfactant solutions, including additive-induced changes of micellar parameters (N(agg)) and morphology changes.

Ion pair stabilization effects on a series of procaine structural analogs

In this work, a series of 10 structural procaine analogs have been synthesized in order to investigate the structural features affecting the stability of ion pair formation and its influence on the lipophilicity of ionizable compounds. The structural variation within this series was focused on the terminal nitrogen substituents and on the intermediate chain linkage nature. The hydrophobic parameters log P(n) and log P(i) (partition coefficient of the neutral and ionic species, respectively), as well as the ionization constants pK(a) and pK(a)(oct), were obtained from log D-pH profiles measured at pH values ranging from 2 to 12. The difference between log P(i) and log P(n) values (i.e. difflog P) of each prepared compound was considered a measure of the stability of ion pair formation. In this set, the difflog P values varied nearly over one log unit, ranging from -2.40 to -3.37. It has been observed that the presence of hydrogen bonding groups (especially donor) and low steric hindrance around the terminal amine ionizable group increases the relative lipophilicity of the ionic species as compared to the corresponding neutral species. These results were interpreted as due to the increased stability of ion pairs of the compounds bearing these structural features. (C) 2010 Elsevier B.V. All rights reserved.

Artificial Neural Networks and the Study of the Psychoactivity of Cannabinoid Compounds

Cannabinoid compounds have widely been employed because of its medicinal and psychotropic properties. These compounds are isolated from Cannabis sativa (or marijuana) and are used in several medical treatments, such as glaucoma, nausea associated to chemotherapy, pain and many other situations. More recently, its use as appetite stimulant has been indicated in patients with cachexia or AIDS. In this work, the influence of several molecular descriptors on the psychoactivity of 50 cannabinoid compounds is analyzed aiming one obtain a model able to predict the psychoactivity of new cannabinoids. For this purpose, initially, the selection of descriptors was carried out using the Fisher`s weight, the correlation matrix among the calculated variables and principal component analysis. From these analyses, the following descriptors have been considered more relevant: E(LUMO) (energy of the lowest unoccupied molecular orbital), Log P (logarithm of the partition coefficient), VC4 (volume of the substituent at the C4 position) and LP1 (Lovasz-Pelikan index, a molecular branching index). To follow, two neural network models were used to construct a more adequate model for classifying new cannabinoid compounds. The first model employed was multi-layer perceptrons, with algorithm back-propagation, and the second model used was the Kohonen network. The results obtained from both networks were compared and showed that both techniques presented a high percentage of correctness to discriminate psychoactive and psychoinactive compounds. However, the Kohonen network was superior to multi-layer perceptrons.