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SAR QSAR Environ Res ; 24(10): 863-82, 2013 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-23985014

RESUMO

In this study we present prediction models for estimating in silico the cationic hydrophobicity and the cytotoxicity (log [1/EC50]) of ionic liquids (ILs) towards the Leukemia rat cell line (IPC-81), the marine bacterium Vibrio fischeri and the limnic green algae Scenedesmus vacuolatus using linear free energy relationship (LFER) descriptors computed by COSMO calculations. The LFER descriptors used for the prediction model (i.e. excess molar refraction (E), dipolarity/polarizability (S), hydrogen-bonding acidity (A), hydrogen-bonding basicity (B) and McGowan volume (V)) were calculated using sub-descriptors (sig2, sig3, HBD3, HBA4, MR, and volume) derived from COSMO-RS, COSMO and OBPROP. With the combination of two solute descriptors (B, V) of the cation we were able to predict cationic hydrophobicity values (log ko ) with r (2) = 0.987 and standard error (SE) = 0.139 log units. By using the calculated log k o values, we were able to deduce a linear toxicity prediction model. In the second prediction study for the cytotoxicity of ILs, analysis of descriptor sensitivity helped us to determine that the McGowan volume (V) terms of the cation was the most important predictor of cytotoxicity and to simplify prediction models for cytotoxicity of ILs towards the IPC-81 (r (2) of 0.778, SE of 0.450 log units), Vibrio fischeri (r (2) of 0.762, SE of 0.529 log units) and Scenedesmus vacuolatus (r (2) of 0.776, SE of 0.825 log units). The robustness and predictivity of the two models for IPC-81 and Vibrio fischeri were checked by comparing the calculated SE and r (2) (coefficient of determination) values of the test set.


Assuntos
Aliivibrio fischeri/efeitos dos fármacos , Interações Hidrofóbicas e Hidrofílicas , Líquidos Iônicos/química , Líquidos Iônicos/toxicidade , Células Mieloides/efeitos dos fármacos , Scenedesmus/efeitos dos fármacos , Animais , Linhagem Celular Tumoral , Sobrevivência Celular/efeitos dos fármacos , Modelos Estatísticos , Ratos
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