PocketMatch: A new algorithm to compare binding sites in protein structures

Background: Recognizing similarities and deriving relationships among protein molecules is a fundamental
requirement in present-day biology. Similarities can be present at various levels which can be detected through comparison of protein sequences or their structural folds. In some cases similarities obscure at these levels could be present merely in the substructures at their binding sites. Inferring functional similarities between protein molecules by comparing their binding sites is still largely exploratory and not as yet a routine protocol. One of
the main reasons for this is the limitation in the choice of appropriate analytical tools that can compare binding sites with high sensitivity. To benefit from the enormous amount of structural data that is being rapidly accumulated, it is essential to have high throughput tools that enable large scale binding site comparison.

Results: Here we present a new algorithm PocketMatch for comparison of binding sites in a frame invariant
manner. Each binding site is represented by 90 lists of sorted distances capturing shape and chemical nature of the site. The sorted arrays are then aligned using an incremental alignment method and scored to obtain PMScores for pairs of sites. A comprehensive sensitivity analysis and an extensive validation of the algorithm have been carried out. Perturbation studies where the geometry of a given site was retained but the residue types were changed randomly, indicated that chance similarities were virtually non-existent. Our analysis also demonstrates that shape information alone is insufficient to discriminate between diverse binding sites, unless
combined with chemical nature of amino acids.

Conclusions: A new algorithm has been developed to compare binding sites in accurate, efficient and
high-throughput manner. Though the representation used is conceptually simplistic, we demonstrate that along
with the new alignment strategy used, it is sufficient to enable binding comparison with high sensitivity. Novel methodology has also been presented for validating the algorithm for accuracy and sensitivity with respect to geometry and chemical nature of the site. The method is also fast and takes about 1/250th second for one comparison on a single processor. A parallel version on BlueGene has also been implemented

Structural Annotation of Mycobacterium tuberculosis Proteome

Of the ∼4000 ORFs identified through the genome sequence of Mycobacterium tuberculosis (TB) H37Rv, experimentally determined structures are available for 312. Since knowledge of protein structures is essential to obtain a high-resolution understanding of the underlying biology, we seek to obtain a structural annotation for the genome, using computational methods. Structural models were obtained and validated for ∼2877 ORFs, covering ∼70% of the genome. Functional annotation of each protein was based on fold-based functional assignments and a novel binding site based ligand association. New algorithms for binding site detection and genome scale binding site comparison at the structural level, recently reported from the laboratory, were utilized. Besides these, the annotation covers detection of various sequence and sub-structural motifs and quaternary structure predictions based on the corresponding templates. The study provides an opportunity to obtain a global perspective of the fold distribution in the genome. The annotation indicates that cellular metabolism can be achieved with only 219 folds. New insights about the folds that predominate in the genome, as well as the fold-combinations that make up multi-domain proteins are also obtained. 1728 binding pockets have been associated with ligands through binding site identification and sub-structure similarity analyses. The resource (http://proline.physics.iisc.ernet.in/Tbstructuralannotation), being one of the first to be based on structure-derived functional annotations at a genome scale, is expected to be useful for better understanding of TB and for application in drug discovery. The reported annotation pipeline is fairly generic and can be applied to other genomes as well

Editing independent effects of ADARs on the miRNA/siRNA pathways

Adenosine deaminases acting on RNA (ADARs) are best known for altering the coding sequences of mRNA through RNA editing, as in the GluR-B Q/R site. ADARs have also been shown to affect RNA interference (RNAi) and microRNA processing by deamination of specific adenosines to inosine. Here, we show that ADAR proteins can affect RNA processing independently of their enzymatic activity. We show that ADAR2 can modulate the processing of mir-376a2 independently of catalytic RNA editing activity. In addition, in a Drosophila assay for RNAi deaminase-inactive ADAR1 inhibits RNAi through the siRNA pathway. These results imply that ADAR1 and ADAR2 have biological functions as RNA-binding proteins that extend beyond editing per se and that even genomically encoded ADARs that are catalytically inactive may have such functions

Search for Limiting Factors in the RNAi Pathway in Silkmoth Tissues and the Bm5 Cell Line: The RNA-Binding Proteins R2D2 and Translin

