Drug molecules and biofuels can be produced in factories of living cells where biological enzymes work. Now, researchers at Chalmers University of Technology have developed a computer model that can predict the rate at which enzymes work, allowing them to find the most efficient living factories, as well as study complex diseases.
Enzymes are proteins found in all living cells. Their job is to act as catalysts that increase the rate of specific chemical reactions that take place in cells. Thus, enzymes play a crucial role in the maintenance of life on Earth, and they can be compared to the small factories of nature. They are also used in detergents and for the production of sweeteners, dyes and medicines, among others. The potential applications are almost limitless, but they are hampered by the fact that studying enzymes is expensive and time-consuming.
“Studying every natural enzyme through experiments in the laboratory would be impossible, there are simply too many of them. But with our algorithm, we can predict which enzymes are the most promising just by looking at the sequence of amino acids they are composed of.” says Edward Kerkhoven, a systems biology researcher at Chalmers University of Technology and lead author of the study.
Only the most promising enzymes need testing
The turnover number of an enzyme, or kcat value, describes how fast and efficient an enzyme is and is essential to understanding cell metabolism. In the new study, Chalmers researchers developed a computer model that can quickly calculate the value of kcat. The only information needed is the order of the amino acids that make up the enzyme, something that is often widely available in open databases. After the model makes the first choice, only the most promising enzymes need to be tested in the lab.
Given the number of naturally occurring enzymes, the researchers believe the new calculation model could make a big difference.
“We see many possible biotechnological applications. For example, biofuels can be produced when enzymes break down biomass in a sustainable manufacturing process. the work of the human body,” says Eduard Kerkhoven.
More knowledge about enzyme production
More possible applications – more efficient production of products from natural organisms, rather than industrial processes. One such example is penicillin, extracted from a mold, as well as the cancer drug taxol from yew, and the sweetener stevia. They are usually produced in small quantities by natural organisms.
“The development and production of new natural products can be greatly helped by knowing which enzymes can be used,” says Eduard Kerkhoven.
The calculation model can also indicate changes in the kcat value that occur when enzymes mutate and identify undesirable amino acids that can have a significant impact on enzyme performance. The model can also predict if enzymes produce more than one “product”.
“We can find out if the enzymes have any kind of “side job” activity and produce unwanted metabolites. This is useful in industries where it is often required to produce a single pure product.”
The researchers tested their model using 3 million kcat values to simulate the metabolism of more than 300 yeast species. They created computer models of how fast yeast can grow or produce certain products such as ethanol. Compared to measured pre-existing knowledge, the researchers concluded that models with predicted kcat values can accurately model metabolism.
Materials provided Chalmers University of Technology. Note. Content can be edited for style and length.