Functional annotation by sequence-weighted structure alignments: statistical analysis and case studies from the Protein 3000 structural genomics project in Japan

Genomes to hits in silico - a country path today, a highway tomorrow: a case study of chikungunya

These are exciting times for bioinformaticians, computational biologists and drug designers with the genome and proteome sequences and related structural databases growing at an accelerated pace. The post-genomic era has triggered high expectations for a rapid and successful treatment of diseases. However, in this biological information rich and functional knowledge poor scenario, the challenges are indeed grand, no less than the assembly of the genome of the whole organism. These include functional annotation of genes, identification of druggable targets, prediction of three-dimensional structures of protein targets from their amino acid sequences, arriving at lead compounds for these targets followed by a transition from bench to bedside. We propose here a "Genome to Hits In Silico" strategy (called Dhanvantari) and illustrate it on Chikungunya virus (CHIKV). "Genome to hits" is a novel pathway incorporating a series of steps such as gene prediction, protein tertiary structure determination, active site identification, hit molecule generation, docking and scoring of hits to arrive at lead compounds. The current state of the art for each of the steps in the pathway is high-lighted and the feasibility of creating an automated genome to hits assembly line is discussed.

Structure-guided rule-based annotation of protein functional sites in UniProt knowledgebase

The rapid growth of protein sequence databases has necessitated the development of methods to computationally derive annotation for uncharacterized entries. Most such methods focus on "global" annotation, such as molecular function or biological process. Methods to supply high-accuracy "local" annotation to functional sites based on structural information at the level of individual amino acids are relatively rare. In this chapter we will describe a method we have developed for annotation of functional residues within experimentally-uncharacterized proteins that relies on position-specific site annotation rules (PIR Site Rules) derived from structural and experimental information. These PIR Site Rules are manually defined to allow for conditional propagation of annotation. Each rule specifies a tripartite set of conditions whereby candidates for annotation must pass a whole-protein classification test (that is, have end-to-end match to a whole-protein-based HMM), match a site-specific profile HMM and, finally, match functionally and structurally characterized residues of a template. Positive matches trigger the appropriate annotation for active site residues, binding site residues, modified residues, or other functionally important amino acids. The strict criteria used in this process have rendered high-confidence annotation suitable for UniProtKB/Swiss-Prot features.

SeSAW: balancing sequence and structural information in protein functional mapping

Motivation: Functional similarity between proteins is evident at both the sequence and structure levels. SeSAW is a web-based program for identifying functionally or evolutionarily conserved motifs in protein structures by locating sequence and structural similarities, and quantifying these at the level of individual residues. Results can be visualized in 2D, as annotated alignments, or in 3D, as structural superpositions. An example is given for both an experimentally determined query structure and a homology model.

Availability and Implementation: The web server is located at http://www.pdbj.org/SeSAW/

Contact:standley@ifrec.osaka-u.ac.jp

A single polymorphic amino acid on Toxoplasma gondii kinase ROP16 determines the direct and strain-specific activation of Stat3

Infection by Toxoplasma gondii down-regulates the host innate immune responses, such as proinflammatory cytokine production, in a Stat3-dependent manner. A forward genetic approach recently demonstrated that the type II strain fails to suppress immune responses because of a potential defect in a highly polymorphic parasite-derived kinase, ROP16. We generated ROP16-deficient type I parasites by reverse genetics and found a severe defect in parasite-induced Stat3 activation, culminating in enhanced production of interleukin (IL) 6 and IL-12 p40 in the infected macrophages. Furthermore, overexpression of ROP16 but not ROP18 in mammalian cells resulted in Stat3 phosphorylation and strong activation of Stat3-dependent promoters. In addition, kinase-inactive ROP16 failed to activate Stat3. Comparison of type I and type II ROP16 revealed that a single amino acid substitution in the kinase domain determined the strain difference in terms of Stat3 activation. Moreover, ROP16 bound Stat3 and directly induced phosphorylation of this transcription factor. These results formally establish an essential and direct requirement of ROP16 in parasite-induced Stat3 activation and the significance of a single amino acid replacement in the function of type II ROP16.

Comprehensive structural classification of ligand-binding motifs in proteins

Comprehensive knowledge of protein-ligand interactions should provide a useful basis for annotating protein functions, studying protein evolution, engineering enzymatic activity, and designing drugs. To investigate the diversity and universality of ligand-binding sites in protein structures, we conducted the all-against-all atomic-level structural comparison of over 180,000 ligand-binding sites found in all the known structures in the Protein Data Bank by using a recently developed database search and alignment algorithm. By applying a hybrid top-down-bottom-up clustering analysis to the comparison results, we determined approximately 3000 well-defined structural motifs of ligand-binding sites. Apart from a handful of exceptions, most structural motifs were found to be confined within single families or superfamilies, and to be associated with particular ligands. Furthermore, we analyzed the components of the similarity network and enumerated more than 4000 pairs of structural motifs that were shared across different protein folds.