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Artificial Intelligence (AI) Can Help in Finding New Drugs That Are Inspired by Nature
The researchers at ETH Zurich have demonstrated that AI can identify the biological activity of natural products in a targeted manner. AI helps in finding molecules having the same effect as a natural substance, but which are easier to manufacture. This does open up large possibilities of drug discovery that have the potential to rewrite the rulebook of pharmaceutical research.
Researchers at ETH are paving the way for major medical advancement. They currently have around 4000 different medicines in all. And the estimates of the number of human proteins go up to 400,000, where each of them could be a target for a drug.
The ETH chemists tested their concept with marinopyrrole A. It is a bacterial molecule known to have antibiotic, anti-inflammatory, and anti-cancer properties. Although, there was limited research on which proteins in the human body the natural substance interacts with to produce these effects.
Marinopyrrole A (like many other natural substances) has a relatively complicated structure, making laboratory synthesis time-consuming and expensive. In order to ensure that the findings of the target proteins of marinopyrrole A result in a useful treatment in the future, finding a molecule that is easy to manufacture was necessary.
The software had access to a catalog with around 200 starting materials, 25,000 purchasable chemical building blocks, and 58 established reaction schemes.
After every reaction step, the starting material that was selected by the program for the next step matched the variants of marinopyrrole A most closely in terms of functionalities.
Overall the algorithm found 802 suitable molecules, based on 334 different scaffolds. The researchers synthesized the best four in the laboratory and discovered that they actually behaved very similarly to the natural model. They had a comparable effect on seven of the eight target proteins identified by the algorithm.
Followed by this, the researchers investigated the most promising molecule in detail. X-ray structure analyses showed that the computer-generated compound binds to the active center of a target protein in much the same way as known inhibitors of this enzyme. Despite its different structure, then, the molecule found by AI works using the same mechanism.
Based on the ETH group’s research methods, we can find drugs that do the same work as existing drugs based on different structures. This can make it easier in the future to design new unpatented molecular structures.
To conclude, the Pharmaceutical industry will have to adapt to a rulebook for its research.
This article is a summary of an article published on WEF. Click here to read more.
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