A COMPUTERIZED CONNECTIVITY APPROACH FOR ANALYZING THE STRUCTURAL BASIS OF MUTAGENICITY IN SALMONELLA AND ITS RELATIONSHIP WITH RODENT CARCINOGENICITY

We have applied a new software program, based on graph theory and deve loped by our group, to predict mutagenicity in Salmonella. The softwar e analyzes, as information in input, the structural formula and the bi ological activities of a relatively large data base of chemicals to ge nerate a ny possible molecular fragment with size ranging From two to ten nonhydrogen atoms, and detects (as predictors of biological activi ty) those fragments statistically associated with the biological prope rty investigated. Our previous work used the program to predict carcin ogenicity in small rodents. In the current work we applied a modified version of the program, which bases its predictions solely on the most important fragment present in a given molecule, considering as practi cally negligible the effects of additional less important fragments. F or Salmonella mutagenicity we used a database of 551 compounds, and th e program achieved a level of predictivity (73.9%) comparable to that obtained by other authors using the Computer Automated Structure Evalu ation (CASE) program. We evaluated the relative contributions of bioph ores and biophobes to overall predictivity: biophores tended to be mor e important than biophobes, and chemicals containing both biophores an d biophobes were more difficult to predict. Many of the molecular Frag ments identified by the program as being strongly associated with muta genic activity were similar to the structural alerts identified by the human experts Ashby and Tennant. Our results tend to confirm that str uctural alerts useful to predict Salmonella mutagenicity are generally not very strong predictors of rodent carcinogenicity. Although the pr edictivity level achieved for oncogenic activity improved when the pro gram was directly trained with carcinoge nicity date, carcinogenicity as a biological endpoint was still more difficult to predict than Salm onella mutagenicity. (C) 1996 Wiley-Liss, Inc.