Dynein structure and power stroke

Dynein ATPases are microtubule motors that are critical to diverse processes such as vesicle transport and the beating of sperm tails; however, their mechanism of force generation is unknown. Each dynein comprises a head, from which a stalk and a stem emerge. Here we use electron microscopy and image processing to reveal new structural details of dynein c, an isoform from Chlamydomonas reinhardtii flagella, at the start and end of its power stroke. Both stem and stalk are flexible, and the stem connects to the head by means of a linker approximately 10 nm long that we propose lies across the head. With both ADP and vanadate bound, the stem and stalk emerge from the head 10 nm apart. However, without nucleotide they emerge much closer together owing to a change in linker orientation, and the coiled-coil stalk becomes stiffer. The net result is a shortening of the molecule coupled to an approximately 15-nm displacement of the tip of the stalk. These changes indicate a mechanism for the dynein power stroke

Discovering Sequence Motifs with Arbitrary Insertions and Deletions

Biology is encoded in molecular sequences: deciphering this encoding remains a grand scientific challenge. Functional regions of DNA, RNA, and protein sequences often exhibit characteristic but subtle motifs; thus, computational discovery of motifs in sequences is a fundamental and much-studied problem. However, most current algorithms do not allow for insertions or deletions (indels) within motifs, and the few that do have other limitations. We present a method, GLAM2 (Gapped Local Alignment of Motifs), for discovering motifs allowing indels in a fully general manner, and a companion method GLAM2SCAN for searching sequence databases using such motifs. glam2 is a generalization of the gapless Gibbs sampling algorithm. It re-discovers variable-width protein motifs from the PROSITE database significantly more accurately than the alternative methods PRATT and SAM-T2K. Furthermore, it usefully refines protein motifs from the ELM database: in some cases, the refined motifs make orders of magnitude fewer overpredictions than the original ELM regular expressions. GLAM2 performs respectably on the BAliBASE multiple alignment benchmark, and may be superior to leading multiple alignment methods for “motif-like” alignments with N- and C-terminal extensions. Finally, we demonstrate the use of GLAM2 to discover protein kinase substrate motifs and a gapped DNA motif for the LIM-only transcriptional regulatory complex: using GLAM2SCAN, we identify promising targets for the latter. GLAM2 is especially promising for short protein motifs, and it should improve our ability to identify the protein cleavage sites, interaction sites, post-translational modification attachment sites, etc., that underlie much of biology. It may be equally useful for arbitrarily gapped motifs in DNA and RNA, although fewer examples of such motifs are known at present. GLAM2 is public domain software, available for download at http://bioinformatics.org.au/glam2

Co-Conserved Features Associated with cis Regulation of ErbB Tyrosine Kinases

BACKGROUND: The epidermal growth factor receptor kinases, or ErbB kinases, belong to a large sub-group of receptor tyrosine kinases (RTKs), which share a conserved catalytic core. The catalytic core of ErbB kinases have functionally diverged from other RTKs in that they are activated by a unique allosteric mechanism that involves specific interactions between the kinase core and the flanking Juxtamembrane (JM) and COOH-terminal tail (C-terminal tail). Although extensive studies on ErbB and related tyrosine kinases have provided important insights into the structural basis for ErbB kinase functional divergence, the sequence features that contribute to the unique regulation of ErbB kinases have not been systematically explored. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we use a Bayesian approach to identify the selective sequence constraints that most distinguish ErbB kinases from other receptor tyrosine kinases. We find that strong ErbB kinase-specific constraints are imposed on residues that tether the JM and C-terminal tail to key functional regions of the kinase core. A conserved RIxKExE motif in the JM-kinase linker region and a glutamine in the inter-lobe linker are identified as two of the most distinguishing features of the ErbB family. While the RIxKExE motif tethers the C-terminal tail to the N-lobe of the kinase domain, the glutamine tethers the C-terminal tail to hinge regions critical for inter-lobe movement. Comparison of the active and inactive crystal structures of ErbB kinases indicates that the identified residues are conformationally malleable and can potentially contribute to the cis regulation of the kinase core by the JM and C-terminal tail. ErbB3, and EGFR orthologs in sponges and parasitic worms, diverge from some of the canonical ErbB features, providing insights into sub-family and lineage-specific functional specialization. CONCLUSION/SIGNIFICANCE: Our analysis pinpoints key residues for mutational analysis, and provides new clues to cancer mutations that alter the canonical modes of ErbB kinase regulation

Conserved phosphoryl transfer mechanisms within kinase families and the role of the C8 proton of ATP in the activation of phosphoryl transfer

