https://phys.org/news/2018-07-automating-molecule-drug.html

Often, chemists use expert knowledge and conduct manual tweaking of molecules, adding and subtracting functional groups—atoms and bonds responsible for specific chemical reactions—one by one. Even if they use systems that predict optimal chemical properties, chemists still need to do each modification step themselves. This can take hours for each iteration and may still not produce a valid drug candidate.

Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and Department of Electrical Engineering and Computer Science (EECS) have developed a model that better selects lead molecule candidates based on desired properties. It also modifies the molecular structure needed to achieve a higher potency, while ensuring the molecule is still chemically valid.