Chemometric Modeling of Algal and Daphnia Toxicity
Luminita Crisan, Ana Borota, Alina Bora, Simona Funar‐Timofei, Gheorghe Ilia · 2021
The REACH (Registration, Evaluation, Authorization, and Restriction of Chemicals) regulations suggest the use of alternative approaches like quantitative structure–activity/toxicity/property relationships (QSARs/QSTRs/QSPRs) to reduce the in vivo experiments which kills animals to save human and financial resources. The QSAR/QSTR/QSPR models use mathematical equations to correlate the biological activity/toxicity/property with molecular parameters obtained from the molecular structure of compounds. A great development is noticed lately in the utilization of these computational modeling techniques in the toxicity domain. In the present chapter, some reported QSAR/QSTR models are included to illustrate the modeling of the aquatic toxicity data for different classes of compounds (nitrobenzenes, anilines, phenols, carboxylates, benzaldehydes, benzoic acids, organophosphates, esters, polyaromatic hydrocarbons, and sulfonates). These approaches were applied to estimate the toxicity of compounds to different species of algae (e.g. Scenedesmus obliquus , Scenedesmus quadricauda , Chlorella vulgaris , Chlorella pyrenoidosa , and Pseudokirchneriella subcapitata ) and daphnia (e.g. Daphnia magna, Daphnia pulex ). Interspecies correlation estimation (ICE) models applied to algae and daphnia extrapolate the known toxicity of chemicals of interest to species missing toxicity data. In silico (QSAR, QSTR, etc.) approaches and interspecies correlation estimation and their derived models constitute important computer-based techniques as a cost-effective alternative to fill the aquatic toxicity data gap for algae and daphnia, to reduce animal sacrifices and the environmental hazardous risks.