Benchmarking network propagation methods for disease gene identification.

In-silico identification of potential target genes for disease is an essential aspect of drug target discovery. Recent studies suggest that successful targets can be found through by leveraging genetic, genomic and protein interaction information. Here, we systematically tested the ability of 12 varied algorithms, based on network propagation, to identify genes that have been targeted by any drug, on gene-disease data from 22 common non-cancerous diseases in OpenTargets.

Integrated pathway clusters with coherent biological themes for target prioritisation.

Prioritising candidate genes for further experimental characterisation is an essential, yet challenging task in biomedical research. One way of achieving this goal is to identify specific biological themes that are enriched within the gene set of interest to obtain insights into the biological phenomena under study. Biological pathway data have been particularly useful in identifying functional associations of genes and/or gene sets.

Target selection for structural genomics of infectious diseases.

This chapter describes the protocols used to identify, filter, and annotate potential protein targets from an organism associated with infectious diseases. Protocols often combine computational approaches for mining information in public databases or for checking whether the protein has already been targeted for structure determination, with manual strategies that examine the literature for information on the biological role of the protein or the experimental strategies that explore the effects of knocking out the protein. Publicly available computational tools have been cited as much as possible.

Gene3D: Multi-domain annotations for protein sequence and comparative genome analysis.

Gene3D (http://gene3d.biochem.ucl.

The chemotherapeutic agent DMXAA as a unique IRF3-dependent type-2 vaccine adjuvant.

5,6-Dimethylxanthenone-4-acetic acid (DMXAA), a potent type I interferon (IFN) inducer, was evaluated as a chemotherapeutic agent in mouse cancer models and proved to be well tolerated in human cancer clinical trials. Despite its multiple biological functions, DMXAA has not been fully characterized for the potential application as a vaccine adjuvant. In this report, we show that DMXAA does act as an adjuvant due to its unique property as a soluble innate immune activator.

Functional site plasticity in domain superfamilies.

We present, to our knowledge, the first quantitative analysis of functional site diversity in homologous domain superfamilies. Different types of functional sites are considered separately. Our results show that most diverse superfamilies are very plastic in terms of the spatial location of their functional sites.

Evolutionary history of the TBP-domain superfamily.

The TATA binding protein (TBP) is an essential transcription initiation factor in Archaea and Eucarya. Bacteria lack TBP, and instead use sigma factors for transcription initiation. TBP has a symmetric structure comprising two repeated TBP domains.

Residue mutations and their impact on protein structure and function: detecting beneficial and pathogenic changes.

The present review focuses on the evolution of proteins and the impact of amino acid mutations on function from a structural perspective. Proteins evolve under the law of natural selection and undergo alternating periods of conservative evolution and of relatively rapid change. The likelihood of mutations being fixed in the genome depends on various factors, such as the fitness of the phenotype or the position of the residues in the three-dimensional structure.

New functional families (FunFams) in CATH to improve the mapping of conserved functional sites to 3D structures.

CATH version 3.5 (Class, Architecture, Topology, Homology, available at http://www.cathdb.

Gene3D: a domain-based resource for comparative genomics, functional annotation and protein network analysis.

Gene3D http://gene3d.biochem.ucl.

Detailed analysis of function divergence in a large and diverse domain superfamily: toward a refined protocol of function classification.

Some superfamilies contain large numbers of protein domains with very different functions. The ability to refine the functional classification of domains within these superfamilies is necessary for better understanding the evolution of functions and to guide function prediction of new relatives. To achieve this, a suitable starting point is the detailed analysis of functional divisions and mechanisms of functional divergence in a single superfamily.

Transient protein-protein interactions: structural, functional, and network properties.

Transient interactions, which involve protein interactions that are formed and broken easily, are important in many aspects of cellular function. Here we describe structural and functional properties of transient interactions between globular domains and between globular domains, short peptides, and disordered regions. The importance of posttranslational modifications in transient interactions is also considered.

FLORA: a novel method to predict protein function from structure in diverse superfamilies.

Predicting protein function from structure remains an active area of interest, particularly for the structural genomics initiatives where a substantial number of structures are initially solved with little or no functional characterisation. Although global structure comparison methods can be used to transfer functional annotations, the relationship between fold and function is complex, particularly in functionally diverse superfamilies that have evolved through different secondary structure embellishments to a common structural core. The majority of prediction algorithms employ local templates built on known or predicted functional residues.

The evolution of protein functions and networks: a family-centric approach.

The study of superfamilies of protein domains using a combination of structure, sequence and function data provides insights into deep evolutionary history. In the present paper, analyses of functional diversity within such superfamilies as defined in the CATH-Gene3D resource are described. These analyses focus on structure-function relationships in very large and diverse superfamilies, and on the evolution of domain superfamily members in protein-protein complexes.

PSI-2: structural genomics to cover protein domain family space.

One major objective of structural genomics efforts, including the NIH-funded Protein Structure Initiative (PSI), has been to increase the structural coverage of protein sequence space. Here, we present the target selection strategy used during the second phase of PSI (PSI-2). This strategy, jointly devised by the bioinformatics groups associated with the PSI-2 large-scale production centers, targets representatives from large, structurally uncharacterized protein domain families, and from structurally uncharacterized subfamilies in very large and diverse families with incomplete structural coverage.

Exploiting structural classifications for function prediction: towards a domain grammar for protein function.

The ability to assign function to proteins has become a major bottleneck for comprehensively understanding cellular mechanisms at the molecular level. Here we discuss the extent to which structural domain classifications can help in deciphering the complex relationship between the functions of proteins and their sequences and structures. Structural classifications are particularly helpful in understanding the mosaic manner in which new proteins and functions emerge through evolution.

Relating destabilizing regions to known functional sites in proteins.

Background: Most methods for predicting functional sites in protein 3D structures, rely on information on related proteins and cannot be applied to proteins with no known relatives. Another limitation of these methods is the lack of a well annotated set of functional sites to use as benchmark for validating their predictions. Experimental findings and theoretical considerations suggest that residues involved in function often contribute unfavorably to the native state stability.