Using Artificial Intelligence to develop better Antimalarial Drugs

Researchers at the Insilico Taiwan discovered a pipeline for end-to-end drug delivery with the use of new generation artificial intelligence. A recent research published in the Scientific Reports stated that malaria is one of the oldest infectious diseases in the world, especially in tropical countries. The study reveals that an inhibitor named E64 approaches and inhibits the parasite Plasmodium falciparum, the deadliest species causing malaria in humans, by blocking the activity of Falcipain-2 (FP-2). The parasite is believed to cause millions of illnesses and over half a million deaths in a year. Plasmodium falciparum in humans causes malaria by destructing haemoglobin via FP-2. The research findings suggested that FP2 inhibition is the remedy for treating malaria. The inhibitors of FP-2 stop Hgb destruction and the parasite development, concluded researchers.

The control of malaria has been hampered due to the rising resistance of parasites toward existing drugs. Hence, there is an urgent need for fresh antimalarial drugs that target new disease sites. In order to overcome this challenge, the researchers closely analyzed the process on how E64 approaches, interacts, and finally inhibits FP-2. The effect of E64 and its derivatives are less harmful among humans and thus making it a prospective drug target for treating malaria.

AI Experts to discover new Drugs with Cutting-edge Techniques

The researchers at Insilico Medicine and Insilico Taiwan are continuously working on finding solutions for the challenges in healthcare. The CEO of Insilico Taiwan further added by saying that they are delighted to work on malaria treatment in help save thousands and millions of human lives. A senior researcher at the Insilico Medicine Taiwan stated that the team of AI engineers applied innovative techniques in drug discovery.

The results have finally confirmed that E64 is responsible for inhibiting FP2 and suggest that the binding of E64 with FP2 is highly favorable.

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