In Silico Prediction of Human Organ Toxicity via Artificial Intelligence Methods.

Unpredicted human organ level toxicity remains one of the major reasons for drug clinical failure. There is a critical need for cost-efficient strategies in the early stages of drug development for human toxicity assessment. At present, artificial intelligence methods are popularly regarded as a promising solution in chemical toxicology. Thus, we provided comprehensive in silico prediction models for eight significant human organ level toxicity end points using machine learning, deep learning, and transfer learning algorithms. In this work, our results showed that the graph-based deep learning approach was generally better than the conventional machine learning models, and good performances were observed for most of the human organ level toxicity end points in this study. In addition, we found that the transfer learning algorithm could improve model performance for skin sensitization end point using source domain of in vivo acute toxicity data and in vitro data of the Tox21 project. It can be concluded that our models can provide useful guidance for the rapid identification of the compounds with human organ level toxicity for drug discovery.

New Strategies for Responding to SARS-CoV-2: The Present and Future of Dual-Target Drugs.

The 2019 coronavirus disease (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in millions of deaths, posing a serious threat to public health and safety. Rapid mutations of SARS-CoV-2 and complex interactions among multiple targets during infection pose a risk of expiry for small molecule inhibitors. This suggests that the traditional concept of "one bug, one drug" could be ineffective in dealing with the coronavirus. The dual-target drug strategy is expected to be the key to ending coronavirus infections. However, the lack of design method and improper combination of dual-targets poses obstacle to the discovery of new dual-target drugs. In this Perspective, we summarized the profiles concerning drug design methods, structure-activity relationships, and pharmacological parameters of dual-target drugs for the treatment of COVID-19. Importantly, we underscored how target combination and rational drug design illuminate the development of dual-target drugs for SARS-CoV-2.