QSAR models for predicting cardiac toxicity of drugs

Cardiotoxicity can play a significant impact on the costs and approval time of a drug. It is a demanding task to develop safe drugs to treat human diseases, with toxicity being a major source of failure in the later stages of development. In this chapter, we examine the computational methods used to predict cardiotoxicity, which can be challenging due to the unpredictable nature of its onset. One area of particular interest is the hERG channel, which has a high affinity for binding to many different types of drugs and has a large amount of data used to generate QSAR models. We also reviewed all freely available QSAR models published between 2016 and 2022 in the literature and discussed the potential of using the newly published hERG Cryo-EM structure to aid drug discovery efforts. Overall, this chapter provides a comprehensive overview of the challenges and opportunities in predicting the risk of cardiotoxicity, which can help save time and reduce the risk of drug withdrawals.