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Characterization of the functional role of the N-glycans in the AMPA receptor ligand-binding domain.

The ligand-binding domains of AMPA receptor subunits carry two conserved N-glycosylation sites. In order to gain insight into the functional role of the corresponding N-glycans, we examined how the elimination of glycosylation at these sites (N407 and N414) affects the ligand-binding characteristics, structural stability, cell-surface expression, and channel properties of homomeric GluR-D (GluR4) receptor and its soluble ligand-binding domain (S1S2). GluR-D S1S2 protein expressed as a secreted protein in insect cells was found to be glycosylated at N407 and N414. No major differences in the ligand-binding properties were observed between the 'wild-type' S1S2 and non-glycosylated N407D/N414Q double mutant, or between S1S2 proteins expressed in the presence or absence of tunicamycin, an inhibitor of N-glycosylation. Purified glycosylated and non-glycosylated S1S2 proteins also showed similar thermostabilities as determined by CD spectroscopy. Full-length homomeric GluR-D receptor with N407D/N414Q mutation was expressed on the surface of HEK293 cells like the wild-type GluR-D. In outside-out patches, GluR-D and the N407D/N414Q mutant produced similar rapidly desensitizing current responses to glutamate and AMPA. We therefore report that the two conserved ligand-binding domain glycans do not play any major role in receptor-ligand interactions, do not impart a stabilizing effect on the ligand-binding domain, and are not critical for the formation and surface localization of homomeric GluR-D AMPA receptors in HEK293 cells.

Amino Acid Substitution↗

The Arg617-Arg618 cleavage site in the C-terminal domain of PC1 plays a major role in the processing and targeting of the enzyme within the regulated secretory pathway.

The C-terminal domain of the prohormone convertase PC1 is involved in targeting of the enzyme to secretory granules in neuroendocrine cells and is subsequently processed in this compartment at an Arg617-Arg618 site. Three other dibasics are found in the C-terminal domain of mouse PC1. Here, we examined the role of the four dibasics in targeting PC1 to secretory granules. All 15 possible combinations of dibasic mutations were performed. Wild-type (WT) and mutant PC1 were stably expressed in neuroendocrine PC12 cells that lacked endogenous PC1. Processing, secretion and intracellular localization of PC1 and its mutants were analyzed. Leaving intact Arg617-Arg618 and mutating any combination of the three other dibasics yielded proteins that were stored and processed in secretory granules, similarly to WT PC1. Mutating Arg617-Arg618 alone or with any one of the three remaining dibasics generated proteins that were efficiently stored in secretory granules but were not processed further. Mutating Arg617-Arg618 with more than one of the remaining dibasics produced proteins that reached the TGN but were not stored in secretory granules and exited the cells through the constitutive secretory pathway. These data demonstrate that the Arg617-Arg618 plays a prominent role in targeting PC1 to secretory granules.

Amino Acid Substitution↗

Structural characterization of the cysteine-rich domain of TFIIH p44 subunit.

In an effort to understand the structure function relationship of TFIIH, a transcription/repair factor, we focused our attention on the p44 subunit, which plays a central role in both mechanisms. The amino-terminal portion of p44 has been shown to be involved in the regulation of the XPD helicase activity; here we show that its carboxyl-terminal domain is essential for TFIIH transcription activity and that it binds three zinc atoms through two independent modules. The first contains a C4 zinc finger motif, whereas the second is characterized by a CX(2)CX(2-4)FCADCD motif, corresponding to interleaved zinc binding sites. The solution structure of this second module reveals an unexpected homology with the regulatory domain of protein kinase C and provides a framework to study its role at the molecular level.

Amino Acid Sequence↗

How dihydrolipoamide dehydrogenase-binding protein binds dihydrolipoamide dehydrogenase in the human pyruvate dehydrogenase complex.

The dihydrolipoamide dehydrogenase-binding protein (E3BP) and the dihydrolipoamide acetyltransferase (E2) component enzyme form the structural core of the human pyruvate dehydrogenase complex by providing the binding sites for two other component proteins, dihydrolipoamide dehydrogenase (E3) and pyruvate dehydrogenase (E1), as well as pyruvate dehydrogenase kinases and phosphatases. Despite a high similarity between the primary structures of E3BP and E2, the E3-binding domain of human E3BP is highly specific to human E3, whereas the E1-binding domain of human E2 is highly specific to human E1. In this study, we characterized binding of human E3 to the E3-binding domain of E3BP by x-ray crystallography at 2.6-angstroms resolution, and we used this structural information to interpret the specificity for selective binding. Two subunits of E3 form a single recognition site for the E3-binding domain of E3BP through their hydrophobic interface. The hydrophobic residues Pro133, Pro154, and Ile157 in the E3-binding domain of E3BP insert themselves into the surface of both E3 polypeptide chains. Numerous ionic and hydrogen bonds between the residues of three interacting polypeptide chains adjacent to the central hydrophobic patch add to the stability of the subcomplex. The specificity of pairing for human E3BP with E3 is interpreted from its subcomplex structure to be most likely due to conformational rigidity of the binding fragment of the E3-binding domain of E3BP and its exquisite amino acid match with the E3 target interface.

