Benoit H. Dessailly

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. We review techniques used in the detection of the different types of transient protein-protein interactions. We also look at the role of transient interactions within protein-protein interaction networks and consider their contribution to different aspects of these networks.

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. These very large families are extremely diverse both structurally and functionally, and are highly overrepresented in known proteomes. On the basis of several metrics, we then discuss to what extent PSI-2, during its first 3 years, has increased the structural coverage of genomes, and contributed structural and functional novelty. Together, the results presented here suggest that PSI-2 is successfully meeting its objectives and provides useful insights into structural and functional space.

Exploring the structure and function paradigm

Advances in protein structure determination, led by the structural genomics initiatives have increased the proportion of novel folds deposited in the Protein Data Bank. However, these structures are often not accompanied by functional annotations with experimental confirmation. In this review, we reassess the meaning of structural novelty and examine its relevance to the complexity of the structure-function paradigm. Recent advances in the prediction of protein function from structure are discussed, as well as new sequence-based methods for partitioning large, diverse superfamilies into biologically meaningful clusters. Obtaining structural data for these functionally coherent groups of proteins will allow us to better understand the relationship between structure and function.

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

Gene3D http://gene3d.biochem.ucl.ac.uk is a comprehensive database of protein domain assignments for sequences from the major sequence databases. Domains are directly mapped from structures in the CATH database or predicted using a library of representative profile HMMs derived from CATH superfamilies. As previously described, Gene3D integrates many other protein family and function databases. These facilitate complex associations of molecular function, structure and evolution. Gene3D now includes a domain functional family (FunFam) level below the homologous superfamily level assignments. Additions have also been made to the interaction data. More significantly, to help with the visualization and interpretation of multi-genome scale data sets, we have developed a new, revamped website. Searching has been simplified with more sophisticated filtering of results, along with new tools based on Cytoscape Web, for visualizing protein–protein interaction networks, differences in domain composition between genomes and the taxonomic distribution of individual superfamilies.

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

Gene3D (http://gene3d.biochem.ucl.ac.uk) is a database of protein domain structure annotations for protein sequences. Domains are predicted using a library of profile HMMs from 2738 CATH superfamilies. Gene3D assigns domain annotations to Ensembl and UniProt sequence sets including >6000 cellular genomes and >20 million unique protein sequences. This represents an increase of 45% in the number of protein sequences since our last publication. Thanks to improvements in the underlying data and pipeline, we see large increases in the domain coverage of sequences. We have expanded this coverage by integrating Pfam and SUPERFAMILY domain annotations, and we now resolve domain overlaps to provide highly comprehensive composite multi-domain architectures. To make these data more accessible for comparative genome analyses, we have developed novel search algorithms for searching genomes to identify related multi-domain architectures. In addition to providing domain family annotations, we have now developed a pipeline for 3D homology modelling of domains in Gene3D. This has been applied to the human genome and will be rolled out to other major organisms over the next year.

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. This is partly because they provide reliable and concrete domain definitions and enable the detection of very remote structural similarities and homologies. It is also because structural data can illuminate more clearly the mechanisms by which a broader functional repertoire can emerge during evolution.

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. Here, we present such a detailed analysis in the superfamily of HUP domains. A biologically meaningful functional classification of HUP domains is obtained manually. Mechanisms of function diversification are investigated in detail using this classification. We observe that structural motifs play an important role in shaping broad functional divergence, whereas residue-level changes shape diversity at a more specific level. In parallel we examine the ability of an automated protocol to capture the biologically meaningful classification, with a view to automatically extending this classification in the future.

Rigid-body ligand recognition drives cytotoxic T-lymphocyte antigen 4 (CTLA-4) receptor triggering

The inhibitory T-cell surface-expressed receptor, cytotoxic T lymphocyte-associated antigen-4 (CTLA-4), which belongs to the class of cell surface proteins phosphorylated by extrinsic tyrosine kinases that also includes antigen receptors, binds the related ligands, B7-1 and B7-2, expressed on antigen-presenting cells. Conformational changes are commonly invoked to explain ligand-induced “triggering” of this class of receptors. Crystal structures of ligand-bound CTLA-4 have been reported, but not the apo form, precluding analysis of the structural changes accompanying ligand binding. The 1.8-Å resolution structure of an apo human CTLA-4 homodimer emphasizes the shared evolutionary history of the CTLA-4/CD28 subgroup of the immunoglobulin superfamily and the antigen receptors. The ligand-bound and unbound forms of both CTLA-4 and B7-1 are remarkably similar, in marked contrast to B7-2, whose binding to CTLA-4 has elements of induced fit. Isothermal titration calorimetry reveals that ligand binding by CTLA-4 is enthalpically driven and accompanied by unfavorable entropic changes. The similarity of the thermodynamic parameters determined for the interactions of CTLA-4 with B7-1 and B7-2 suggests that the binding is not highly specific, but the conformational changes observed for B7-2 binding suggest some level of selectivity. The new structure establishes that rigid-body ligand interactions are capable of triggering CTLA-4 phosphorylation by extrinsic kinase(s).

Function Diversity Within Folds and Superfamilies

The structural genomics initiatives significantly increased the numbers of three-dimensional structures available for proteins of unknown function. However, the extent to which structural information helps understanding function is still a matter of debate. Here, the value of detecting structural relationships at different levels (typically, fold and superfamily ) for transferring functional annotations between proteins is reviewed. First, function diversity of proteins sharing the same fold is investigated, and it is shown that although the identification of a fold can in some cases provide clues on functional properties, the diversity of functions within a fold can be such that this information is very limited for some particularly diverse folds (e.g. super-folds). Next, since structural data can help detecting homology in the absence of sequence similarity, function diversity between proteins from the same superfamily (homologous proteins) is analysed. The evolutionary causes and the mechanisms that have generated the observed functional diversity between related proteins are discussed, and helpful tools for the correlated analysis of structure, function and evolution are reviewed.

Exploiting Protein Structures to Predict Protein Functions

The exponential growth of experimentally determined protein structures in the Protein Data Bank (PDB) has provided structural data for an ever increasing proportion of genomic sequences. In combination with enhanced functional annotation from sequence, it has become possible to predict protein function from structure. In this chapter we discuss a range of methods which aim to recognise enzyme active sites and predict protein-ligand interactions. We then focus on algorithms developed as part of the CATH database of structural domains, where an evolutionary approach is used to recognise proteins with similar functions. While protein domains that exhibit the same structural fold tend to display related functional activities, there are a several large domain structure superfamilies that show a high degree of functional diversity. In these cases, we have built novel tools (FLORA and GeMMA) which are able to effectively identify sub-families of functionally linked domains, where standard methods of homologue detection (e.g. sequence profile and global structure alignment) fail.