British AI robot finds malaria killer in common toothpaste ingredient

An artificial intelligence (AI) robot made by a British university has a become a big star after it has helped scientists find a malaria killer in a common toothpaste ingredient.

The scientists at the University of Cambridge in Britain used the “Robot Scientist”, Eve, and discovered that triclosan. It is an ingredient found in many kinds of toothpaste. It may help fight against strains of a malaria parasite that have grown resistant to one of the recently-used drugs to treat disease.

The researchers discovered that triclosan inhabits the spread of a kind of enzyme of the malaria parasite called DHFR. Thus stopping the growth the of the parasite in the blood.

The discovery challenged an early assumption that triclosan inhabits the growth in the culture of the malaria parasite Plasmodium during the blood stage. The reason is that it is aiming an enzyme known as enoyl reductase (ENR) found in the liver.

The scientist discovered that triclosan was able to aim and act on the DHFR enzyme. Also in parasites that were resistant to an antimalarial drug named pyrimethamine. Malaria is spread to humans by the bites of a mosquito infected with malaria parasites that are transferred into their bloodstream via its saliva.

With the new function of triclosan, the researchers believe it is possible that the parasite may be targeted at both the liver stage and the later blood stage.

“The discovery by our robot ‘colleague’ Eve that triclosan is effective against malaria targets offers hope that we may be able to use it to develop a new drug,” said Elizabeth Bilsland, lead author of the study.

Robot Eve was developed by a group of scientists at the British universities of Manchester, Aberystwyth in Wales, and Cambridge. The development was led by Professor Ross King. Who is from the Manchester Institute of Biotechnology at the University of Manchester.

It automates and speeds up the drug discovery process, including auto testing of hypotheses to explain observations, running experiments, and automating high-throughput hypothesis-led research.

AI and machine learning make it possible to create automated scientists that “take an intelligent approach to science,” which could greatly speed up the drug discovery progress, King said.