Computational Biology, Genetics
The University of Texas Southwestern Medical Center
Dr. Grishin is also a professor of biophyscis and of biochemistry at the University of Texas Southwestern Medical Center.
Computational Biology of Proteins
Nick Grishin suspects some scientists might find his laboratory at the University of Texas (UT) Southwestern Medical Center a disappointment at first glance. It looks like an office. Instead of lab benches crowded with glassware, microscopes, and mysterious bottles, the Grishin lab has cubicles. True, the desks are crowded with computer monitors—Grishin's lab members like to run two or three at a time.
This is a bioinformatics lab, a number-crunching "dry" lab that performs all its research "in silico"—that is, using computer algorithms to find the patterns and connections in data from conventional "wet" labs with test tubes and model organisms. No other approach, says Grishin, could hope to dent the great problem that his lab pursues—how is biological diversity generated at the protein level, and what are the rules that govern the evolution of proteins? Nature has already performed a vast experiment with proteins in the course of evolution and thus careful analysis of the data generated by this natural experiment is very fruitful, he explains.
Life on Earth runs on proteins. Grishin estimates that living things today have a repertoire of ancestral proteins. Currently, researchers have determined amino acid sequences for about 7 million proteins. This primary molecular structure is thought to dictate the molecular shape or fold of a protein. In humans, how a protein folds has a lot to do with what a protein does to keep us healthy or make us sick, as proteins function as three-dimensional (3D) objects, not as linear sequences.
Unfortunately, we do not understand how to deduce this 3D structure from sequence, Grishin explains. Currently we've experimentally determined the 3D structure of about 50,000 proteins. That means we've barely scratched the surface of the protein world. Understanding the folding patterns of proteins would give us important insights into their evolution as well as powerful new tools for biomedicine. Devising new methods to predict and compare 3D protein structure is what's reflected in all those monitors in the Grishin lab.
The real action takes place in the lab's meeting room. "We come together every day and 'fight' with each other," laughs Grishin. "We like opinionated people, and we like independent people." These intellectual wrestling matches are integral to bioinformatics, he says. "This kind of science stems from discussion. It's very hard to come up with (scientific) ideas today if you are a loner. Science is truly a group activity now."
Grishin's lab team draws researchers from many disciplines—biologists, physicists, mathematicians, and computer programmers. They are debating ways to model the protein world that are detailed enough to yield good predictions yet not so unwieldy that they bog down in minutiae. An example of Grishin's protein-searching approach was the collaborative work published in 2008 with Michael Brown and Joseph Goldstein, UT Southwestern's resident Nobel laureates and longtime collaborators. Goldstein told Grishin that they needed to identify the enzyme that modifies ghrelin, an appetite-stimulating peptide hormone released by a food-deprived stomach and pancreas, and suggested looking for candidates among a certain family of transmembrane proteins. Ghrelin was apparently activated by an unknown transferase that added a molecular tag derived from octanoic acid. Thus began the search for a suitable "ghrelin O-acyltransferase" or GOAT.
Grishin's algorithms identified a16-member family of transferases that seemed to fill the GOAT bill. If Grishin's short list worked, it would save hundreds of lab days attempting to experimentally find the single right gene among many thousands. "You really have to believe in this approach," Grishin explains, "and keep on testing because our methods are just predictive, and by no means 100 percent accurate." Goldstein's lab cloned the first candidate and it flunked the ghrelin activation test. They cloned the second and it failed. And so on until number 15 failed. "This was getting embarrassing," Grishin recalls. "But fortunately Jing Yang, a graduate student working with Brown and Goldstein had the guts to keep going and test number 16, and that was the one."
GOAT is more than a funny name. Since the discovery of ghrelin in 1999, pharmaceutical companies have unsuccessfully pursued a ghrelin antagonist as an anti-obesity drug. Ghrelin itself may be too difficult to manipulate, but GOAT is a new target and a more precise one. Grishin thinks that this is just the beginning of protein bioinformatics as a shortcut for drug and clinical research.
Grishin's road to protein bioinformatics began in the old Soviet Union. His father is a mathematician, a skill and an interest that he passed on to his son, but Nick Grishin was equally fascinated by the natural world. "My grandmother told me that when I was two or three years old, I would stand for hours beside the ant hill and watch the ants," Grishin recalls.
In the end, Grishin was drawn to protein biochemistry at Moscow State University (MSU). His co-mentor at MSU, Andrei Osterman, left for UT Southwestern before Grishin could finish his "Diplom," the Russian equivalent of a master's rolled in with a bachelor of science. "He left me hanging," Grishin recalls, "but he promised to get me over [to the United States] as soon as I defended my thesis. And he did." Grishin defended in August 1993. In September, he was on his way to Dallas to begin his doctoral work in the lab of enzymologist Margaret Phillips.
Grishin's Ph.D. thesis combined protein structure prediction with x-ray crystallography and conventional protein biochemistry techniques, but the emerging field of bioinformatics intrigued him more and more. His interests were cemented by a postgraduate research fellowship with one of the pioneers of computational biology, Eugene Koonin, at the National Institutes of Health's National Center for Biotechnology Information. In 1999, Grishin jumped at the chance to return to UT Southwestern and set up his own bioinformatics group.
Grishin loves Texas. He loves it for its sheer size, for its ecology, and for its supporting his childhood interest in bugs. Instead of ants, he pursues giant skippers, members of a butterfly subfamily called the Megathyminae, which can be described as either graceful moths or ugly butterflies. Their various species are found wherever yuccas or agaves grow, which is just about everywhere in Texas. "I think Texas is the best state in the U.S. because it is so diverse naturally, from eastern forests to western deserts with mountains, and reaching for the tropics in the south," Grishin declares. Hunts for giant skippers have carried him to every corner. "One of the great benefits of looking for insects is that when I go out collecting, I can clear my mind and gear up for new attacks on protein problems."