Identification of small RNAs abundant in Burkholderia cenocepacia biofilms reveal putative regulators with a potential role in carbon and iron metabolism

Small RNAs play a regulatory role in many central metabolic processes of bacteria, as well as in developmental processes such as biofilm formation. Small RNAs of Burkholderia cenocepacia, an opportunistic pathogenic beta-proteobacterium, are to date not well characterised. To address that, we performed genome-wide transcriptome structure analysis of biofilm grown B. cenocepacia J2315. 41 unannotated short transcripts were identified in intergenic regions of the B. cenocepacia genome. 15 of these short transcripts, highly abundant in biofilms, widely conserved in Burkholderia sp. and without known function, were selected for in-depth analysis. Expression profiling showed that most of these sRNAs are more abundant in biofilms than in planktonic cultures. Many are also highly abundant in cells grown in minimal media, suggesting they are involved in adaptation to nutrient limitation and growth arrest. Their computationally predicted targets include a high proportion of genes involved in carbon metabolism. Expression and target genes of one sRNA suggest a potential role in regulating iron homoeostasis. The strategy used for this study to detect sRNAs expressed in B. cenocepacia biofilms has successfully identified sRNAs with a regulatory function

Template-based structure modeling of protein-protein interactions

The structure of protein-protein complexes can be constructed by using the known structure of other protein complexes as a template. The complex structure templates are generally detected either by homology-based sequence alignments or, given the structure of monomer components, by structure-based comparisons. Critical improvements have been made in recent years by utilizing interface recognition and by recombining monomer and complex template libraries. Encouraging progress has also been witnessed in genome-wide applications of template-based modeling, with modeling accuracy comparable to high-throughput experimental data. Nevertheless, bottlenecks exist due to the incompleteness of the protein-protein complex structure library and the lack of methods for distant homologous template identification and full-length complex structure refinement. © 2013

Computational approaches to protein ligand interactions: Protein haem complexes

Many different proteins bind and utilise haem to perform important biological functions; the aim of this work was to gain an understanding of some of the underlying molecular recognition processes. We considered how the protein environment determines haem binding, and what are the consequences for ligand conformation. Sets of homologous globins and of non-homologous haem-binding proteins were chosen on the basis of sequence and structural similarity, allowing us to compare ligand conformation and to explore the factors that modulate its structure. Comparison of bound and un-bound haems revealed a conformational disparity between the data-sets, suggesting that protein structural factors provide the dominant effect over the conformational features of the ligand. Even in the homologous globins, the ligand side-chain conformation is variable; greater variability within the non-homologous group reflects different local amino acid sequences of their binding pockets. Moreover, the haem skeleton can be severely distorted, being particularly sensitive to local environment, to attached molecules, and to ligation state. The haem environment was analysed to understand its role in the functional and structural variability of the ligand. Predominance of mainly-alpha structures characterises haemoproteins. While the binding sites are radically different in topology, there are preferred binding modes, with the ligand side-chains engaged in a network of hydrophobic and hydrogen bonding interactions. The stacking of aromatic side-chains on the haem skeleton also appears to be essential in the formation of protein-ligand complexes. Analysis of the haem interface revealed that specific residues prefer to line the binding site and to form ligand contacts. An attempt to correlate properties of the unrelated protein-ligand complexes with haem redox potential was made. A compendium of these analyses has been developed and made accessible via the WWW, providing a user-friendly interface for analysing protein-haem interactions. A search tool allows on-the-fly analysis of protein-ligand relationships, which should facilitate both the comparison of different binding sites, and prediction and design of novel ones

Detecting similarities among distant homologous proteins by comparison of domain flexibilities

Aim of this work is to assess the informativeness of protein dynamics in the detection of similarities among distant homologous proteins. To this end, an approach to perform large-scale comparisons of protein domain flexibilities is proposed. CONCOORD is confirmed as a reliable method for fast conformational sampling. The root mean square fluctuation of alpha carbon positions in the essential dynamics subspace is employed as a measure of local flexibility and a synthetic index of similarity is presented. The dynamics of a large collection of protein domains from ASTRAL/SCOP40 is analyzed and the possibility to identify relationships, at both the family and the superfamily levels, on the basis of the dynamical features is discussed. The obtained picture is in agreement with the SCOP classification, and furthermore suggests the presence of a distinguishable familiar trend in the flexibility profiles. The results support the complementarity of the dynamical and the structural information, suggesting that information from dynamics analysis can arise from functional similarities, often partially hidden by a static comparison. On the basis of this first test, flexibility annotation can be expected to help in automatically detecting functional similarities otherwise unrecoverable. © 2007 The Author(s)

