Computer-Assisted Methods in Chemical Toxicity Prediction
C. Gopi Mohan, Tamanna Gandhi, Divita Garg and Ranajit Shinde
Affiliation: Centre for Pharmacoinformatics,National Institute of Pharmaceutical Education and Research, Sector 67, S.A.S. Nagar, Punjab-160 062, India.
In Silico predictive ADME/Tox screening of compounds is one of the hottest areas in drug discovery. To provide predictions of compound drug-like characteristics early in modern drug-discovery decision making, computational technologies have been widely accepted to develop rapid high throughput in silico ADMET analysis. It is widely perceived that the early screening of chemical entities can significantly reduce the expensive costs associated with late stage failures of drugs due to poor ADME/Tox properties. Drug toxic effects are broadly defined to include toxicity, mutagenicity, carcinogenicity, teratogenicity, neurotoxicity and immunotoxicity. Toxicity prediction techniques and structure-activity relationships relies on the accurate estimation and representation of physico-chemical and toxicological properties. This review highlights some of the freely and commercially available softwares for toxicity predictions. The information content can be utilized as a guide for the scientists involved in the drug discovery arena.
Keywords: Toxicity prediction, In silico, TOPKAT, LAZAR, DEREK, MULTICASE, HazardExpert, OncoLogic
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