APPLICATION OF GRAPH-THEORETICAL PARAMETERS IN QUANTIFYING MOLECULAR SIMILARITY AND STRUCTURE-ACTIVITY-RELATIONSHIPS

Two molecular similarity methods have been used to select nearest neig hbors from four different sets of chemicals. One of the methods is bas ed on the Euclidean distance of chemicals in the ten dimensional princ ipal components space derived from 97 graph invariants. The second app roach is based on the count of atom pairs common to a pair of molecule s. Two probe chemicals were selected, and neighbors of each were deter mined by the two methods for the following four sets of molecules: (a) a combined set of octane and nonane isomers, (b) a relatively more di verse set of 382 chemicals, (c) a diverse set of 3692 chemicals, and ( d) the STARLIST data base of log P consisting of 4067 structures. The results show that the measures reflect an intuitive notion of chemical similarity.