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Finding Order in Disorder


  • Title: Group Leader in Computational Biophysics, Mediterranean Institute for Life Sciences
  • Education: PhD, Stanford University, 2004
  • Recommended by: Vijay Pande

As a grad student who helped Stanford's Vijay Pande develop the [email protected] project, Bojan Zagrovic knows what the current protein modeling tools can and cannot do. And while a lot of progress has been made in the field of computational proteomics, there's still much to be figured out.

As group leader of the computational biophysics lab at the Mediterranean Institute for Life Sciences in Split, Croatia, Zagrovic uses molecular simulations to model the folding and binding dynamics of mainly protein-protein interactions, but also lipids and DNA. "It's 99 percent theoretical," Zagrovic says. After leaving Stanford in 2004, Zagrovic has continued to use and develop the [email protected] distributed computing cluster centered at Pande's lab in order to look at "how dynamics and structure are connected, and related to function."

One of his lab's main areas of interest outside protein folding is the unstructured nature of proteins. Natively unfolded proteins, or "intrinsically unstructured proteins," he says, are common and present a new frontier for computational simulation. "It turns out that almost 30 percent of eukaryotic proteins actually have significant regions [where] there's simply no structure. They do not conform to the 3D structure-equals-function paradigm," he says. "The problem is the standard techniques of structural biology are not capable of describing these molecules."

The limiting factor in his work, of course, is computational power, and in the coming years he hopes to have "better algorithms, faster computers, [and] more sampling." As it stands, processors are capable of rendering only a small fraction of what he needs to see in order to understand many biological processes. "There's two [or] three orders of magnitude — if not more — difference between what we want [to see] and what we can," he says.

Looking ahead

Zagrovic will continue studying what he thinks could become a new paradigm for understanding unfolded protein structure. In the next five years, he hopes to apply computational modeling to solving problems associated with the "entropic component to protein activation," which could have a clinical impact when it comes to finding ideal drug target binding sites. "If you tap into these allosteric effects, could you actually affect the function of an enzyme by creating something that would bind somewhere else," he says, "not necessarily in the active site, but still have effect in the active site?"

Publications of note

In 2005, Zagrovic published a paper in PNAS that explored the conformation of unfolded polypeptides. In the study, he combined wet lab work and molecular modeling using the [email protected] cluster and found that the structure of unfolded proteins does reside in the previously described configuration, a polyproline type II helix, "but that it is much, much more compact than previously thought," Zagrovic says. "In other words, what we have shown is that locally the chain is PPII, but when it comes to its long-range structure it is still a compact random coil." It was one of the largest simulations to date — the team employed seven different commonly used models, or force fields, to simulate the polypeptide configurations.

And the Nobel goes to …

If Zagrovic were to win the Nobel prize, he would hope to get it "for proving that proteins and biomolecules, in general, are more much flexible than we think," he says. "The way we picture things right now is quite ordered still; our logic is still very much mechanistic. But I have this feeling that things are much more fuzzy, things are much more fluctuant, things are much more crazy than we think."

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