"Function follows form" might have been written to describe proteins, as the M. C. Escher-esque folds and twists of nature's workhorse biomolecules enables each to carry out its specific responsibilities. Technology's workhorse for determining protein structures is X-ray protein crystallography, in which a beam of x-rays sent through a crystallized protein is scattered by the protein's atoms, creating a diffraction pattern of dots that can be reconstructed by computer into a 3D model.
While synchrotron radiation facilities, such as Berkeley Lab's Advanced Light Source, have been a boon to the field of protein crystallography, providing increasingly higher resolution structures over increasingly shorter time-spans, the technology is still a challenge. For some molecules, especially large molecular complexes, it is often only possible to obtain low-resolution experimental data, which means models are difficult to make and must be manually refined using computer modeling.
"Refinement of protein and other biomolecular structural models against low-resolution crystallographic data has been limited by the ability of current methods to converge on a structure with realistic geometry," says Paul Adams, a bioengineer with Berkeley Lab's Physical Biosciences Division and leading authority on x-ray crystallography, who, starting in 2000, has been leading the development of a highly successful software program called PHENIX (Python-based Hierarchical ENvironment for Integrated Xtallography) that automates crystallography data analysis.
Now, Adams and a team that included Nathaniel Echols in his research group, and Frank DiMaio with the research group of David Baker at the University of Washington, have developed a new method for refining crystallographic data that combines aspects of PHENIX with aspects of Rosetta, the most widely used software for the prediction and design of the three-dimensional structure of proteins and other large biomolecul
|Contact: Lynn Yarris|
DOE/Lawrence Berkeley National Laboratory