Amino Acid Sequence↗

Target selection and determination of function in structural genomics.

The first crucial step in any structural genomics project is the selection and prioritization of target proteins for structure determination. There may be a number of selection criteria to be satisfied, including that the proteins have novel folds, that they be representatives of large families for which no structure is known, and so on. The better the selection at this stage, the greater is the value of the structures obtained at the end of the experimental process. This value can be further enhanced once the protein structures have been solved if the functions of the given proteins can also be determined. Here we describe the methods used at either end of the experimental process: firstly, sensitive sequence comparison techniques for selecting a high-quality list of target proteins, and secondly the various computational methods that can be applied to the eventual 3D structures to determine the most likely biochemical function of the proteins in question.

Amino Acid Motifs↗

Architecture of basic building blocks in protein and domain structural interaction networks.

MOTIVATION: The structural interaction of proteins and their domains in networks is one of the most basic molecular mechanisms for biological cells. Topological analysis of such networks can provide an understanding of and solutions for predicting properties of proteins and their evolution in terms of domains. A single paradigm for the analysis of interactions at different layers, such as domain and protein layers, is needed. RESULTS: Applying a colored vertex graph model, we integrated two basic interaction layers under a unified model: (1) structural domains and (2) their protein/complex networks. We identified four basic and distinct elements in the model that explains protein interactions at the domain level. We searched for motifs in the networks to detect their topological characteristics using a pruning strategy and a hash table for rapid detection. We obtained the following results: first, compared with a random distribution, a substantial part of the protein interactions could be explained by domain-level structural interaction information. Second, there were distinct kinds of protein interaction patterns classified by specific and distinguishable numbers of domains. The intermolecular domain interaction was the most dominant protein interaction pattern. Third, despite the coverage of the protein interaction information differing among species, the similarity of their networks indicated shared architectures of protein interaction network in living organisms. Remarkably, there were only a few basic architectures in the model (>10 for a 4-node network topology), and we propose that most biological combinations of domains into proteins and complexes can be explained by a small number of key topological motifs. CONTACT: doheon@kaist.ac.kr.

Animals↗

PIBASE: a comprehensive database of structurally defined protein interfaces.

MOTIVATION: In recent years, the Protein Data Bank (PDB) has experienced rapid growth. To maximize the utility of the high resolution protein-protein interaction data stored in the PDB, we have developed PIBASE, a comprehensive relational database of structurally defined interfaces between pairs of protein domains. It is composed of binary interfaces extracted from structures in the PDB and the Probable Quaternary Structure server using domain assignments from the Structural Classification of Proteins and CATH fold classification systems. RESULTS: PIBASE currently contains 158,915 interacting domain pairs between 105,061 domains from 2125 SCOP families. A diverse set of geometric, physiochemical and topologic properties are calculated for each complex, its domains, interfaces and binding sites. A subset of the interface properties are used to remove interface redundancy within PDB entries, resulting in 20,912 distinct domain-domain interfaces. The complexes are grouped into 989 topological classes based on their patterns of domain-domain contacts. The binary interfaces and their corresponding binding sites are categorized into 18,755 and 30,975 topological classes, respectively, based on the topology of secondary structure elements. The utility of the database is illustrated by outlining several current applications. AVAILABILITY: The database is accessible via the world wide web at http://salilab.org/pibase SUPPLEMENTARY INFORMATION: http://salilab.org/pibase/suppinfo.html.

Algorithms↗

Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites.

MOTIVATION: Identifying the location of ligand binding sites on a protein is of fundamental importance for a range of applications including molecular docking, de novo drug design and structural identification and comparison of functional sites. Here, we describe a new method of ligand binding site prediction called Q-SiteFinder. It uses the interaction energy between the protein and a simple van der Waals probe to locate energetically favourable binding sites. Energetically favourable probe sites are clustered according to their spatial proximity and clusters are then ranked according to the sum of interaction energies for sites within each cluster. RESULTS: There is at least one successful prediction in the top three predicted sites in 90% of proteins tested when using Q-SiteFinder. This success rate is higher than that of a commonly used pocket detection algorithm (Pocket-Finder) which uses geometric criteria. Additionally, Q-SiteFinder is twice as effective as Pocket-Finder in generating predicted sites that map accurately onto ligand coordinates. It also generates predicted sites with the lowest average volumes of the methods examined in this study. Unlike pocket detection, the volumes of the predicted sites appear to show relatively low dependence on protein volume and are similar in volume to the ligands they contain. Restricting the size of the pocket is important for reducing the search space required for docking and de novo drug design or site comparison. The method can be applied in structural genomics studies where protein binding sites remain uncharacterized since the 86% success rate for unbound proteins appears to be only slightly lower than that of ligand-bound proteins. AVAILABILITY: Both Q-SiteFinder and Pocket-Finder have been made available online at http://www.bioinformatics.leeds.ac.uk/qsitefinder and http://www.bioinformatics.leeds.ac.uk/pocketfinder

Algorithms↗

Protein domains and conformational changes in the activation of RepA, a DNA replication initiator.

