HomeScienceGeneticsResearch: AI tailors artificial DNA for future drug development

Research: AI tailors artificial DNA for future drug development

Using AI, researchers at Chalmers University of Technology, Sweden, have succeeded in designing synthetic DNA that controls the cells’ protein production. The technology can contribute much faster and at significantly lower costs to the development and production of vaccines, medicines for serious diseases and alternative dietary proteins. How our genes are expressed is a process fundamental to the functionality of cells in all living organisms. Simply put, the genetic code in DNA is transcribed into the molecule messenger RNA (mRNA), which tells the cell factory what protein to produce and in what amounts.

Researchers have put a lot of effort into trying to control gene expression because it can contribute to the development of protein-based drugs, among other things. A recent example is the mRNA vaccine against Covid-19, which instructed the body’s cells to produce the same protein as on the surface of the coronavirus. The body’s immune system could then learn to form antibodies against the virus. Likewise, it is possible to teach the body’s immune system to defeat cancer cells or other complex diseases if one understands the genetic code behind the production of specific proteins. Most of today’s new drugs are based on proteins, but the techniques to produce them are both expensive and slow because it is difficult to control how the DNA is expressed. Last year, a research group at Chalmers, led by Aleksej Zelezniak, associate professor of systems biology, took an important step in understanding and controlling how much of a protein is made from a given DNA sequence.

“First it was about being able to ‘read’ the instructions of the DNA molecule completely. Now we have succeeded in designing our own DNA that contains the exact instructions to control the amount of a specific protein,” says Aleksej Zelezniak about the latest major breakthrough. The principle behind the new method is similar to when an AI generates faces that look like real people. By learning what a large selection of faces look like, the AI ​​can then create completely new, yet natural-looking faces. It’s then easy to adjust a face by saying, for example, that it should look older, or have a different haircut. On the other hand, programming a believable face from scratch, without the use of AI, would have been much more difficult and time consuming. Similarly, the researchers’ AI has been taught the structure and regulatory code of DNA. The AI ​​then designs synthetic DNA where it is easy to alter the regulatory information in the desired direction of gene expression. Simply put, the AI ​​is told how much of a gene is desired and then ‘prints’ the correct DNA sequence.

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“DNA is an incredibly long and complex molecule. So it is extremely challenging experimentally to make changes to it by repeatedly reading and changing it, and then reading and changing it again. This way it takes years of research to find something that works. Instead, it is much more effective to let an AI learn the principles of navigating DNA. What would otherwise take years is now shortened to weeks or days,” says first author Jan Zrimec , a research associate at the National Institute of Biology in Slovenia and former postdoctoral fellow in Aleksej Zelezniak’s group. The researchers developed their method in the yeast Saccharomyces cerevisiae, whose cells resemble mammalian cells. The next step is the use of human cells. The researchers hope that their progress will have an impact on the development of both new and existing drugs.

“Protein-based drugs for complex diseases or alternative sustainable dietary proteins can take many years and can be extremely expensive to develop. Some are so expensive that it is impossible to achieve a return on investment, making them economically unviable With our technology it is impossible to develop and produce proteins much more efficiently so that they can be marketed,” says Aleksej Zelezniak. (ANI)

(This story has not been edited by Devdiscourse staff and is automatically generated from a syndicated feed.)



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