Structural formulae show how chemical compounds are constructed, i.e., which atoms they consist of, how these are arranged spatially and how they are connected. Chemists can deduce from a structural formula, among other things, which molecules can react with each other and which cannot, how complex compounds can be synthesised or which natural substances could have a therapeutic effect because they fit together with target molecules in cells.
Developed in the 19th century, the representation of molecules as structural formulae has stood the test of time and is still used in every chemistry textbook. But what makes the chemical world intuitively comprehensible for humans is just a collection of black and white pixels for software. "To make the information from structural formulae usable in databases that can be searched automatically, they have to be translated into a machine-readable code," explains Christoph Steinbeck, Professor for Analytical Chemistry, Cheminformatics and Chemometrics at the University of Jena.
An image becomes a code
And that is precisely what can be done using the Artificial Intelligence tool "DECIMER", developed by the team led by Prof. Steinbeck and his colleague Prof. Achim Zielesny from the Westphalian University of Applied Sciences. DECIMER stands for "Deep Learning for Chemical Image Recognition". It is an open-source platform that is freely available to everyone on the Internet and can be used in a standard web browser. Scientific articles containing chemical structural formulae can be uploaded there simply by dragging and dropping, and the AI tool will immediately get to work.
