Studies Prove that Viewing Angle Influences Microscopic Research

Viewing Angle

According to Salk scientists, tilting the frozen protein sample under an electron microscope provides a better viewing angle. This provides effective approach for better information deduction during the research. Which further helps understand the structure of proteins and host diseases such as HIV and cancer. The new study in September 13th, issue of the Progress in Biophysics and Molecular Biology. It provides quantitative proof that the angle of sight can significantly influence the result of 3D structures of proteins. The study can also help in determining an optimal setup for further experiments.

As per Dmitry Lyumkis, an assistant Professor at Salk University, the study offers a quantitative understanding of why angle of sight affects the results of 3D modeling of protein structure. Additionally, it shows that the angle also improves the quality of the 3D structures and enables the researchers to extract better information to improve their data. He also states that similar theoretical frameworks are crucial to understanding how information attenuates because of imperfections related to imaging researches. This study shall eventually provide better structural information from cryo-EM data, says the professor.

What Stimulated Researchers to Focus on Viewing Angle during Experiment?

It is obvious fact that in cryo-EM, the samples are frozen rapidly before bombardment with an electron beam. Post bombardment, the scattering of electrons helps understand the structure of protein or protein complex. This has been the best and most effective way to develop a 3D structure of the protein sample. However, this process has a long-standing problem that caused an anomaly in the structure due to the imperfection on the grid they are prepared on. Consequently, researchers were unable to develop a symmetric structure that was visible from every angle.

Dmitry states that tilting the samples can solve the problem but, his team was unaware that up to what extent the sample must be tilted to get optimal results. This issue got its solution by the introduction of the sampling compensation factor or SCF into the equation. The closer the SCF value to 1, the symmetric the model is. The calculation of SCF lets the researchers determine the tilting angle prior to the experiment and optimize the results.

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