MOLECULAR MODELING BY LINEAR-COMBINATIONS OF CONNECTIVITY INDEXES

The modeling power of the method of linear combinations of connectivit y indexes (LCCI), based on a minimal and on an expanded set of connect ivity indexes, has been tested on several properties of different clas ses of organic compounds: the melting points and motor octane numbers of alkanes, the melting points and solubilities of caffein homologues, and four different physicochemical properties of organophosphorus com pounds. The modeling of the first property, a classical shape-dependen t property and up to date a challenging problem of molecular modeling, was resolved by partitioning the entire set of alkanes into congruent subsets. A minimal set of normal and valence connectivity indexes was able to model the melting points of caffein homologues that have quit e similar molecular shapes and sizes, while the modeling of the solubi lities of these homologues was unravelled by taking into consideration their association in solution and by employing linear combinations of squared connectivity indexes. The very effective modeling of the two different types (shape- and size-dependent) of properties of the organ ophosphorus compounds, with a minimal set of connectivity indexes, del ineates also a test for the proposed valence delta(v) value of phospho rus in organophosphorus derivatives. Linear LCOCI combinations of orth ogonal connectivity indexes were also tested to improve, if possible, the modeling of the properties of the given classes of compounds. Mode led properties show that the connectivity indexes can be highly depend ent on the detailed knowledge of the physicochemical state of the inve stigated system and that, usually, LCCIs with a minimal basis set yiel d quite adequate modeling.