Nanobots. If you’re familiar with Michael Crichton’s novel, Prey, you may have a decidedly gloomy outlook on nanoscale robotics. If you’re familiar with K. Eric Drexler’s book, Engines of Creation, you might imagine what possibilities nanoscale machines could bring (gray goo aside). In order to control nanomachines, you have to understand them. That’s where researchers at Los Alamos National Lab (LANL) are starting.
Atomic scale autonomous processing is not just the stuff of science fiction. In fact, it’s not new at all. Biological processes are driven by nanoscale processes and are exceptionally complex and amazingly robust. Many of these processes are driven by proteins, so getting structural information on those proteins is vital in controlling these “molecular machines."
As described in a LANL news report, researchers there are part of a collaborative effort to probe the complex working of proteins using X-ray diffraction. To study the structure, first the protein has to be synthesized in large quantities, and then it is dissolved in water and allowed to crystallize.
X-ray diffraction reveals nano- and microscale structural information, such as atomic spacing, as well as compositional information based on unique diffraction signatures for individual elements and compounds. X-ray, then is well-suited to help reveal protein structure, but it can be difficult to separate out all the information in materials like proteins with complex structures.
The thousands of diffraction spots created are dissected using Phenix, powerful software co-developed by scientists at Los Alamos, Lawrence Berkeley National Laboratory, and Duke and Cambridge universities. Phenix, which is short for Python-based Hierarchical ENvironment for Integrated Xtallography, is capable of producing data on the 3-D structure of molecules.
The LANL team recently streamlined the analysis process by eliminating the middle-man, so to speak. The software looks for diffraction caused by metal atoms first, as they respond quite differently than carbon, nitrogen, hydrogen or oxygen that typically comprise a protein. This necessitated the artificial incorporation of metals into many proteins where they do not naturally occur so that analysis could be completed.
By applying improved statistical methods, the updated analysis can identify atoms which do not differ greatly from “typical” elements in the structure. For example, sulfur can now be identified and is part of many proteins. This allows for many more unaltered proteins to now be analyzed.
One example of the success of Phenix is the 3-D analysis of Cascade, reported in Science last summer. Cascade is the name given to a very large molecular machine in bacteria that is made up of 11 proteins and an RNA molecule and works to identify foreign DNA and avoid infection. Cascade is reported to be shaped much like a seahorse.
Understanding the structures of molecular machines is expected to advance medicine into new frontiers such as the treatment of genetic disorders. Not all nanoscale machines can be cast in a sci-fi thriller, but it seems there can still be a happy ending.
Image: Los Alamos National Laboratory