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Metals play vital roles in both the mechanism and architecture of biological macromolecules. Yet structures of metal-containing macromolecules where metals are misidentified and/or suboptimally modeled are abundant in the Protein Data Bank (PDB). This shows the need for a diagnostic tool to identify and correct such modeling problems with metal binding environments. The "CheckMyMetal" (CMM) web server (http://csgid.org/csgid/metal_sites/) is a sophisticated, user-friendly web-based method to evaluate metal binding sites in macromolecular structures in respect to 7350 metal binding sites observed in a benchmark dataset of 2304 high resolution crystal structures. The protocol outlines how the CMM server can be used to detect geometric and other irregularities in the structures of metal binding sites and alert researchers to potential errors in metal assignment. The protocol also gives practical guidelines for correcting problematic sites by modifying the metal binding environment and/or redefining metal identity in the PDB file. Several examples where this has led to meaningful results are described in the anticipated results section. CMM was designed for a broad audience—biomedical researchers studying metal-containing proteins and nucleic acids—but is equally well suited for structural biologists to validate new structures during modeling or refinement. The CMM server takes the coordinates of a metal-containing macromolecule structure in the PDB format as input and responds within a few seconds for a typical protein structure modeled with a few hundred amino acids.

Metals are essential in many biological processes, and metal ions are modeled in roughly 40% of the macromolecular structures in the Protein Data Bank (PDB). However, a significant fraction of these structures contain poorly modeled metal-binding sites. CheckMyMetal (CMM) is an easy-to-use metal-binding site validation server for macromolecules that is freely available at http://csgid.org/ csgid/metal_sites. The CMM server can detect incorrect metal assignments as well as geometrical and other irregularities in the metal-binding sites. Guidelines for metal-site modeling and validation in macromolecules are illustrated by several practical examples grouped by the type of metal. These examples show CMM users (and crystallographers in general) problems they may encounter during the modeling of a specific metal ion.

Growing well-diffracting crystals constitutes a serious bottleneck in structural biology. A recently proposed crystallization methodology for ''stubborn crystallizers'' is to engineer surface sequence variants designed to form intermolecular contacts that could support a crystal lattice. This approach relies on the concept of surface entropy reduction (SER), i.e., the replacement of clusters of flexible, solvent-exposed residues with residues with lower conformational entropy. This strategy minimizes the loss of conformational entropy upon crystallization and renders crystallization thermodynamically favorable. The method has been successfully used to crystallize more than 15 novel proteins, all stubborn crystallizers. But the choice of suitable sites for mutagenesis is not trivial. Herein, we announce a Web server, the surface entropy reduction prediction server (SERp server), designed to identify mutations that may facilitate crystallization. Suggested mutations are predicted based on an algorithm incorporating a conformational entropy profile, a secondary structure prediction, and sequence conservation. Minor considerations include the nature of flanking residues and gaps between mutation candidates. While designed to be used with default values, the server has many user-controlled parameters allowing for considerable flexibility. Within, we discuss (1) the methodology of the server, (2) how to interpret the results, and (3) factors that must be considered when selecting mutations. We also attempt to benchmark the server by comparing the server's predictions with successful SER structures. In most cases, the structure yielding mutations were easily identified by the SERp server. The server can be accessed at http://www.doe-mbi.ucla.edu/Services/SER.

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Acetate kinase, an enzyme widely distributed in the Bacteria and Archaea domains, catalyzes the phosphorylation of acetate. We have determined the three-dimensional structure of Methanosarcina thermophila acetate kinase bound to ADP through crystallography. As we previously predicted, acetate kinase contains a core fold that is topologically identical to that of the ADP-binding domains of glycerol kinase, hexokinase, the 70-kDa heat shock cognate (Hsc70), and actin. Numerous charged active-site residues are conserved within acetate kinases, but few are conserved within the phosphotransferase superfamily. The identity of the points of insertion of polypeptide segments into the core fold of the superfamily members indicates that the insertions existed in the common ancestor of the phosphotransferases. Another remarkable shared feature is the unusual, epsilon conformation of the residue that directly precedes a conserved glycine residue (Gly-331 in acetate kinase) that binds the ␣-phosphate of ADP. Structural, biochemical, and geochemical considerations indicate that an acetate kinase may be the ancestral enzyme of the ASKHA (acetate and sugar kinases/Hsc70/actin) superfamily of phosphotransferases.

A strategy of rationally engineering protein surfaces with the aim of obtaining mutants that are distinctly more susceptible to crystallization than the wild-type protein has previously been suggested. The strategy relies on replacing small clusters of two to three surface residues characterized by high conformational entropy with alanines. This surface entropy reduction (or SER) method has proven to be an effective salvage pathway for proteins that are difficult to crystallize. Here, a systematic comparison of the efficacy of using Ala, His, Ser, Thr and Tyr to replace high-entropy residues is reported. A total of 40 mutants were generated and screened using two different procedures. The results reaffirm that alanine is a particularly good choice for a replacement residue and identify tyrosines and threonines as additional candidates that have considerable potential to mediate crystal contacts. The propensity of these mutants to form crystals in alternative screens in which the normal crystallization reservoir solutions were replaced with 1.5 M NaCl was also examined. The results were impressive: more than half of the mutants yielded a larger number of crystals with salt as the reservoir solution. This method greatly increased the variety of conditions that yielded crystals. Taken together, these results suggest a powerful crystallization strategy that combines surface engineering with efficient screening using standard and alternate reservoir solutions.

Mutations in the Lis1 gene result in lissencephaly (smooth brain), a debilitating developmental syndrome caused by the impaired ability of postmitotic neurons to migrate to their correct destination in the cerebral cortex. Sequence similarities suggest that the LIS1 protein contains a C-terminal seven-blade beta-propeller domain, while the structure of the N-terminal fragment includes the LisH (Lis-homology) motif, a pattern found in over 100 eukaryotic proteins with a hitherto unknown function. We present the 1.75 A resolution crystal structure of the N-terminal domain of mouse LIS1, and we show that the LisH motif is a novel, thermodynamically very stable dimerization domain. The structure explains the molecular basis of a low severity form of lissencephaly.