Naview: A d3.js Based JavaScript Library for Drawing and Annotating Voltage-Gated Sodium Channels Membrane Diagrams.

Voltage-gated sodium channels (Nav) are membrane proteins essential to initiating and propagating action potential in neurons and other excitable cells. For a given organism there are often multiple, specialized sodium channels found in different tissues, whose mutations can cause deleterious effects observed in numerous diseases. Consequently, there is high medical and pharmacological interest in these proteins. Scientific literature often uses membrane diagrams to depict important patterns in these channels including the six transmembrane segments (S1-S6) present in four different homologous domains (D1-D4), the S4 voltage sensors, the pore-lining residue segments and the ion selectivity filter residues, glycosylation and phosphorylation residues, toxin binding sites and the inactivation loop, among others. Most of these diagrams are illustrated either digitally or by hand and programs specifically dedicated to the interactive and data-friendly generation of such visualizations are scarce or non-existing. This paper describes Naview, an open-source javascript visualization compatible with modern web browsers for the dynamic drawing and annotation of voltage-gated sodium channels membrane diagrams based on the D3.js library. By using a graphical user interface and combining user-defined annotations with optional UniProt code as inputs, Naview allows the creation and customization of membrane diagrams. In this interface, a user can also map and display important sodium channel properties, residues, regions and their relationships through symbols, colors, and edge connections. Such features can facilitate data exploration and provide fast, high-quality publication-ready graphics for this highly active area of research.

PDBe and PDBe-KB: Providing high-quality, up-to-date and integrated resources of macromolecular structures to support basic and applied research and education.

The archiving and dissemination of protein and nucleic acid structures as well as their structural, functional and biophysical annotations is an essential task that enables the broader scientific community to conduct impactful research in multiple fields of the life sciences. The Protein Data Bank in Europe (PDBe; pdbe.org) team develops and maintains several databases and web services to address this fundamental need. From data archiving as a member of the Worldwide PDB consortium (wwPDB; wwpdb.org), to the PDBe Knowledge Base (PDBe-KB; pdbekb.org), we provide data, data-access mechanisms, and visualizations that facilitate basic and applied research and education across the life sciences. Here, we provide an overview of the structural data and annotations that we integrate and make freely available. We describe the web services and data visualization tools we offer, and provide information on how to effectively use or even further develop them. Finally, we discuss the direction of our data services, and how we aim to tackle new challenges that arise from the recent, unprecedented advances in the field of structure determination and protein structure modeling.

A new method bridging graph theory and residue co-evolutionary networks for specificity determinant positions detection.

MOTIVATION: Computational studies of molecular evolution are usually performed from a multiple alignment of homologous sequences, on which sequences resulting from a common ancestor are aligned so that equivalent residues are placed in the same position. Residues frequency patterns of a full alignment or from a subset of its sequences can be highly useful for suggesting positions under selection. Most methods mapping co-evolving or specificity determinant sites are focused on positions, however, they do not consider the case for residues that are specificity determinants in one subclass, but variable in others. In addition, many methods are impractical for very large alignments, such as those obtained from Pfam, or require a priori information of the subclasses to be analyzed. RESULTS: In this paper we apply the complex networks theory, widely used to analyze co-affiliation systems in the social and ecological contexts, to map groups of functional related residues. This methodology was initially evaluated in simulated environments and then applied to four different protein families datasets, in which several specificity determinant sets and functional motifs were successfully detected. AVAILABILITY AND IMPLEMENTATION: The algorithms and datasets used in the development of this project are available on http://www.biocomp.icb.ufmg.br/biocomp/software-and-databases/networkstats/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Residue correlation networks in nuclear receptors reflect functional specialization and the formation of the nematode-specific P-box.

BACKGROUND: Nuclear receptors (NRs) are transcription factors which bind small hormones, whose evolutionary history and the presence of different functional surfaces makes them an interesting target for a correlation based analysis. RESULTS: Correlation analysis of ligand binding domains shows that correlated residue subsets arise from the differences between functional sites in different nuclear receptor subfamilies. For the DNA binding domain, particularly, the analysis shows that the main source of correlation comes from residues that regulate hormone response element specificity, and one of the conserved residue sub-sets arises due to the presence of an unusual sequence for the DNA binding motif known as P-box in nematodes, suggesting the existence of different DBD-DNA specificities in nuclear receptors. CONCLUSIONS: We conclude that DNA specificity and functional surface specialization has independently driven nuclear receptor evolution, and suggest possible binding modes for the class of divergent nuclear receptors in nematodes.