RNA interference (RNAi), an RNA-dependent gene silencing process that is initiated by double-stranded RNA (dsRNA) molecules, has been applied with variable success in lepidopteran insects, in contrast to the high efficiency achieved in the coleopteran Tribolium castaneum. To gain insight into the factors that determine the efficiency of RNAi, a survey was carried out to check the expression of factors that constitute the machinery of the small interfering RNA (siRNA) and microRNA (miRNA) pathways in different tissues and stages of the silkmoth, Bombyx mori. It was found that the dsRNA-binding protein R2D2, an essential component in the siRNA pathway in Drosophila, was expressed at minimal levels in silkmoth tissues. The silkmoth-derived Bm5 cell line was also deficient in expression of mRNA encoding full-length BmTranslin, an RNA-binding factor that has been shown to stimulate the efficiency of RNAi. However, despite the lack of expression of the RNA-binding proteins, silencing of a luciferase reporter gene was observed by co-transfection of luc dsRNA using a lipophilic reagent. In contrast, gene silencing was not detected when the cells were soaked in culture medium supplemented with dsRNA. The introduction of an expression construct for Tribolium R2D2 (TcR2D2) did not influence the potency of luc dsRNA to silence the luciferase reporter. Immunostaining experiments further showed that both TcR2D2 and BmTranslin accumulated at defined locations within the cytoplasm of transfected cells. Our results offer a first evaluation of the expression of the RNAi machinery in silkmoth tissues and Bm5 cells and provide evidence for a functional RNAi response to intracellular dsRNA in the absence of R2D2 and Translin. The failure of TcR2D2 to stimulate the intracellular RNAi pathway in Bombyx cells is discussed

Competing Activities of Heterotrimeric G Proteins in Drosophila Wing Maturation

Drosophila genome encodes six alpha-subunits of heterotrimeric G proteins. The Gαs alpha-subunit is involved in the post-eclosion wing maturation, which consists of the epithelial-mesenchymal transition and cell death, accompanied by unfolding of the pupal wing into the firm adult flight organ. Here we show that another alpha-subunit Gαo can specifically antagonize the Gαs activities by competing for the Gβ13F/Gγ1 subunits of the heterotrimeric Gs protein complex. Loss of Gβ13F, Gγ1, or Gαs, but not any other G protein subunit, results in prevention of post-eclosion cell death and failure of the wing expansion. However, cell death prevention alone is not sufficient to induce the expansion defect, suggesting that the failure of epithelial-mesenchymal transition is key to the folded wing phenotypes. Overactivation of Gαs with cholera toxin mimics expression of constitutively activated Gαs and promotes wing blistering due to precocious cell death. In contrast, co-overexpression of Gβ13F and Gγ1 does not produce wing blistering, revealing the passive role of the Gβγ in the Gαs-mediated activation of apoptosis, but hinting at the possible function of Gβγ in the epithelial-mesenchymal transition. Our results provide a comprehensive functional analysis of the heterotrimeric G protein proteome in the late stages of Drosophila wing development

Prodepth: Predict Residue Depth by Support Vector Regression Approach from Protein Sequences Only

Residue depth (RD) is a solvent exposure measure that complements the information provided by conventional accessible surface area (ASA) and describes to what extent a residue is buried in the protein structure space. Previous studies have established that RD is correlated with several protein properties, such as protein stability, residue conservation and amino acid types. Accurate prediction of RD has many potentially important applications in the field of structural bioinformatics, for example, facilitating the identification of functionally important residues, or residues in the folding nucleus, or enzyme active sites from sequence information. In this work, we introduce an efficient approach that uses support vector regression to quantify the relationship between RD and protein sequence. We systematically investigated eight different sequence encoding schemes including both local and global sequence characteristics and examined their respective prediction performances. For the objective evaluation of our approach, we used 5-fold cross-validation to assess the prediction accuracies and showed that the overall best performance could be achieved with a correlation coefficient (CC) of 0.71 between the observed and predicted RD values and a root mean square error (RMSE) of 1.74, after incorporating the relevant multiple sequence features. The results suggest that residue depth could be reliably predicted solely from protein primary sequences: local sequence environments are the major determinants, while global sequence features could influence the prediction performance marginally. We highlight two examples as a comparison in order to illustrate the applicability of this approach. We also discuss the potential implications of this new structural parameter in the field of protein structure prediction and homology modeling. This method might prove to be a powerful tool for sequence analysis

The Stimulatory Gαs Protein Is Involved in Olfactory Signal Transduction in Drosophila

Seven-transmembrane receptors typically mediate olfactory signal transduction by coupling to G-proteins. Although insect odorant receptors have seven transmembrane domains like G-protein coupled receptors, they have an inverted membrane topology, constituting a key difference between the olfactory systems of insects and other animals. While heteromeric insect ORs form ligand-activated non-selective cation channels in recombinant expression systems, the evidence for an involvement of cyclic nucleotides and G-proteins in odor reception is inconsistent. We addressed this question in vivo by analyzing the role of G-proteins in olfactory signaling using electrophysiological recordings. We found that Gαs plays a crucial role for odorant induced signal transduction in OR83b expressing olfactory sensory neurons, but not in neurons expressing CO2 responsive proteins GR21a/GR63a. Moreover, signaling of Drosophila ORs involved Gαs also in a heterologous expression system. In agreement with these observations was the finding that elevated levels of cAMP result in increased firing rates, demonstrating the existence of a cAMP dependent excitatory signaling pathway in the sensory neurons. Together, we provide evidence that Gαs plays a role in the OR mediated signaling cascade in Drosophila