In silico prediction of ADME and toxicity profiles of the drug candidates

Abstract

Computational methods present an advantage of estimating the bioavailability and safety of drug candidates and selecting better lead compounds even before they are synthesized and undergo preclinical tests and clinical trials. The computational models that can predict ADME/Tox profiles have become an alternative and complementary approach to existing in vitro and in vivo toxicity tests, thereby minimizing the need for animal testing, reducing the cost and time of relevant tests, and improving bioavailability/toxicity prediction and efficacy/safety assessments. In silico drug design and development studies that focus on the treatment of COVID-19 increase day by day. Some old drugs and newly designed molecules are investigated in silico for the therapeutic potential against SARS-CoV-2 and their safety by different research groups. In this presentation, our in silico ADME/Tox profile studies of anti- SARS-CoV-2 agents will be discussed in detail based on different safety parameters including structural alerts, carcinogenicity, mutagenicity, and target organ toxicity.