RepA is the DNA replication initiator protein of the Pseudomonas plasmid pPS10. RepA has a dual function: as a dimer, it binds to an inversely-repeated sequence acting as a repressor of its own synthesis; as a monomer, RepA binds to four directly-repeated sequences to constitute a specialized nucleoprotein complex responsible for the initiation of DNA replication. We have previously shown that a Leucine Zipper-like motif (LZ) at the N-terminus of RepA is responsible for protein dimerization. In this paper we characterize the existence in RepA of two protein globular domains C-terminal to the LZ. We propose that dissociation of RepA dimers into monomers results in a conformational change from a compact arrangement of both domains, competent for binding to the operator, to an extended species that is suited for iteron binding. This model establishes the structural basis for the activation of DNA replication initiators in plasmids from Gram-negative bacteria.

Amino Acid Sequence↗

The SBASE protein domain library, release 9.0: an online resource for protein domain identification.

SBASE (http://www.icgeb.trieste.it/sbase) is an online resource of protein domain sequences designed to facilitate detection of domain homologies based on a simple database search. The ninth release of the SBASE library of protein domain sequences contains 320 000 annotated structural, functional, ligand-binding and topogenic segments of proteins clustered into over 3481 domain groups and 483 protein families. Domain identification and functional prediction are based on a comparison of BLAST search outputs with a knowledge base of within-group ('self') and out-of-group ('non-self') similarities of the known domain groups. This is a memory-based approach wherein class-specific similarity functions are automatically learned from the database [Stanfill,C. and Waltz,D. (1986) COMMUN: ACM, 29, 1213-1228].

Animals↗

Recent improvements to the PROSITE database.

The PROSITE database consists of a large collection of biologically meaningful signatures that are described as patterns or profiles. Each signature is linked to documentation that provides useful biological information on the protein family, domain or functional site identified by the signature. The PROSITE web page has been redesigned and several tools have been implemented to help the user discover new conserved regions in their own proteins and to visualize domain arrangements. We also introduced the facility to search PDB with a PROSITE entry or a user's pattern and visualize matched positions on 3D structures. The latest version of PROSITE (release 18.17 of November 30, 2003) contains 1676 entries. The database is accessible at http://www.expasy.org/prosite/.

Amino Acid Motifs↗

Conserved structural features and sequence patterns in the GroES fold family.

An irregular, all beta-class of proteins, comprising members of the chaperonin-10, quinone oxidoreductase, glucose dehydrogenase and alcohol dehydrogenase families has earlier been classified as the GroES fold. In this communication, we present an extensive analysis of sequences and three dimensional structures of proteins belonging to this family. The individual protein structures can be superposed within 1.6 A for more than 60 structurally equivalent residues. The comparisons show a highly conserved hydrophobic core and conservation of a few key residues. A glycyl-aspartate dipeptide is suggested as being critical for the maintenance of the GroES fold. One of the surprising findings of the study is the non-conservative nature of Ile to Leu mutations in the protein core, although Ile to Val mutations are found to occur frequently.

Alcohol Dehydrogenase↗

Use of covariance analysis for the prediction of structural domain boundaries from multiple protein sequence alignments.

Current methods for identification of domains within protein sequences require either structural information or the identification of homologous domain sequences in different sequence contexts. Knowledge of structural domain boundaries is important for fold recognition experiments and structural determination by X-ray crystallography or nuclear magnetic resonance spectroscopy using the divide-and-conquer approach. Here, a new and conceptually simple method for the identification of structural domain boundaries in multiple protein sequence alignments is presented. Analysis of covariance at positions within the alignment is first used to predict 3D contacts. By the nature of the domain as an independent folding unit, inter-domain predicted contacts are fewer than intra-domain predicted contacts. By analysing all possible domain boundaries and constructing a smoothed profile of predicted contact density (PCD), true structural domain boundaries are predicted as local profile minima associated with low PCD. A training data set is constructed from 52 non-homologous two-domain protein sequences of known 3D structure and used to determine optimal parameters for the profile analysis. The alignments in the training data set contained 48 +/- 17 (mean +/- SD) sequences and lengths of 257 +/- 121 residues. Of the 47 alignments yielding predictions, 35% of true domain boundaries are predicted to within 15 amino acids by the local profile minimum with the lowest profile value. Including predictions from the second- and third-lowest local minima increases the correct domain boundary coverage to 60%, whereas the lowest five local minima cover 79% of correct domain boundaries. Through further profile analysis, criteria are presented which reliably identify subsets of more accurate predictions. Retrospective analysis of CASP3 targets shows predictions of sufficient accuracy to enable dramatically improved fold recognition results. Finally, a prediction is made for geminivirus AL1 protein which is in full agreement with biochemical data, yielding a plausible, novel threading result.

