An in silico approach to cytotoxicity of pharmaceuticals and personal care products on the rainbow trout liver cell line RTL-W1.

Abstract

The authors constructed novel, robust, and validated linear Quantitative Structure-Toxicity Relationship (QSTR) models in line with Organisation of Co-operation and Development (OECD) criteria using 2 cytotoxicity data sets which were obtained from the Alamar Blue and 5-carboxyfluorescein diacetate acetoxymethyl ester (CFDA-AM) assays. The data sets comprise the cytotoxic effect of structurally diverse and widely used pharmaceuticals, synthetic musks, and industrial chemicals on the rainbow trout (Oncorhynchus mykiss) liver cell line RTL-W1. Common descriptors defined the relationship between structure and cytotoxicity for both the Alamar Blue and the CFDA-AM assays which measure the metabolic activity and membrane integrity, respectively. Only the statistical parameters of the best Alamar Blue-based model were given (nTR = 13; R2 = 0.839; the root-mean-square error of the training set [RMSETR ] = 0.261; nTEST = 5; R2TEST = 0.903; RMSETEST = 0.181; CCCTEST = 0.939). The proposed QSTR model was able to predict the cytotoxicity of 101 diverse chemicals on the RTL-W1 cell line with 91% structural coverage. The authors found that in vitro-derived cytotoxicity data are promising predictors of in vivo fish toxicity and may provide an initial, rapid screening tool for acute fish toxicity assessment and reduce the need for extensive in vivo toxicity testing. Environ Toxicol Chem 2017;36:1162-1169. © 2016 SETAC.