Comparison of Chemical Toxicity to Different Algal Species Based on Interspecies Correlation, Species Sensitivity, and Excess Toxicity. Issue 7 (21st March 2016) - Wang, Xiao H.; Yu, Yang; Fu, Ling; Tai, Hong W.; Qin, Wei C.; Su, Li M.; Zhao, Yuan H.
Abstract : Although algal toxicity is species dependent, it is not clear if compounds share the same modes of action (MOAs) among algal species. Investigations on the algal toxicity to six species show that Pseudokirchneriella subcapitata is the most sensitive species and its toxicity is significantly related to Dunaliella tertiolecta toxicity, but relates poorly to other algal species. The excess toxicity calculated from a baseline model shows that most of the compounds share the same MOAs among different species, but some share different MOAs. Anilides show excess toxicity to P. subcapitata, but not to other species; they are predicted as reactive compounds to P. subcapitata, but narcotics to other algal species. On the other hand, although hydroxyquinones and phenylureas show greater toxicity to P. subcapitata than to any other algal species, they are predicted as reactive compounds to all algal species because of excess toxicity to all species. Development of any quantitative structure–activity relationship model should be based on a single algal species because algal toxicity is species dependent. Several outliers have been observed, such as acids and highly hydrophobic chemicals with long chains. Their toxicities are over‐estimated from linear baseline models because of over‐estimated log K OW for ionized acids and obstruction of algal cell membranes for long chain compounds. Abstract : Although algal toxicity is species dependent, it is not clear if compounds have the same toxicity sensitivity among algal species. The interspecies correlations show that most of the tested compounds have the same toxicity sensitivity and share the same modes of action (MOA) in algal toxicity, but some share different MOA. This information will help understanding toxic mechanisms and developing quantitative structure–activity relationships.