Local changes, global effects: Unpacking action at a distance using computers, X-rays and classic biochemistry
Local changes, global effects: Unpacking action at a distance using computers, X-rays and classic biochemistry

When I entered Assistant Professor Vatsan Raman’s office to talk about his group’s latest research study, I didn’t expect that our conversation about proteins would turn toward Rube Goldberg machines.

Biochemists like Raman study how nature functions at molecular and sub-molecular scales and in doing so observe a myriad of biological phenomena. One such phenomenon, allostery, is critical for protein function. But, what is allostery?

Enter the Rube Goldberg machine.

“Allostery is like a Rube Goldberg machine. You poke something in one place and that has an impact elsewhere,” said Raman. “Most of us have seen a Rube Goldberg machine in real life or on TV. If you move a lever at one end, the lever rolls a ball, the balls falls into a balance, the balance tips something over, and so on and so forth until some action happens at the other end, far from the origin.

Assistant Professor Vatsan Raman.
Assistant Professor Vatsan Raman. 
 

Imagine instead of a Rube Goldberg machine, a protein. When a protein is perturbed at one end, say by binding to another molecule, that perturbation travels through a network of amino acids resulting in action at another end. This is allostery.

Allosteric proteins play critical roles in signal transduction, metabolism, gene regulation and other cellular functions. Nearly half of all protein drug targets are allosteric proteins; yet, how allostery works remains a mystery. A comprehensive picture of allostery might help scientists develop more sensitive biosensors and effective pharmaceuticals.

Raman’s group is making headway in uncovering the mysteries of allostery. Last year, they demonstrated that when allosteric communication is interrupted by a mutation, protein function can be restored by another mutation. In their Nature Communications paper released this month, Raman, Integrated Program in Biochemistry graduate student Kyle Nishikawa, and their team describe how allosteric proteins evolve by reconstructing their evolutionary pathways in the laboratory. By incorporating mutations one at a time, they showed that not all mutations are additive – in fact, the non-additive mutations play a critical role in the evolution of allosteric proteins.

Unraveling the mysteries of allostery

IPiB graduate student Kyle Nishikawa.
IPiB graduate student 
Kyle Nishikawa.
 
 

A protein evolves by picking up changes in amino acid sequences known as mutations. In the ideal case, each mutation helps a protein move from its original function to a new function. In real life though, the evolutionary pathway is full of peaks and valleys, and not all mutations are helpful. Some mutations even make it impossible for a protein to evolve.

Still, there are often hundreds of thousands of possible mutations. Figuring out just how many – and which – combinations of these mutations can lead a protein to gain a new function requires the work of powerful computers.

Raman’s research group harnessed the computational resources and power of the Center for High Throughput Computing at UW-Madison to identify which sets of mutations allowed one protein to go from its old function to a new one. High-throughput screening allowed them to test thousands of different mutations and possible pathways without creating and testing each one in the lab. After identifying which mutations led to the desired change in function of a protein, Raman's group created and studied with old-school biochemistry experiments only those combinations of mutations that led to the new function.

There was still a piece of the puzzle missing – what did the protein look like with its new function? How did its configuration, its relationship in space, to other biomolecules change?

To investigate, Raman’s research group used technologies available through the Collaborative Crystallography Core at UW-Madison and the Advanced Photon Source at the Department of Energy’s Argonne National Laboratory.

X-ray crystallography, one of the most frequently used experimental approaches to study allostery, provides snapshots of proteins before and after they are perturbed by specific mutations. With X-ray crystallography, proteins are bombarded by photons to create diffraction maps that illuminate how the proteins look. Then, these maps are turned into three-dimensional structures that scientists can analyze.

“The crystal structure [in our study] showed something quite remarkable. The ligand molecule had rotated from a vertical to a horizontal orientation, which is a fairly large change. Yet, allosteric signaling worked both in the old and new orientations. This is evidence that many possible solutions exist that enable allosteric signaling,” Raman said.

Allosteric proteins not unlike the one Raman’s group studied can be used as biosensors to measure a wide range of chemicals from environmental contaminants to human wellness indicators.

“Understanding the evolutionary landscape is really useful for designing allosteric biosensors with real-world applications. What makes protein design really challenging is mutations don’t always “add up” – you have to look at how multiple mutations play together and assess their impact on not just one protein property, but several properties at the same time. Through this work, we are beginning to answer some of these questions about allostery.”

Story written by Catherine Steffel, Ph.D. Read the open-access research article here. This research was supported by the U.S. Army Research Office. Nishikawa was supported by an NIH NRSA T32 award and the Robert and Katherine Burns Biochemistry Fund. This work was performed using resources from the UW-Madison Center for High Throughput Computing and Argonne National Laboratory’s Advanced Photon Source. Access to the Advanced Photon Source is provided through the Life Sciences Collaborative Access Team. Direct questions and media inquiries to communications@biochem.wisc.edu. Photos: Robin Davies.