“Today the computer is just as important as tool for chemists as the test tube. Simulations are so realistic that they predict the outcome of traditional experiments.”
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In C&EN's June cover story, Matthias Rarey highlights how computational tools help to navigate chemical spaces and virtual libraries in the search for new drugs.
Connecting chemical building blocks allows drug hunters to explore a much bigger chemical space than before. The challenge is to narrow this field of compounds to something manageable. To do that, chemists are turning to new computational tools to navigate this increasingly huge chemical universe, and they are combining technologies. Experts say these new approaches should speed up the identification process, and industry is investing time and money to optimize the hunt.
Frank Glorius and Philipp Pflüger talk about the new field of research “Molecular Machine Learning".
“Molecular Machine Learning” (MML) is a new branch of research with the potential to change chemical research. Prof. Frank Glorius, coordinator of the new Priority Programme “Molecular Machine Learning” (SPP 2363), funded by the German Research Foundation (DFG), and Philipp Pflüger, who is working on his PhD in Chemistry and helped to develop the programme, explain in this interview with Christina Hoppenbrock what MML means, what opportunities and challenges this new field of research presents, and what working in chemistry will be like in tomorrow’s world.
