An in silico algal toxicity model with a wide applicability potential for industrial chemicals and pharmaceuticals

Abstract

The authors modeled the 72-h algal toxicity data of hundreds of chemicals with different modes of action as a function of chemical structures. They developed mode of action-based local quantitative structure-toxicity relationship (QSTR) models for nonpolar and polar narcotics as well as a global QSTR model with a wide applicability potential for industrial chemicals and pharmaceuticals. The present study rigorously evaluated the generated models, meeting the Organisation for Economic Co-operation and Development principles of robustness, validity, and transparency. The proposed global model had a broad structural coverage for the toxicity prediction of diverse chemicals (some of which are high-production volume chemicals) with no experimental toxicity data. The global model is potentially useful for endpoint predictions, the evaluation of algal toxicity screening, and the prioritization of chemicals, as well as for the decision of further testing and the development of risk-management measures in a scientific and regulatory frame. Environ Toxicol Chem 2017;36:1012-1019. © 2016 SETAC.

Assessments of Algal Toxicity and PBT Behaviour of Pesticides with No Eco‐toxicological Data: Predictive Ability of QSA/(T)R Models

“…The experimental value of the studied eight pesticides were compared with four QSA/(T)R models selected from the literature . Detailed information on these four models was given in Table S8 (Supporting Information) together with the number of training and test chemicals (n Tr /n Test ), the AD ranges based on the dependent variable (pT) and leverage approach…”

“…Model 3 was generated using toxicity data for freshwater green algae Chlorella vulgaris, whereas model 4 was generated using toxicity data for mixed type of freshwater algae including particularly data on Pseudokirchneriella subcapitata and Chlorella vulgaris . Similarly, descriptors relevant to another two‐descriptor model (model 3) and the eight‐descriptor model (model 4) were calculated and used to predict the algal toxicity values of pesticides. The descriptor and hat values are given together with the predicted algal toxicity values by model 3 and model 4, in Table S11 and Table S12 (Supporting Information), respectively.…”

“…Four different linear QSA/(T)R models were selected from the literature to compare the measured and predicted algal toxicity of the eight pesticides from these models. At first, two QSAR models were considered.…”

“…The fourth selected QSTR model (eq. 4) was on the 72‐h algal toxicity (pEC 50 ) of 389 diverse chemicals reported by Önlü and Saçan . Descriptors (SPAM, Mor31p, NdsCH, CATS2D_02_AP, B05[C‐S], F03[C‐N], MLOGP2, and Hardness) appearing in this QSTR model were from SPARTAN 10 and DRAGON 6.4 software packages.…”

“…The first objective of this study is to determine the 96‐h algal toxicity of eight pesticides lacking ecotoxicological data using freshwater algae, Chlorella vulgaris , as a test organism and standardized test protocols . The second objective of the present study is to compare the experimental algal toxicity values with the predicted toxicity values from the selected QSA/(T)R models . The third objective of the present study is the assessment of PBT Index as implemented in QSARINS 2.2.1 software for the studied pesticides regarding that there is no existing relevant information for them.…”