In 2017, Salk scientists said that frozen protein sampling, as it sat under an electron microscope, was an effective approach to better understand its structure and assist researchers in helping people with HIV. Now they have developed a mathematical framework based on these initial observations.
Their new study, published Progress in Biophysics and Molecular Biology September 13, 2019, provides the basis for quantifying how the differences in viewing angles affect the resulting 3-D structure of proteins, and may help other researchers determine the best fit for experiments to improve imaging techniques called cryo-EM.
"It provides a quantitative understanding of why the variations of the viewing angles affect the quality of the 3-D structure resulting from proteins and where we can do better with data," said Dimitri Liumk, assistant professor of genetics and co-author of the new work. "These types of theoretical frameworks are important to understand how information is received, due to the drawbacks of the visualization experiment, which leads us to finally get better structures from the cryo-EM data."
In cryo-EM, or in a cryogenic electron microscope, proteins rapidly freeze in their natural form before being bombarded with electrons. By determining how electrons scatter when they sample, researchers can determine the molecular structure of a protein or protein complex. Compared to other imaging methods, it is easier for scientists to prepare cyto-EM proteins, and this technique can potentially address a wide range of questions in structural biology. However, the long-standing problem in Cryo-M is that the proteins tend to stick to the top or bottom of the sample network on which they are made. This chosen orientation means that researchers do not always see the protein structure from all angles. The sample inclination, Liumkis and his colleagues discovered in 2017, helped to solve this problem.
"We knew that in terms of quality, in some cases, data improvements were refined," says Liumki. "What we didn't know was exactly how structures could affect the angle of vision."
Recently, Philip Baldwin, a senior fellow at Salk and his assistant researcher, was looking at a set of cryo-EM data collected from different angles when he noticed that such variations affected the overall resolution of the protein structure. After some calculations, he realized that the association between the angle of view and resolution was generalized to all cryo-EM experiments.
The new formula allows researchers to calculate any angle for any protein, a number called the selection bias factor or SCF. The closer the SCF value to 1, the more complete the protein structure. If the SCF is 0.5 instead of 1, or the data is incomplete, or the researchers have to collect data twice as long to obtain the same structural resolution. By calculating SCF values before the experiment, scientists can optimize the angle of inclination and data collection.
The new quantitative formulations have also helped Lumk and Baldwin calculate how incomplete the complete Cryo-EM data set is. Previously, they may have avoided the multiplicity of data and realized whether this was a good or bad approach to the protein structure. Now the SCF can say this numerically.
"It's very convenient," says Baldwin. "Basically, this formula will tell you if you have very bad protein regions from which you didn't collect data."
Lumqui and Baldwin hope to evaluate cryo-EM results using a formula that includes simple calculation or part of the code to become the standard and help guide experiments and new approaches to cryo-EM. This will lead to a faster breakthrough in the basic biological sciences and drug development.
The work reflects a growing tendency, both at the Salk Institute and elsewhere, to integrate computing and approaches in biology research.
The angled microscope technique can better detect protein structures
Philip R. Baldwin et al. Uniformity of project distribution reduces resolution in Cryo-EM, Progress in Biophysics and Molecular Biology (2019). DOI: 10.1016 / j.pbiomolbio.2019.09.002
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