Structure of the Helicase Domain of DNA Polymerase Theta Reveals a Possible Role in the Microhomology-Mediated End-Joining Pathway

DNA polymerase theta (Polθ) has been identified as a crucial alternative non-homologous end-joining factor in mammalian cells. Polθ is upregulated in a range of cancer cell types defective in homologous recombination, and knockdown has been shown to inhibit cell survival in a subset of these, making it an attractive target for cancer treatment. We present crystal structures of the helicase domain of human Polθ in the presence and absence of bound nucleotides, and a characterization of its DNA-binding and DNA-stimulated ATPase activities. Comparisons with related helicases from the Hel308 family identify several unique features. Polθ exists as a tetramer both in the crystals and in solution. We propose a model for DNA binding to the Polθ helicase domain in the context of the Polθ tetramer, which suggests a role for the helicase domain in strand annealing of DNA templates for subsequent processing by the polymerase domain

Law of Genome Evolution Direction : Coding Information Quantity Grows

The problem of the directionality of genome evolution is studied. Based on the analysis of C-value paradox and the evolution of genome size we propose that the function-coding information quantity of a genome always grows in the course of evolution through sequence duplication, expansion of code, and gene transfer from outside. The function-coding information quantity of a genome consists of two parts, p-coding information quantity which encodes functional protein and n-coding information quantity which encodes other functional elements except amino acid sequence. The evidences on the evolutionary law about the function-coding information quantity are listed. The needs of function is the motive force for the expansion of coding information quantity and the information quantity expansion is the way to make functional innovation and extension for a species. So, the increase of coding information quantity of a genome is a measure of the acquired new function and it determines the directionality of genome evolution.Comment: 16 page

Structural Prediction of Protein–Protein Interactions by Docking: Application to Biomedical Problems

A huge amount of genetic information is available thanks to the recent advances in sequencing technologies and the larger computational capabilities, but the interpretation of such genetic data at phenotypic level remains elusive. One of the reasons is that proteins are not acting alone, but are specifically interacting with other proteins and biomolecules, forming intricate interaction networks that are essential for the majority of cell processes and pathological conditions. Thus, characterizing such interaction networks is an important step in understanding how information flows from gene to phenotype. Indeed, structural characterization of protein–protein interactions at atomic resolution has many applications in biomedicine, from diagnosis and vaccine design, to drug discovery. However, despite the advances of experimental structural determination, the number of interactions for which there is available structural data is still very small. In this context, a complementary approach is computational modeling of protein interactions by docking, which is usually composed of two major phases: (i) sampling of the possible binding modes between the interacting molecules and (ii) scoring for the identification of the correct orientations. In addition, prediction of interface and hot-spot residues is very useful in order to guide and interpret mutagenesis experiments, as well as to understand functional and mechanistic aspects of the interaction. Computational docking is already being applied to specific biomedical problems within the context of personalized medicine, for instance, helping to interpret pathological mutations involved in protein–protein interactions, or providing modeled structural data for drug discovery targeting protein–protein interactions.Spanish Ministry of Economy grant number BIO2016-79960-R; D.B.B. is supported by a predoctoral fellowship from CONACyT; M.R. is supported by an FPI fellowship from the Severo Ochoa program. We are grateful to the Joint BSC-CRG-IRB Programme in Computational Biology.Peer ReviewedPostprint (author's final draft

Activation of tyrosine kinases by mutation of the gatekeeper threonine.

Protein kinases targeted by small-molecule inhibitors develop resistance through mutation of the gatekeeper threonine residue of the active site. Here we show that the gatekeeper mutation in the cellular forms of c-ABL, c-SRC, platelet-derived growth factor receptor-alpha and -beta, and epidermal growth factor receptor activates the kinase and promotes malignant transformation of BaF3 cells. Structural analysis reveals that a network of hydrophobic interactions-the hydrophobic spine-characteristic of the active kinase conformation is stabilized by the gatekeeper substitution. Substitution of glycine for the residues constituting the spine disrupts the hydrophobic connectivity and inactivates the kinase. Furthermore, a small-molecule inhibitor that maximizes complementarity with the dismantled spine (compound 14) inhibits the gatekeeper mutation of BCR-ABL-T315I. These results demonstrate that mutation of the gatekeeper threonine is a common mechanism of activation for tyrosine kinases and provide structural insights to guide the development of next-generation inhibitors