Exploration of Computational Approaches in Toxicity Prediction
Prashant Revan Murumkar, Rasana Yadav, Rahul R. Barot, Rutvi Shah, V.K. Srivastava, M. R. Yadav · Apple Academic Press eBooks · 2025
During drug development, it has been observed that safety is the most important issue. For the estimation of chemical safety of designed molecules, evaluation of chemical toxicity is of great importance. In recent years machine learning models have gathered exceptional attention in order to predict the toxicity of small molecules. There are several toxic parameters which were identified In-silico like acute oral toxicity, hepatotoxicity, cardiotoxicity, mutagenicity, etc. In a last decade various software’s were develop to predict the toxicity. This chapter include computational approaches to predict the toxicity of small molecules using software’s like ProTox-II, Derek (Deductive estimate of risk from existing knowledge), ToxiM, ADMET Predictor, OECD toolbox, Toxtree, q-Tox, TOPKAT, MDL QSAR, Osiris property explorer, T.E.S.T., etc.