Solid-state NMR moves toward atomic-scale resolution of proteins

4th March 2013

By combining custom-built spectrometres, novel probe designs and faster pulse sequences, a team led by Illinois chemistry professor Chad Rienstra has developed unique capabilities for probing protein chemistry and structure through the use of solid-state nuclear magnetic resonance spectroscopy. The researchers' recent results represent significant progress toward atomic-scale resolution of protein structure by solid-state NMR spectroscopy. The technique can be applied to a large range of membrane proteins and fibrils, which, because they are not water-soluble, are often not amenable to more conventional solution NMR spectroscopy or X-ray crystallography.

Scientist Live spoke with Dr. Rienstra about his research and its implications.

How did you come to work on this project?

This is a continuation of a quest of mine from my graduate studies at MIT with Robert Griffin at the Francis Bitter Magnet Laboratory and with Ann McDermott at Columbia University. The goal of this work has been to solve high resolution structures of proteins by solid state nuclear magnetic resonance (NMR). The motivation of my research is to allow the examination of many types of proteins that cannot be crystallised and cannot be studied in solution. This includes many important proteins for human medicine. I also found these problems in NMR to be fascinating problems in physics and engineering.

Can you describe what current methods for analysing protein structure are and what their shortcomings are?

The Protein Data Bank ( tracks the number of structures solved of all types of biomolecule (not just proteins as the name implies but also nucleic acids, but most are proteins). The vast majority of the proteins have been solved by x-ray crystallography using, in most cases, high energy synchrotron sources; the key to solving a crystal structure is growing a crystal. That is relatively straight forward to do nowadays for most soluble proteins. For membrane proteins, it is exceedingly difficult. Only a couple of hundred out of the 50,000 total structures in the PDB are membrane proteins and for proteins involved in neurodegeneration, so called amyloid proteins, they essentially cannot be studied by these methods. Solution NMR is the other major competitor for x-ray crystallography. More than 5,000 protein structures have been solved that way. It is a powerful tool for addressing soluble proteins with the molecular weight of less than 20,000 Daltons or so. In some instances it has been applied to larger proteins. But the limitation is that one must find the conditions where the protein is soluble in aqueous buffer. To study membrane proteins by solution NMR requires solublisation in detergents and this is often an impediment to finding good sample conditions. So in solid state NMR we can avoid a lot of those complications because we don't need the sample to be soluble in order to crystallise it or to study it in solution NMR where it also has to be soluble. So solid state NMR is uniquely able to address those types of proteins that are not soluble and do not form crystals.

Tell us about the solid state NMR developed in your lab and how it works.

First of all, we prepare the protein using 13C and 15N growth media. We prepare them from bacterial expressions vectors in E. coli and that enriches the 13C and 15N nuclei in the protein to improve the sensitivity of the spectra. Then we perform magic angle spinning which is a technique to improve the resolution of the spectra. Essentially what magic angle spinning does is it gives high resolution spectra despite the fact that the sample was not tumbling in aqueous solution. Normally, in solution NMR, the molecule must tumble rapidly in the magnetic field in order to give high resolution spectra. With magic angle sinning we can avoid that requirement. Rather than relying on the tumbling of the molecule in solution, we essentially perform that averaging process for the molecule by rotating the sample very rapidly within the magnetic field.

Are there any other applications for this?


Listen to Dr. Rienstra discuss other applications for solid-state nuclear magnetic resonance by clicking the audio link at the end of this article.

You developed a way of measuring the distance and angles between atoms within a molecule. Can you explain how you accomplished this?

We have integrated ideas from several previous investigators and extended them further and taken them to the logical extreme so that they work well for protein studies. It has also required advances in the instrumentation so that the quality of the data obtained can be satisfactory, as well as in the data analysis protocol which because of the shear volume of data we had to write a whole serious of analysis software in order to interpret the data sets. So it is a culmination of ideas and contributions from a number of investigators early on and team efforts within my own group over the last several years.

One example is the measurement of vector angles, which is the principle methodological advance of ours that we have recently demonstrated in our Proceedings of the National Academy of Sciences (PNAS) paper. Essentially what we have done is measure the orientation of pairs of atoms relative to other pairs of atoms, through a quantity called the dipolar coupling. Imagine that in a molecule each pair of atoms represents a bar magnet, and the atoms can "feel" the direction of the other magnets nearby. This allows us to piece together the detailed structure of a molecule, like fitting pieces into a puzzle, until the orientations all agree with the experimentally determined data. It is a really complicated puzzle, but with computational algorithms it can be solved very precisely and accurately.

What is next for your laboratory?

We have demonstrated this idea in the paper published in PNAS this year and shows that we can solve very high resolution structures of small proteins and now we are trying to extend that to larger proteins as well as proteins specifically involved in human disease. For example, alpha-synuclein is implicated in Parkinson's disease and we're working hard to extend the ideas we have developed with our model protein in order to solve the structure of alpha-synuclein. In general, these proteins are not accessible to other techniques so the structural information will be very valuable for the design of drugs... Most of our future projects are much more directed at human diseases and we hope that the structural data will have a positive impact on human medicine.

Reporting by Marc Landas





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