Determination of octanol/water partition coefficients by flow injection analysis

Determination of octanol/water partition coefficients by batch-extraction methods is currently the only acceptable procedure for application to structure/activity relationships. Work on the development of flow-injection systems to determine these partition coefficients is reported. It is shown that it is not necessary to know the concentration of the analytic in either phase; the partition coefficient should be equal to the differences in the octanol and water peak widths divided. by the system residence time. For a limited number of compounds, this is shown to be valid. Several systems were developed, including a flow-through dialyzer which was 5 times more efficient than the best commercial unit.     

Transferability of fragmental contributions to the octanol/water partition coefficient: an NDDO-based MST study

This study examines the transferability of fragmental contributions to the octanol/water partition coefficient. As a previous step, we report the parameterization of the AM1 and PM3 versions of the MST model for n-octanol. The final AM1 and PM3 MST models reproduce the experimental free energy of solvation and the octanol/water partition coefficient (log P(ow)) with a root-mean-square deviation of around 0.7 kcal/mol and 0.5 (in units of log P), respectively. Based on this parameterization, an NNDO-based procedure is presented to dissect the free energy of transfer between octanol and water in contributions directly associated with specific atoms or functional groups. The application of this procedure to a set of representative molecular systems illustrates the dependence of the log P(ow) fragmental contribution due to electronic, hydrogen bonding, and steric effects, which cannot be easily accounted for in simple additive-based empirical schemes. The results point out the potential use of theoretical methods to refine the fragmental contributions in empirical methods.     

Novel atomic-level-based AI topological descriptors: application to QSPR/QSAR modeling

Novel atomic level AI topological indexes based on the adjacency matrix and distance matrix of a graph is used to code the structural environment of each atomic type in a molecule. These AI indexes, along with Xu index, are successfully extended to compounds with heteroatoms in terms of novel vertex degree v(m), which is derived from the valence connectivity delta(v) of Kier-Hall to resolve the differentiation of heteroatoms in molecular graphs. The multiple linear regression (MLR) is used to develop the structure-property/activity models based on the modified Xu and AI indices. The efficiency of these indices is verified by high quality QSPR/QSAR models obtained for several representative physical properties and biological activities of several data sets of alcohols with a wide range of non-hydrogen atoms. The results indicate that the physical properties studied are dominated by molecular size, but other atomic types or groups have small influences dependent on the studied properties. Among all atomic types, -OH groups seem to be most important due to hydrogen-bonding interactions. On the contrary, -OH groups play a dominant role in biological activities studied, although molecular size is also an important factor. These results indicate that both Xu and AI indices are useful model parameters for QSPR/QSAR analysis of complex compounds.