Development of predictive QSAR models for Vibrio fischeri toxicity of ionic liquids and their true external and experimental validation tests
نویسندگان
چکیده
Despite possessing an interesting chemical nature and tuneable physicochemical properties, ionic liquids (ILs) must have their ecotoxicity tested in order to be commercialized. The water solubility of ILs allows their easy access to the aquatic compartment of the ecosystem creating a potential hazard to aquatic organisms. Hence, it is relevant to design ionic liquids with lower toxicity while keeping the desired properties of interest. Considering the possibility of an enormous number of combinations of different cations and anions, a rational guidance for the structural design of ionic liquids is essential in order to prioritize the synthesis as well as testing of selected molecules only. Predictive in silico models, such as quantitative structure–activity relationship (QSAR) models, can play a pivotal role in exploring the important chemical attributes contributing to the response activity. These models may then lead to the design of novel ionic liquids. The present study aims at developing predictive QSAR models for the ecotoxicity of ionic liquids using the bacteria Vibrio fischeri as an indicator response species. Instead of a single model, here we have used multiple models to capture more complete structural information of ionic liquids for toxicity towards Vibrio fischeri. The derived chemical attributes have been implemented in designing new analogues, some of which have been synthesized and had their ecotoxicity tested for the same model organism. The predictive QSAR models reported here can be used for ecotoxicity prediction of new IL chemicals and for data-gap filling. Moreover, the synthesized low-toxic ILs could be considered for evaluation as well as for application in suitable processes serving the purpose of industry and academia.
منابع مشابه
Comparative QSAR Analysis of 3,5-bis (Arylidene)-4-Piperidone Derivatives: the Development of Predictive Cytotoxicity Models
1-[4-(2-Alkylaminoethoxy)phenylcarbonyl]-3,5-bis(arylidene)-4-piperidones are a novel class of potent cytotoxic agents. These compounds demonstrate low micromolar to submicromolar IC50 values against human Molt 4/C8 and CEM T-lymphocytes and murine leukemia L1210 cells. In this study, a comparative QSAR investigation was performed on a series of 3,5-bis(arylidene)-4-piperidones using different ...
متن کاملA Spectral-SAR Model for the Anionic-Cationic Interaction in Ionic Liquids: Application to Vibrio fischeri Ecotoxicity
Within the recently launched the spectral-structure activity relationship (S-SAR) analysis, the vectorial anionic-cationic model of a generic ionic liquid is proposed, along with the associated algebraic correlation factor in terms of the measured and predicted activity norms. The reliability of the present scheme is tested by assessing the Hansch factors, i.e. lipophylicity, polarizability and...
متن کاملComparative QSAR Analysis of 3,5-bis (Arylidene)-4-Piperidone Derivatives: the Development of Predictive Cytotoxicity Models
1-[4-(2-Alkylaminoethoxy)phenylcarbonyl]-3,5-bis(arylidene)-4-piperidones are a novel class of potent cytotoxic agents. These compounds demonstrate low micromolar to submicromolar IC50 values against human Molt 4/C8 and CEM T-lymphocytes and murine leukemia L1210 cells. In this study, a comparative QSAR investigation was performed on a series of 3,5-bis(arylidene)-4-piperidones using different ...
متن کاملToxicity assessment of organic pollutants: reliability of bioluminescence inhibition assay and univariate QSAR models using freshly prepared Vibrio fischeri.
The toxicity of 14 industrially relevant organic chemicals was determined using freshly grown Vibrio fischeri bioluminescence inhibition assay. The results were compared to lyophilized V. fischeri, 96h fish, 48h Daphnia magna and 95h green algae bioassays. Reliability of octanol-water partition coefficient (K(ow)), and first order simple and valence molecular connectivity index ((1)chi, (1)chi(...
متن کاملA Novel QSAR Model for the Evaluation and Prediction of (E)-N’-Benzylideneisonicotinohydrazide Derivatives as the Potent Anti-mycobacterium Tuberculosis Antibodies Using Genetic Function Approach
Abstract A dataset of (E)-N’-benzylideneisonicotinohydrazide derivatives as a potent anti-mycobacterium tuberculosis has been investigated utilizing Quantitative Structure-Activity Relationship (QSAR) techniques. Genetic Function Algorithm (GFA) and Multiple Linear Regression Analysis (MLRA) were used to select the descriptors and to generate the correlation QSAR models that relate the Mi...
متن کامل