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Unlocking the secrets of protein mimics

“Our lab is developing computational methods that will rely on experimental and evolutionary data to determine structural information about protein complexes,” said Dmitry Korkin, a University of Missouri assistant professor of computer science, and a faculty member of he MU Informatics Institute.

He explained that evolutionary data is novel data that, with the recent advancements in computational methods, has become vastly available to scientists. Experimental data is just that—sometimes it is insufficient, and sometimes it may be inaccurate. But data from a variety of sources increases the odds of a good result.

Korkin is collaborating with Melissa Mitchum, an assistant professor in life sciences, on her research investigating the infection of plants by nematodes, roundworms found in the soil.

Invasion and survival of pathogens in animals, plants and humans—whether the pathogens are viruses, bacteria, or multi-cellular parasites—involve vast numbers of protein interactions, Korkin said.

“We are trying to detect nematode proteins that interact with plant proteins, and to characterize the ones that are critical for this nematode infection. It would allow us to generate a biological hypothesis that can be tested in Dr. Mitchum’s lab.”

Pathogens are in desperate need to penetrate the host’s defense system and must secrete proteins that will interact with the host proteins, altering the host’s function. For the host organisms, explained Korkin, the evolutionary rate of modifications within their proteins is slow.

“With a pathogen, it’s much faster, which is a very cool advantage because it can compete with its host,” said Korkin. “Pathogens invent the need for their proteins to perform the same function as structurally unrelated host proteins, altering themselves to do so. Once the protein interaction corresponding to a host function has been detected by a microbe, it can alter its proteins radically, mimicking one of the host’s interaction partners.”

Experimental data has identified individual residues used in these interactions. Amazingly, these residues can be superimposed in the same positions in a protein structure with the same properties even though the proteins are often totally unrelated.

“Detecting binding sites of pathogenic proteins is a difficult task. You often need to know the right structure of the lock, a host protein, to know the right structure of the key, or pathogen protein,” Korkin continued.

“If we are able to predict the mimicking microbial proteins—and to detect the residues that are important for their interactions with the host proteins—this information can enable experimental scientists to design drugs that block these residues,” said Korkin.

Korkin explained that he and collaborators Andrej Sali, Carol Gross and Elizabeth Blackburn at the University of California-San Francisco, Wah Chiu from Baylor College of Medicine, and Judith Frydman from Stanford are working to refine their methods.

“There are a lot of exciting discoveries to be made, and I am fortunate to have these collaborations.”

“Interdisciplinary research is a big advantage, and it distinguishes our program from other bioinformatics programs. Our ultimate goal is to discover the insights of a living cell on an atomic level to help experimental biologists study the structure, function and evolution of life.”

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