A new approach that integrates data collection, data reduction, phasing and model building significantly accelerates the process of structure determination and on average minimizes the number of data sets and synchrotron time required for structure solution. Initial testing of the HKL-3000 system (the beta version was named HKL-2000_ph) with more than 140 novel structure determinations has proven its high value for MAD/SAD experiments. The heuristics for choosing the best computational strategy at different data resolution limits of phasing signal and crystal diffraction are being optimized. The typical end result is an interpretable electrondensity map with a partially built structure and, in some cases, an almost complete refined model. The current development is oriented towards very fast structure solution in order to provide feedback during the diffraction experiment. Work is also proceeding towards improving the quality of phasing calculation and model building.

Serum albumin (SA) is the most abundant plasma protein in mammals. SA is a multifunctional protein with extraordinary ligand binding capacity, making it a transporter molecule for a diverse range of metabolites, drugs, nutrients, metals and other molecules. Due to its ligand binding properties, albumins have wide clinical, pharmaceutical, and biochemical applications. Albumins are also allergenic, and exhibit a high degree of cross-reactivity due to significant sequence and structure similarity of SAs from different organisms. Here we present crystal structures of albumins from cattle (BSA), horse (ESA) and rabbit (RSA) serums. The structural data are correlated with the results of immunological studies of SAs. We also analyze the conservation or divergence of structures and sequences of SAs in the context of their potential allergenicity and cross-reactivity. In addition, we identified a previously uncharacterized ligand binding site in the structure of RSA, and calcium binding sites in the structure of BSA, which is the first serum albumin structure to contain metal ions.

Chromodomains are modules implicated in the recognition of lysine-methylated histone tails and nucleic acids. CHD (for chromo-ATPase/helicase-DNA-binding) proteins regulate ATP-dependent nucleosome assembly and mobilization through their conserved double chromodomains and SWI2/SNF2 helicase/ATPase domain. The Drosophila CHD1 localizes to the interbands and puffs of the polytene chromosomes, which are classic sites of transcriptional activity. Other CHD isoforms (CHD3/4 or Mi-2) are important for nucleosome remodelling in histone deacetylase complexes. Deletion of chromodomains impairs nucleosome binding and remodelling by CHD proteins. Here we describe the structure of the tandem arrangement of the human CHD1 chromodomains, and its interactions with histone tails. Unlike HP1 and Polycomb proteins that use single chromodomains to bind to their respective methylated histone H3 tails, the two chromodomains of CHD1 cooperate to interact with one methylated H3 tail. We show that the human CHD1 double chromodomains target the lysine 4-methylated histone H3 tail (H3K4me), a hallmark of active chromatin. Methylammonium recognition involves two aromatic residues, not the three-residue aromatic cage used by chromodomains of HP1 and Polycomb proteins. Furthermore, unique inserts within chromodomain 1 of CHD1 block the expected site of H3 tail binding seen in HP1 and Polycomb, instead directing H3 binding to a groove at the inter-chromodomain junction.

Analysis of metal-protein interaction distances, coordination numbers, B-factors (displacement parameters), and occupancies of metal binding sites in protein structures determined by X-ray crystallography and deposited in the PDB shows many unusual values and unexpected correlations. By measuring the frequency of each amino acid in metal ion binding sites, the positive or negative preferences of each residue for each type of cation were identified. Our approach may be used for fast identification of metal-binding structural motifs that cannot be identified on the basis of sequence similarity alone. The analysis compares data derived separately from high and medium resolution structures from the PDB with those from very high resolution small-molecule structures in the Cambridge Structural Database (CSD). For high resolution protein structures, the distribution of metal-protein or metal-water interaction distances agrees quite well with data from CSD, but the distribution is unrealistically wide for medium (2.0 -2.5 Å) resolution data. Our analysis of cation B-factors versus average B-factors of atoms in the cation environment reveals substantial numbers of structures contain either an incorrect metal ion assignment or an unusual coordination pattern. Correlation between data resolution and completeness of the metal coordination spheres is also found.