University at Buffalo, Buffalo, NY
A new method of X-ray scanning will allow for the visualization of many more biological molecules, providing critical information about what is inside molecules to scientists who currently can only access their outer shape or envelope. Such information could be a major boost to studies of viruses, for example.
With existing techniques, you can only see the outline of the virus, but this method allows us to see inside the virus molecule to understand how the genetic information is arranged, potentially giving new insight into how the virus injects this genetic information into its host.”
The method has solved the phase problem for a particular molecular determination technique called solution scattering. The phase problem is where critical information about the phase of a molecule is lost during the experimental process of making a physical measurement.
Most molecular structures today are solved using X-ray crystallography, where the structures scatter intense X-rays in patterns consisting of hundreds of thousands of unique pieces of information, which are used to ultimately reveal the structure at high-resolution.
The problem is that more than 75% of molecular structures do not readily form ordered crystals that diffract well. That means many molecules are difficult to visualize in three dimensions.
Biological molecules can exhibit dynamic motions that have an impact on how they function, but those motions are missing when structures crystallize, resulting in the loss of important biological information.
One way around this obstacle is to use a technique called solution scattering in which X-rays scatter off of molecules floating in solution instead of arranged in a crystal. Solution scattering allows the molecules to move dynamically in their natural states, enabling the visualization of large-scale conformational dynamics important for biological function. However, as the molecules tumble in solution, they scatter the X-rays in many different orientations, losing most of the information, typically yielding only 10 to 20 unique pieces of data. Until now, such little information only yielded low-resolution outlines of the particle shapes.
The researchers developed an algorithm that enables reconstructing the three-dimensional electron density of a molecule, similar to a 3-D reconstruction of the brain produced by a CT scan. However, this algorithm uses only the one-dimensional data from solution scattering experiments. It enables seeing the internal density variations of the molecules instead of only the envelope of the particle shape in order to better understand the molecular structures in solution.
The new method is based on the well-known mathematical technique called iterative phase retrieval, which is a computational technique that provides a way to solve the phase problem. The phase problem is akin to having a camera that accurately records all the intensities of each pixel, but scrambles where those pixels are, based on a complex mathematical equation. So, you’re left with a useless image of scrambled pixels.
Scientists have typically worked to decode that mathematical equation by changing the image a little bit to make sure it looks approximately as they expect. For example, in a landscape photo, the blue pixels depicting the sky should naturally be at the top. Solving the phase problem is like decoding the equation and being able to place all the pixels where they’re supposed to be, reconstructing the original image.
However, this process changes some of the intensities, so you correct them based on the original scrambled image. This method cycles through the process iteratively, gradually improving the phases with each cycle, ultimately retrieving the final phases, solving the phase problem and reconstructing the desired image.
This allows scientists to reconstruct not only the three- dimensional phases but also the three-dimensional intensities that are lost in solution scattering experiments as the molecules tumble randomly — and all from one-dimensional experimental data.
via NASA Tech Briefs https://www.techbriefs.com
January 8, 2019 at 09:28PM