Predicting Protein Dynamics and Allostery Using Multi-Protein Atomic Distance Constraints.

The related concepts of protein dynamics, conformational ensembles and allostery are often difficult to study with molecular dynamics (MD) due to the timescales involved. We present ExProSE (Exploration of Protein Structural Ensembles), a distance geometry-based method that generates an ensemble of protein structures from two input structures. ExProSE provides a unified framework for the exploration of protein structure and dynamics in a fast and accessible way.

Comparative proteomics of cucurbit phloem indicates both unique and shared sets of proteins.

Cucurbits are well-studied models for phloem biology but unusually possess both fascicular phloem (FP) within vascular bundles and additional extrafascicular phloem (EFP). Although the functional differences between the two systems are not yet clear, sugar analysis and limited protein profiling have established that FP and EFP have divergent compositions. Here we report a detailed comparative proteomics study of FP and EFP in two cucurbits, pumpkin and cucumber.

Exploring the cellular basis of human disease through a large-scale mapping of deleterious genes to cell types.

Background: Each cell type found within the human body performs a diverse and unique set of functions, the disruption of which can lead to disease. However, there currently exists no systematic mapping between cell types and the diseases they can cause.

Methods: In this study, we integrate protein-protein interaction data with high-quality cell-type-specific gene expression data from the FANTOM5 project to build the largest collection of cell-type-specific interactomes created to date.

Genome3D: exploiting structure to help users understand their sequences.

Genome3D (http://www.genome3d.eu) is a collaborative resource that provides predicted domain annotations and structural models for key sequences.

Using a periclinal chimera to unravel layer-specific gene expression in plants.

Plant organs are made from multiple cell types, and defining the expression level of a gene in any one cell or group of cells from a complex mixture is difficult. Dicotyledonous plants normally have three distinct layers of cells, L1, L2 and L3. Layer L1 is the single layer of cells making up the epidermis, layer L2 the single cell sub-epidermal layer and layer L3 constitutes the rest of the internal cells.

RAPPORT: running scientific high-performance computing applications on the cloud.

Cloud computing infrastructure is now widely used in many domains, but one area where there has been more limited adoption is research computing, in particular for running scientific high-performance computing (HPC) software. The Robust Application Porting for HPC in the Cloud (RAPPORT) project took advantage of existing links between computing researchers and application scientists in the fields of bioinformatics, high-energy physics (HEP) and digital humanities, to investigate running a set of scientific HPC applications from these domains on cloud infrastructure. In this paper, we focus on the bioinformatics and HEP domains, describing the applications and target cloud platforms.

Genome3D: a UK collaborative project to annotate genomic sequences with predicted 3D structures based on SCOP and CATH domains.

Genome3D, available at http://www.genome3d.eu, is a new collaborative project that integrates UK-based structural resources to provide a unique perspective on sequence-structure-function relationships.

Optimal contact definition for reconstruction of contact maps.

Background: Contact maps have been extensively used as a simplified representation of protein structures. They capture most important features of a protein's fold, being preferred by a number of researchers for the description and study of protein structures. Inspired by the model's simplicity many groups have dedicated a considerable amount of effort towards contact prediction as a proxy for protein structure prediction.

Defining an essence of structure determining residue contacts in proteins.

The network of native non-covalent residue contacts determines the three-dimensional structure of a protein. However, not all contacts are of equal structural significance, and little knowledge exists about a minimal, yet sufficient, subset required to define the global features of a protein. Characterisation of this "structural essence" has remained elusive so far: no algorithmic strategy has been devised to-date that could outperform a random selection in terms of 3D reconstruction accuracy (measured as the Ca RMSD).

Designing evolvable libraries using multi-body potentials.

Novel high-throughput technologies for directed evolution enable experimental coverage of an impressive number of sequences. Nevertheless, the success of such experiments hinges on the initial sequence libraries. Here we consider the computational design of smart focused libraries and review insights from experimental strategies and theoretic advances in modelling their energy landscapes.

Optimized null model for protein structure networks.

Much attention has recently been given to the statistical significance of topological features observed in biological networks. Here, we consider residue interaction graphs (RIGs) as network representations of protein structures with residues as nodes and inter-residue interactions as edges. Degree-preserving randomized models have been widely used for this purpose in biomolecular networks.

Residue contact-count potentials are as effective as residue-residue contact-type potentials for ranking protein decoys.

Background: For over 30 years potentials of mean force have been used to evaluate the relative energy of protein structures. The most commonly used potentials define the energy of residue-residue interactions and are derived from the empirical analysis of the known protein structures. However, single-body residue 'environment' potentials, although widely used in protein structure analysis, have not been rigorously compared to these classical two-body residue-residue interaction potentials.

Detection of protein catalytic residues at high precision using local network properties.

Background: Identifying the active site of an enzyme is a crucial step in functional studies. While protein sequences and structures can be experimentally characterized, determining which residues build up an active site is not a straightforward process. In the present study a new method for the detection of protein active sites is introduced.