Activity-based protein profiling of host-virus interactions

Virologists have benefited from large-scale profiling methods to discover new host-virus interactions and to learn about the mechanisms of pathogenesis. One such technique, referred to as activity-based protein profiling (ABPP), uses active site-directed probes to monitor the functional state of enzymes, taking into account post-translational interactions and modifications. ABPP gives insight into the catalytic activity of enzyme families that does not necessarily correlate with protein abundance. ABPP has been used to investigate several viruses and their interactions with their hosts. Differential enzymatic activity induced by viruses has been monitored using ABPP. In this review, we present recent advances and trends involving the use of ABPP methods in understanding host-virus interactions and in identifying novel targets for diagnostic and therapeutic applications.     

Activity-based protein profiling: an enabling technology in chemical biology research

Activity-based protein profiling (ABPP) is one of the main driving forces in chemical biology and one of the most visible areas where organic chemistry contributes to chemical biology research. In recent years, ABPP research has gradually made the transfer from the relatively easy target enzymes (for instance serine hydrolases, cysteine and threonine proteases) toward targeting enzymes that are intrinsically more difficult to address. These include less abundant enzymes, enzymes that do not employ a nucleophilic amino acid residue in their active site and enzymes more particular with respect to their substrate. At the same time, ABPP has started to make a tangible impact on clinical research.     

ProFAT: a web-based tool for the functional annotation of protein sequences

Background  

The functional annotation of proteins relies on published information concerning their close and remote homologues in sequence databases. Evidence for remote sequence similarity can be further strengthened by a similar biological background of the query sequence and identified database sequences. However, few tools exist so far, that provide a means to include functional information in sequence database searches.     

Probabilistic annotation of protein sequences based on functional classifications

Background  

One of the most evident achievements of bioinformatics is the development of methods that transfer biological knowledge from characterised proteins to uncharacterised sequences. This mode of protein function assignment is mostly based on the detection of sequence similarity and the premise that functional properties are conserved during evolution. Most automatic approaches developed to date rely on the identification of clusters of homologous proteins and the mapping of new proteins onto these clusters, which are expected to share functional characteristics.     

ProSAT: functional annotation of protein 3D structures

ProSAT (for Protein Structure Annotation Tool) is a tool to facilitate interactive visualization of non-structure-based functional annotations in protein 3D structures. It performs automated mapping of the functional annotations onto the protein structure and allows functional sites to be readily identified upon visualization. The current version of ProSAT can be applied to large datasets of protein structures for fast visual identification of active and other functional sites derived from the SwissProt and Prosite databases.     

Activity-based protein profiling implicates urokinase activation as a key step in human fibrosarcoma intravasation

Entry of malignant cells into the vasculature (i.e. intravasation) requires proteolytic remodeling of the extracellular matrix so that tumor cells may pass through the local stroma and penetrate the vessel wall. The circulatory system then provides a means of transporting tumor cells to distant sites where they extravasate and establish metastatic lesions. This study utilizes activity-based protein profiling to compare the active serine hydrolase repertoire in high intravasating (HT-hi/diss) and low intravasating (HT-lo/diss) variants of the human fibrosarcoma HT-1080 cell line to determine which enzyme(s) play a role in intravasation. Activity-based protein profiling revealed multiple serine hydrolases with altered activity between HT-hi/diss and HT-lo/diss cells, with the largest difference being the activity of urokinase-type plasminogen activator (uPA). Levels of inactive uPA zymogen were similar between the two cell variants, but only HT-hi/diss conditioned medium contained active uPA, suggesting that uPA activation may contribute to the enhanced intravasation of HT-hi/diss cells. To analyze the role of uPA activity specifically in the process of intravasation, we grafted cells from the two HT-1080 variants onto the chorioallantoic membrane of chick embryos and measured levels of tumor cell intravasation in the distal chorioallantoic membrane using quantitative human-specific Alu PCR. Inhibition of uPA activity with natural (plasminogen activator inhibitor-1) or synthetic (amiloride) inhibitors diminished HT-hi/diss Matrigel invasion in vitro and intravasation and metastasis in vivo. Additionally, treatment of HT-lo/diss tumors with exogenous active uPA increased the number of intravasated cells in vivo. These results indicate that active uPA promotes tumor cell intravasation and that uPA activation appears to be a key step in tumor progression.     

Partially-supervised protein subclass discovery with simultaneous annotation of functional residues

Background  

The study of functional subfamilies of protein domain families and the identification of the residues which determine substrate specificity is an important question in the analysis of protein domains. One way to address this question is the use of clustering methods for protein sequence data and approaches to predict functional residues based on such clusterings. The locations of putative functional residues in known protein structures provide insights into how different substrate specificities are reflected on the protein structure level.     

Activity-based proteomics: enzymatic activity profiling in complex proteomes

Summary. In the postgenomic era new technologies are emerging for global analysis of protein function. The introduction of active site-directed chemical probes for enzymatic activity profiling in complex mixtures, known as activity-based proteomics has greatly accelerated functional annotation of proteins. Here we review probe design for different enzyme classes including serine hydrolases, cysteine proteases, tyrosine phosphatases, glycosidases, and others. These probes are usually detected by their fluorescent, radioactive or affinity tags and their protein targets are analyzed using established proteomics techniques. Recent developments, such as the design of probes for in vivo analysis of proteomes, as well as microarray technologies for higher throughput screenings of protein specificity and the application of activity-based probes for drug screening are highlighted. We focus on biological applications of activity-based probes for target and inhibitor discovery and discuss challenges for future development of this field.     

Functional annotation strategy for protein structures

Whole-genome sequencing projects are a major source of unknown function proteins. However, as predicting protein function from sequence remains a difficult task, research groups recently started to use 3D protein structures and structural models to bypass it. MED-SuMo compares protein surfaces analyzing the composition and spatial distribution of specific chemical groups (hydrogen bond donor, acceptor, positive, negative, aromatic, hydrophobic, guanidinium, hydroxyl, acyl and glycine). It is able to recognize proteins that have similar binding sites and thus, may perform similar functions. We present here a fine example which points out the interest of MED-SuMo approach for functional structural annotation.     

Gene annotation and network inference by phylogenetic profiling

Background  

Phylogenetic analysis is emerging as one of the most informative computational methods for the annotation of genes and identification of evolutionary modules of functionally related genes. The effectiveness with which phylogenetic profiles can be utilized to assign genes to pathways depends on an appropriate measure of correlation between gene profiles, and an effective decision rule to use the correlate. Current methods, though useful, perform at a level well below what is possible, largely because performance of the latter deteriorates rapidly as coverage increases.     

DIG--a system for gene annotation and functional discovery

SUMMARY: We describe a database and information discovery system named DIG (Duke Integrated Genomics) designed to facilitate the process of gene annotation and the discovery of functional context. The DIG system collects and organizes gene annotation and functional information, and includes tools that support an understanding of genes in a functional context by providing a framework for integrating and visualizing gene expression, protein interaction and literature-based interaction networks.