Ecotoxicological prediction of organic chemicals toward Pseudokirchneriella subcapitata by Monte Carlo approach. Issue 38 (1st September 2022)

• Record Type: Journal Article
• Authors: Lotfi, Shahram; Ahmadi, Shahin; Kumar, Parvin
• Is Part Of: RSC advances. Volume 12:Issue 38(2022)
• Page Start: 24988
• Page End: 24997
• Publication Date: 2022-09-01
• Subjects: Chemistry -- Periodicals; 540.5
• DOI: 10.1039/d2ra03936b
• Languages: English
• ISSNs: 2046-2069

Abstract

Abstract : In the ecotoxicological risk assessment, acute toxicity is one of the most significant criteria. Abstract : In the ecotoxicological risk assessment, acute toxicity is one of the most significant criteria. Green alga Pseudokirchneriella subcapitata has been used for ecotoxicological studies to assess the toxicity of different toxic chemicals in freshwater. Quantitative Structure Activity Relationships (QSAR) are mathematical models to relate chemical structure and activity/physicochemical properties of chemicals quantitatively. Herein, Quantitative Structure Toxicity Relationship (QSTR) modeling is applied to assess the toxicity of a data set of 334 different chemicals on Pseudokirchneriella subcapitata, in terms of EC10 and EC50 values. The QSTR models are established using CORAL software by utilizing the target function (TF2 ) with the index of ideality of correlation (IIC). A hybrid optimal descriptor computed from SMILES and molecular hydrogen-suppressed graphs (HSG) is employed to construct QSTR models. The results of various statistical parameters of the QSTR model developed for pEC10 and pEC50 range from excellent to good and are in line with the standard parameters. The models prepared with IIC for Split 3 are chosen as the best model for both endpoints (pEC10 and pEC50 ). The numerical value of the determination coefficient of the validation set of split 3 for the endpoint pEC10 is 0.7849 and for the endpoint pEC50, it is 0.8150. The structural fractions accountable for the toxicity of chemicals are also extracted. The hydrophilic attributes like 1… n …(… and S…(…… exert positive contributions to controlling the aquatic toxicity and reducing algal toxicity, whereas attributes such as c…c…c…, C…C…C… enhance lipophilicity of the molecules and consequently enhance algal toxicity.