Researchers from the University of Bonn have trained an AI process to predict potential active ingredients with special properties. Therefore, they derived a chemical language model – a kind of ChatGPT for molecules. Following a training phase, the AI was able to exactly reproduce the chemical structures of compounds with known dual-target activity that may be particularly effective medications.
The study has now been published in Cell Reports Physical Science . Do not publish before Wednesday, October 23rd, 5:00 pm CEST! Anyone who wants to delight their granny with a poem on her 90th birthday doesn't need to be a poet nowadays: A short prompt in ChatGPT is all it takes, and within a few seconds the AI spits out a long list of words that rhyme with the birthday girl's name. It can even produce a sonnet to go with it if you like.
Researchers at the University of Bonn have implemented a similar model in their study – known as a chemical language model. This does not, however, produce rhymes. Instead, the AI displays the structural formulas of chemical compounds that may have a particularly desirable property: They are able to bind to two different target proteins.
In the organism, this means, for example, they can inhibit two enzymes at once. Wanted: Active ingredients with a double effect In pharmaceutical research, these types of active compounds are highly desirable due to their polypharmacology." Prof.
Dr. Jürgen Bajorath The computational chemistry expert heads the .