Scientist develops a new method for identifying proteins to build new biological products -
A scientist from University of Toronto has developed a new method to identify the raw materials needed the construction "biologics", a powerful class of drugs that revolutionized the treatment of diseases such as rheumatoid arthritis and certain cancers.
Biologics are a type of drug that results from handling high technology of our own proteins, to more traditional medications opposed constructed from synthetic chemicals. Because of their success to date, scientists are racing to develop new organic products - and now the University of Toronto researcher has developed a way to make this process more powerful
Philip M . Kim, Associate Professor U. Donnelly T cellular and biomolecular research Centre, the simulation of high technology handsets and computer broadband laboratory experiments to create what he hopes is the most effective way to discover proteins that are essential for new biologics. His research was published online in the journal Science Advances on 20 July, 2016.
"Much of the new therapies these days involve modified proteins that lock onto a drug target eg on a cancer cell, "said Kim, also of molecular genetics and computer science departments. "Finding a protein that binds efficiently to a target can feel like looking for a needle in a haystack Our method should open new opportunities to find these key proteins - .. And have a major impact on development new biological products "
under the traditional approach to the development of a biological product, researchers identify a protein of interest, then test billions of variants, either randomly generated or from a natural source, in the hope of finding an effective binder But these methods very little control over where and how the protein performs this crucial function on its target -.. an important factor in its effectiveness
Kim and his team took a different approach. They used a computer to simulate the binding process and designed proteins that function to the target. This type of theoretical approach has been in development for several decades, but is still not effective enough. Kim then combined the best of both methods. Instead of randomly create massive libraries of variants, as with the traditional approach, he used computer modeling to generate a smaller repertoire, but cleverly designed variants. Each variant design allows tight control of all its properties, unlike conventional approaches.
"We have shown that this method you binders that are a little stronger than what you get with the conventional approach gives," said Kim. "The much smaller library also solves many technical problems and we can detect new, previously unscreenable, targets. It is a very exciting time for cancer research, and for organic products. "
For Kim, the next step is to produce proteins that are important for certain types of cancer, but have not been filtered before because of the difficulty of producing them.
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