<p>Abstract</p> <p>Background</p> <p>The kinome is made up of a large number of functionally diverse enzymes, with the classification indicating very little about the extent of the conserved kinetic mechanisms associated with phosphoryl transfer. It has been demonstrated that C8-H of ATP plays a critical role in the activity of a range of kinase and synthetase enzymes.</p> <p>Results</p> <p>A number of conserved mechanisms within the prescribed kinase fold families have been identified directly utilizing the C8-H of ATP in the initiation of phosphoryl transfer. These mechanisms are based on structurally conserved amino acid residues that are within hydrogen bonding distance of a co-crystallized nucleotide. On the basis of these conserved mechanisms, the role of the nucleotide C8-H in initiating the formation of a pentavalent intermediate between the γ-phosphate of the ATP and the substrate nucleophile is defined. All reactions can be clustered into two mechanisms by which the C8-H is induced to be labile via the coordination of a backbone carbonyl to C6-NH₂of the adenyl moiety, namely a "push" mechanism, and a "pull" mechanism, based on the protonation of N7. Associated with the "push" mechanism and "pull" mechanisms are a series of proton transfer cascades, initiated from C8-H, via the tri-phosphate backbone, culminating in the formation of the pentavalent transition state between the γ-phosphate of the ATP and the substrate nucleophile.</p> <p>Conclusions</p> <p>The "push" mechanism and a "pull" mechanism are responsible for inducing the C8-H of adenyl moiety to become more labile. These mechanisms and the associated proton transfer cascades achieve the proton transfer via different family-specific conserved sets of amino acids. Each of these mechanisms would allow for the regulation of the rate of formation of the pentavalent intermediate between the ATP and the substrate nucleophile. Phosphoryl transfer within kinases is therefore a specific event mediated and regulated via the coordination of the adenyl moiety of ATP and the C8-H of the adenyl moiety.</p

rMotifGen: random motif generator for DNA and protein sequences

<p>Abstract</p> <p>Background</p> <p>Detection of short, subtle conserved motif regions within a set of related DNA or amino acid sequences can lead to discoveries about important regulatory domains such as transcription factor and DNA binding sites as well as conserved protein domains. In order to help assess motif detection algorithms on motifs with varying properties and levels of conservation, we have developed a computational tool, rMotifGen, with the sole purpose of generating a number of random DNA or protein sequences containing short sequence motifs. Each motif consensus can be user-defined, randomly generated, or created from a position-specific scoring matrix (PSSM). Insertions and mutations within these motifs are created according to user-defined parameters and substitution matrices. The resulting sequences can be helpful in mutational simulations and in testing the limits of motif detection algorithms.</p> <p>Results</p> <p>Two implementations of rMotifGen have been created, one providing a graphical user interface (GUI) for random motif construction, and the other serving as a command line interface. The second implementation has the added advantages of platform independence and being able to be called in a batch mode. rMotifGen was used to construct sample sets of sequences containing DNA motifs and amino acid motifs that were then tested against the Gibbs sampler and MEME packages.</p> <p>Conclusion</p> <p>rMotifGen provides an efficient and convenient method for creating random DNA or amino acid sequences with a variable number of motifs, where the instance of each motif can be incorporated using a position-specific scoring matrix (PSSM) or by creating an instance mutated from its corresponding consensus using an evolutionary model based on substitution matrices. rMotifGen is freely available at: <url>http://bioinformatics.louisville.edu/brg/rMotifGen/</url>.</p

Highly Sensitive Detection of Individual HEAT and ARM Repeats with HHpred and COACH

BACKGROUND:HEAT and ARM repeats occur in a large number of eukaryotic proteins. As these repeats are often highly diverged, the prediction of HEAT or ARM domains can be challenging. Except for the most clear-cut cases, identification at the individual repeat level is indispensable, in particular for determining domain boundaries. However, methods using single sequence queries do not have the sensitivity required to deal with more divergent repeats and, when applied to proteins with known structures, in some cases failed to detect a single repeat. METHODOLOGY AND PRINCIPAL FINDINGS:Testing algorithms which use multiple sequence alignments as queries, we found two of them, HHpred and COACH, to detect HEAT and ARM repeats with greatly enhanced sensitivity. Calibration against experimentally determined structures suggests the use of three score classes with increasing confidence in the prediction, and prediction thresholds for each method. When we applied a new protocol using both HHpred and COACH to these structures, it detected 82% of HEAT repeats and 90% of ARM repeats, with the minimum for a given protein of 57% for HEAT repeats and 60% for ARM repeats. Application to bona fide HEAT and ARM proteins or domains indicated that similar numbers can be expected for the full complement of HEAT/ARM proteins. A systematic screen of the Protein Data Bank for false positive hits revealed their number to be low, in particular for ARM repeats. Double false positive hits for a given protein were rare for HEAT and not at all observed for ARM repeats. In combination with fold prediction and consistency checking (multiple sequence alignments, secondary structure prediction, and position analysis), repeat prediction with the new HHpred/COACH protocol dramatically improves prediction in the twilight zone of fold prediction methods, as well as the delineation of HEAT/ARM domain boundaries. SIGNIFICANCE:A protocol is presented for the identification of individual HEAT or ARM repeats which is straightforward to implement. It provides high sensitivity at a low false positive rate and will therefore greatly enhance the accuracy of predictions of HEAT and ARM domains

GibbsST: a Gibbs sampling method for motif discovery with enhanced resistance to local optima

