A computer program has been developed to aid the analysis of molecular dynamics trajectories. The program is tuned for macromolecular large-scale problems and supports features such as removal of global translations-rotations of the solute, calculation of average distance maps and their corresponding standard deviations, calculation of the variance-covariance and cross-correlation matrices, and principal component analysis of trajectories with the added ability to create artificial trajectories based on selected eigenvectors. Limited graphics (trajectory viewing) capabilities are also available.

We report the availability of grcarma, a program encoding for a fully automated set of tasks aiming to simplify the analysis of molecular dynamics trajectories of biological macromolecules. It is a cross-platform, Perl/Tk-based front-end to the program carma and is designed to facilitate the needs of the novice as well as those of the expert user, while at the same time maintaining a user-friendly and intuitive design. Particular emphasis was given to the automation of several tedious tasks, such as extraction of clusters of structures based on dihedral and Cartesian principal component analysis, secondary structure analysis, calculation and display of root-meansquare deviation (RMSD) matrices, calculation of entropy, calculation and analysis of variance–covariance matrices, calculation of the fraction of native contacts, etc. The program is free-open source software available immediately for download.

Type III secretion systems enable plant and animal bacterial pathogens to deliver virulence proteins into the cytosol of eukaryotic host cells, causing a broad spectrum of diseases including bacteremia, septicemia, typhoid fever, and bubonic plague in mammals, and localized lesions, systemic wilting, and blights in plants. In addition, type III secretion systems are also required for biogenesis of the bacterial flagellum. The HrcQB protein, a component of the secretion apparatus of Pseudomonas syringae with homologues in all type III systems, has a variable N-terminal and a conserved C-terminal domain (HrcQB-C). Here, we report the crystal structure of HrcQB-C and show that this domain retains the ability of the full-length protein to interact with other type III components. A 3D analysis of sequence conservation patterns reveals two clusters of residues potentially involved in protein-protein interactions. Based on the analogies between HrcQB and its flagellum homologues, we propose that HrcQB-C participates in the formation of a C-ring-like assembly.

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research papers 422 Dennis et al. AhrC Acta Cryst. (2002). D58, 421±430 pseudo-palindromic ARG boxes which are the binding sites for the E. coli arginine repressor ArgR (ArgREc; Glansdorff, 1987; Smith et al., 1989). Examination of the argC promoter and gene using DNase I and hydroxyl radical footprinting revealed two AhrC-binding sites, which were named argC 01 and argC 02. The higher af®nity binding site, argC 01 , contains two ARG boxes separated by 11 bp and lies within the argC promoter, whilst the lower af®nity site, argC 02 , contains a single ARG box and is located within the argC structural gene (Czaplewski et al., 1992). The argG promoter contains two ARG boxes, separated by 2 bp, upstream of the transcription start site (Miller, 1997). The B. subtilis arginine catabolic pathway contains six enzymes encoded by genes within the two clusters rocABC and rocDEF. AhrC has been shown to interact in an l-arginine-dependent manner with operators within the promoter regions of rocA and rocD. Each of these operators consists of a single ARG box which is located directly adjacent to the transcription start site (Calogero et al., 1994; Klingel et al., 1995; Gardan et al., 1995; Miller et al., 1997). The af®nity of AhrC for the catabolic operators is 10-to 20-fold less than for the biosynthetic gene promoters (Miller et al., 1997), a ®nding consistent with the notion of cooperative binding of AhrC to the tandem repeats of ARG boxes within the upstream regulatory regions of argC and argG. The mechanism by which AhrC activates transcription from rocA and rocD remains unclear, although AhrC binding has been shown to increase the natural bend of the rocA promoter (Miller et al., 1997), which may facilitate interactions with RNA polymerase. Arginine-regulatory proteins, which are usually called ArgR in organisms other than B. subtilis, have been identi®ed in E. coli (Lim et al., 1987), B. stearothermophilus (Dion et al., 1997) and Salmonella typhimurium (Lu et al., 1992). These proteins have been biochemically characterized and shown to act as repressors of arginine biosynthesis in their respective hosts, although any roles in the activation of arginine catabolism remain to be con®rmed experimentally. Sequences are also known for probable AhrC/ArgR homologues from Clostridium perfringens (Ohtani et al., 1997), Haemophilus in¯uenzae (Fleischmann et al., 1995), Mycobacterium tuberculosis (Cole et al., 1998), Streptomyces clavuligerus (Rodriguez-Garcia et al., 1997) and Streptococcus pneumoniae (Priebe et al., 1988). The best characterized of the AhrC homologues is ArgR of E. coli (ArgREc; Lim et al., 1987; Maas, 1994). AhrC and ArgREc share 27% identity (North et al., 1989) and can crossfunction to some extent in vivo. AhrC can repress E. coli arginine genes and complement for ArgR as an essential accessory protein in the resolution of plasmid ColE1 multimers (Stirling et al., 1988); however, ArgR cannot repress the B. subtilis argC promoter (Smith et al., 1989). AhrC and ArgR both require the binding of l-arginine for hig...