To study quantitative structure-activity/property relationships (QSAR/QSPR) for hydroxy acids and amino acids, the distance matrices and the augmented distance matrices have been constructed to derive the chiral parameters. Several regression results obtained by using these parameters have been achieved. Chiral topological indices eAm by extending Am indices, chiral product parameters as well as their combinations were used to explain the variance in thin-layer chromatographic indices. For the same purpose, artificial neural networks were applied, and the results were improved obviously. The methods suggest that this research can be used for QSAR/QSPR extensively.

Key words: chiral compound, QSAR/QSPR, chiral index, multiple regression analysis, artificial neural network