BACKGROUND: Computational discovery of transcription factor binding sites (TFBS) is a challenging but important problem of bioinformatics. In this study, improvement of a Gibbs sampling based technique for TFBS discovery is attempted through an approach that is widely known, but which has never been investigated before: reduction of the effect of local optima. RESULTS: To alleviate the vulnerability of Gibbs sampling to local optima trapping, we propose to combine a thermodynamic method, called simulated tempering, with Gibbs sampling. The resultant algorithm, GibbsST, is then validated using synthetic data and actual promoter sequences extracted from Saccharomyces cerevisiae. It is noteworthy that the marked improvement of the efficiency presented in this paper is attributable solely to the improvement of the search method. CONCLUSION: Simulated tempering is a powerful solution for local optima problems found in pattern discovery. Extended application of simulated tempering for various bioinformatic problems is promising as a robust solution against local optima problems

Characterisation of the Putative Effector Interaction Site of the Regulatory HbpR Protein from Pseudomonas azelaica by Site-Directed Mutagenesis

Bacterial transcription activators of the XylR/DmpR subfamily exert their expression control via σ54-dependent RNA polymerase upon stimulation by a chemical effector, typically an aromatic compound. Where the chemical effector interacts with the transcription regulator protein to achieve activation is still largely unknown. Here we focus on the HbpR protein from Pseudomonas azelaica, which is a member of the XylR/DmpR subfamily and responds to biaromatic effectors such as 2-hydroxybiphenyl. We use protein structure modeling to predict folding of the effector recognition domain of HbpR and molecular docking to identify the region where 2-hydroxybiphenyl may interact with HbpR. A large number of site-directed HbpR mutants of residues in- and outside the predicted interaction area was created and their potential to induce reporter gene expression in Escherichia coli from the cognate PC promoter upon activation with 2-hydroxybiphenyl was studied. Mutant proteins were purified to study their conformation. Critical residues for effector stimulation indeed grouped near the predicted area, some of which are conserved among XylR/DmpR subfamily members in spite of displaying different effector specificities. This suggests that they are important for the process of effector activation, but not necessarily for effector specificity recognition

Identification of an Amphipathic Helix Important for the Formation of Ectopic Septin Spirals and Axial Budding in Yeast Axial Landmark Protein Bud3p

Correct positioning of polarity axis in response to internal or external cues is central to cellular morphogenesis and cell fate determination. In the budding yeast Saccharomyces cerevisiae, Bud3p plays a key role in the axial bud-site selection (axial budding) process in which cells assemble the new bud next to the preceding cell division site. Bud3p is thought to act as a component of a spatial landmark. However, it is not clear how Bud3p interacts with other components of the landmark, such as the septins, to control axial budding. Here, we report that overexpression of Bud3p causes the formation of small septin rings (∼1 µm in diameter) and arcs aside from previously reported spiral-like septin structures. Bud3p closely associates with the septins in vivo as Bud3p colocalizes with these aberrant septin structures and forms a complex with two septins, Cdc10p and Cdc11p. The interaction of Bud3p with the septins may involve multiple regions of Bud3p including 1–858, 850–1220, and 1221–1636 a.a. since they all target to the bud neck but exhibit different effects on septin organization when overexpressed. In addition, our study reveals that the axial budding function of Bud3p is mediated by the N-terminal region 1–858. This region shares an amphipathic helix (850–858) crucial for bud neck targeting with the middle portion 850–1103 involved in the formation of ectopic septin spirals and rings. Interestingly, the Dbl-homology domain located in 1–858 is dispensable for axial bud-site selection. Our findings suggest that multiple regions of Bud3p ensure efficient targeting of Bud3p to the bud neck in the assembly of the axial landmark and distinct domains of Bud3p are involved in axial bud-site selection and other cellular processes

Query Large Scale Microarray Compendium Datasets Using a Model-Based Bayesian Approach with Variable Selection

In microarray gene expression data analysis, it is often of interest to identify genes that share similar expression profiles with a particular gene such as a key regulatory protein. Multiple studies have been conducted using various correlation measures to identify co-expressed genes. While working well for small datasets, the heterogeneity introduced from increased sample size inevitably reduces the sensitivity and specificity of these approaches. This is because most co-expression relationships do not extend to all experimental conditions. With the rapid increase in the size of microarray datasets, identifying functionally related genes from large and diverse microarray gene expression datasets is a key challenge. We develop a model-based gene expression query algorithm built under the Bayesian model selection framework. It is capable of detecting co-expression profiles under a subset of samples/experimental conditions. In addition, it allows linearly transformed expression patterns to be recognized and is robust against sporadic outliers in the data. Both features are critically important for increasing the power of identifying co-expressed genes in large scale gene expression datasets. Our simulation studies suggest that this method outperforms existing correlation coefficients or mutual information-based query tools. When we apply this new method to the Escherichia coli microarray compendium data, it identifies a majority of known regulons as well as novel potential target genes of numerous key transcription factors