The trans-activation domain of the sporulation response regulator Spo0A revealed by X-ray crystallography

Sporulation in Bacillus involves the induction of scores of genes in a temporally and spatially co-ordinated programme of cell development. Its initiation is under the control of an expanded two-component signal transduction system termed a phosphorelay. The master control element in the decision to sporulate is the response regulator, Spo0A, which comprises a receiver or phosphoacceptor domain and an effector or transcription activation domain. The receiver domain of Spo0A shares sequence similarity with numerous response regulators, and its structure has been determined in phosphorylated and unphosphorylated forms. However, the effector domain (C-Spo0A) has no detectable sequence similarity to any other protein, and this lack of structural information is an obstacle to understanding how DNA binding and transcription activation are controlled by phosphorylation in Spo0A. Here, we report the crystal structure of C-Spo0A from Bacillus stearothermophilus revealing a single alpha -helical domain comprising six alpha -helices in an unprecedented fold. The structure contains a helix-turn-helix as part of a three alpha -helical bundle reminiscent of the catabolite gene activator protein (CAP), suggesting a mechanism for DNA binding. The residues implicated in forming the sigma (A)-activating region clearly cluster in a flexible segment of the polypeptide on the opposite side of the structure from that predicted to interact with DNA. The structural results are discussed in the context of the rich array of existing mutational data

Automated Structure Solution with the PHENIX Suite

Significant time and effort are often required to solve and complete a macromolecular crystal structure. The development of automated computational methods for the analysis, solution and completion of crystallographic structures has the potential to produce minimally biased models in a short time without the need for manual intervention. The PHENIX software suite is a highly automated system for macromolecular structure determination that can rapidly arrive at an initial partial model of a structure without significant human intervention, given moderate resolution and good quality data. This achievement has been made possible by the development of new algorithms for structure determination, maximum-likelihood molecular replacement (PHASER), heavy-atom search (HySS), template and pattern-based automated model-building (RESOLVE, TEXTAL), automated macromolecular refinement (phenix.refine), and iterative model-building, density modification and refinement that can operate at moderate resolution (RESOLVE, AutoBuild). These algorithms are based on a highly integrated and comprehensive set of crystallographic libraries that have been built and made available to the community. The algorithms are tightly linked and made easily accessible to users through the PHENIX Wizards and the PHENIX GUI

Iterative build OMIT maps: Map improvement by iterative model-building and refinement without model bias

A procedure for carrying out iterative model-building, density modification and refinement is presented in which the density in an OMIT region is essentially unbiased by an atomic model. Density from a set of overlapping OMIT regions can be combined to create a composite 'Iterative-Build' OMIT map that is everywhere unbiased by an atomic model but also everywhere benefiting from the model-based information present elsewhere in the unit cell. The procedure may have applications in the validation of specific features in atomic models as well as in overall model validation. The procedure is demonstrated with a molecular replacement structure and with an experimentally-phased structure, and a variation on the method is demonstrated by removing model bias from a structure from the Protein Data Bank

Structural Genomics of Minimal Organisms: Pipeline and Results

The initial objective of the Berkeley Structural Genomics Center was to obtain a near complete three-dimensional (3D) structural information of all soluble proteins of two minimal organisms, closely related pathogens Mycoplasma genitalium and M. pneumoniae. The former has fewer than 500 genes and the latter has fewer than 700 genes. A semiautomated structural genomics pipeline was set up from target selection, cloning, expression, purification, and ultimately structural determination. At the time of this writing, structural information of more than 93percent of all soluble proteins of M. genitalium is avail able. This chapter summarizes the approaches taken by the authors' center

Protein crystallography: From X-ray diffraction spots to a three dimensional image

Proteins are remarkable molecular machines that are essential for life. They can do many things ranging from the precise control of blood clotting to synthesizing complex organic compounds. Pictures of protein molecules are in high demand in biotechnology because they are important for applications such as drug discovery and for engineering enzymes for commercial use. X-ray crystallography is the most common method for determining the three-dimensional structures of protein molecules. When a crystal of a protein is placed in an X-ray beam, scattering of X-rays off the ordered molecules produces a diffraction pattern that can be measured on a position-sensitive CCD or image-plate detector. Protein crystals typically contain thousands of atoms and the diffraction data are generally measured to relatively low resolution. Consequently the direct methods approaches generally cannot be applied. Instead, if the crystal is modified by adding metal atoms at specific sites or by tuning the wavelength of the X-rays to cross an absorption edge of a metal atom in the crystal, then the information from these additional measurements is sufficient to first identify the /locations of the metal atoms. This information is then used along with the diffraction data to make a three-dimensional picture of electron densities. This picture can be used to determine the position of most or all of the atoms in the protein

Modeling Structural Heterogeneity in Proteins From X-Ray Data

Abstract: In a crystallographic experiment, a protein is precipitated to obtain a crystalline sample (crystal) containing many copies of the molecule. An electron density map (edm) is calculated from diffraction images obtained from focusing X-rays through the sample at different angles. This involves iterative phase determination and density calculation. The protein conformation is modeled by placing the atoms in 3-D space to best match the electron density. In practice, the copies of a protein in a crystal are not exactly in the same conformation. Consequently the obtained edm, which corresponds to the cumulative distribution of atomic positions over all conformations, is blurred. Existing modeling methods compute an “average ” protein conformation by maximizing its fit with the edm and explain structural heterogeneity in the crystal with a harmonic distribution of the position of each atom. However, proteins undergo coordinated conformational variations leading to substantial correlated changes in atomic positions. These variations are biologically important. This paper presents a sample-select approach to model structural heterogeneity by computing an ensemble of conformations (along with occupancies) that, collectively, provide a near-optimal explanation of the edm. The focus is on deformable protein fragments, mainly loops and side-chains. Tests were successfully conducted on simulated and experimental edms.