Artificial intelligence accelerates the discovery of plants with antimalarial properties. This is the conclusion of an international research team with Swiss participation in a new study. Scientists from the Royal Botanic Gardens in London and the University of Freiburg have developed a new method based on machine learning.
In a short period of time, the approach discovered at least 1,300 species with antimalarial properties that would not have been found using conventional methods, according to the researchers in the study published in the journal Frontiers in Plant Science. Malaria medicines could be developed with these plants.
According to the University of Freiburg, plants as a rich source of bioactive substances have also laid the foundation for the development of numerous medicines in the past. For example, quinine and artemisinin – two important drugs against malaria – come from plants. However, resistance to these drugs is a growing challenge, according to the researchers.
However, since there are an estimated 343,000 different species of vascular plants, identifying plants with antimalarials can be time consuming and costly. In the study, the researchers examined 21,000 species from three plant families. The results show that 7677 of the species should be further studied. According to the scientists, almost every sixth of them would have been overlooked by conventional methods.
Source: Krone
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