3-D Proteins...

Image Source: Technology Review

Topics: 3-D Objects, Algorithm, Biology, Computer Science, Molecular Biology

TECHNOLOGY REVIEW: One of the great challenges in molecular biology is to determine the three-dimensional structure of large biomolecules such as proteins. But this is a famously difficult and time-consuming task.

The standard technique is x-ray crystallography, which involves analyzing the x-ray diffraction pattern from a crystal of the molecule under investigation. That works well for molecules that form crystals easily.

But many proteins, perhaps most, do not form crystals easily. And even when they do, they often take on unnatural configurations that do not resemble their natural shape.

So finding another reliable way of determining the 3-D structure of large biomolecules would be a huge breakthrough. Today, Marcus Brubaker and a couple of pals at the University of Toronto in Canada say they have found a way to dramatically improve a 3-D imaging technique that has never quite matched the utility of x-ray crystallography.

The new technique is based on an imaging process called electron cryomicroscopy. This begins with a purified solution of the target molecule that is frozen into a thin film just a single molecule thick.

This film is then photographed using a process known as transmission electron microscopy—it is bombarded with electrons and those that pass through are recorded. Essentially, this produces two-dimensional “shadowgrams” of the molecules in the film. Researchers then pick out each shadowgram and use them to work out the three-dimensional structure of the target molecule.

Abstract

Discovering the 3D atomic structure of molecules such as proteins and viruses is a fundamental research problem in biology and medicine. Electron Cryomicroscopy (Cryo-EM) is a promising vision-based technique for structure estimation which attempts to reconstruct 3D structures from 2D images. This paper addresses the challenging problem of 3D reconstruction from 2D Cryo-EM images. A new framework for estimation is introduced which relies on modern stochastic optimization techniques to scale to large datasets. We also introduce a novel technique which reduces the cost of evaluating the objective function during optimization by over five orders or magnitude. The net result is an approach capable of estimating 3D molecular structure from large scale datasets in about a day on a single workstation.

Physics arXiv:
Building Proteins in a Day: Efficient 3D Molecular Reconstruction
Marcus A. Brubaker, Ali Punjani, David J. Fleet