
ALT Strategy to use a masked language model to mutate molecule sequences. First, a given molecule is tokenized (i.e. split into commonly occurring subsequences). Second, certain tokens are masked. Finally, the masked language model ranks possible replacements for the mask based on neighboring tokens, providing possible mutations.

ALT Training runs with molecules of 20 atoms or less. Results are shown for control (blue) and drug replacement with recombination (green). (a) Histogram showing number of new molecules produced in control run for different drug-likeness scores. (b) Histogram showing number of new molecules produced in our approach using updates to the training data for different drug-likeness scores. (c) A few sample new molecules from the drug replacement with recombination run.





