DNA-Binding Proteins↗

Hepatitis C virus core protein selectively inhibits synthesis and accumulation of p21/Waf1 and certain nuclear proteins.

By using a vaccinia virus-T7 expression system, possible effects of hepatitis C virus (HCV) core protein on synthesis and accumulation of host cellular proteins transiently expressed in cultured cells were analyzed. Immunoblot and immunofluorescence analyses revealed that synthesis and accumulation of certain nuclear proteins, such as p21/Waf1, p53, proliferating cell nuclear antigen and c-Fos, were strongly inhibited by HCV core protein. On the other hand, synthesis and accumulation of cytoplasmic proteins, such as 2'-5'-oligoadenylate synthetase (2'-5'-OAS), RNase L and MEK1, were barely affected by HCV core protein. Northern blot analysis showed that the degrees of mRNA expression for those proteins did not differ between HCV core protein-expressing cells and the control, suggesting that the inhibition occurred at the post-transcription level. Pulse-labeling analysis suggested that HCV core protein strongly inhibited synthesis of p21/Waf1 at the translation level. Once being accumulated in the nucleus, p21/Waf1 stability was not significantly affected by HCV core protein. Mutants of HCV core protein C-terminally deleted by 18 or 41 amino acids (aa), which were localized almost exclusively in the nucleus, lost their ability to inhibit synthesis/accumulation of p21/Waf1 whereas another mutant C-terminally deleted by 8 aa still maintained the same properties (subcellular localization and the inhibitory effect) as the full-length HCV core protein of 191 aa. Taken together, our present results suggest that expression of HCV core protein in the cytoplasm selectively inhibits synthesis of p21/Waf1 and some other nuclear proteins at the translation level.

Cyclin-Dependent Kinase Inhibitor p21↗

Identification by functional proteomics of a deubiquitinating/deNeddylating enzyme in Plasmodium falciparum.

Ubiquitination is a post-translational modification implicated in a variety of cellular functions, including transcriptional regulation, protein degradation and membrane protein trafficking. Ubiquitin and the enzymes that act on it, although conserved and essential in eukaryotes, have not been well studied in parasites, despite sequencing of several parasite genomes. Several putative ubiquitin hydrolases have been identified in Plasmodium falciparum based on sequence homology alone, with no evidence of expression or function. Here we identify the first deubiquitinating enzyme in P. falciparum, PfUCH54, by its activity. We show that PfUCH54 also has deNeddylating activity, as assayed by a mammalian Nedd8-based probe. This activity is absent from mammalian homologues of PfUCH54. Given the importance of parasitic membrane protein trafficking as well as protein degradation in the virulence of this parasite, this family of enzymes may represent a target for pharmacological intervention with this disease.

Amino Acid Sequence↗

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. RESULTS: We present ProFAT, a web-based tool for the functional annotation of protein sequences based on remote sequence similarity. ProFAT combines sensitive sequence database search methods and a fold recognition algorithm with a simple text-mining approach. ProFAT extracts identified hits based on their biological background by keyword-mining of annotations, features and most importantly, literature associated with a sequence entry. A user-provided keyword list enables the user to specifically search for weak, but biologically relevant homologues of an input query. The ProFAT server has been evaluated using the complete set of proteins from three different domain families, including their weak relatives and could correctly identify between 90% and 100% of all domain family members studied in this context. ProFAT has furthermore been applied to a variety of proteins from different cellular contexts and we provide evidence on how ProFAT can help in functional prediction of proteins based on remotely conserved proteins. CONCLUSION: By employing sensitive database search programs as well as exploiting the functional information associated with database sequences, ProFAT can detect remote, but biologically relevant relationships between proteins and will assist researchers in the prediction of protein function based on remote homologies.

Algorithms↗

Prediction of protein-protein interaction based on structure.

A great challenge in the proteomics and structural genomics era is to predict protein structure and function from sequence, including the identification of biological partners. The development of a procedure to construct position-specific scoring matrices for the prediction and identification of sequences with putative significant affinity faces this challenge. The local and web applications used for sequence and structure search, sequence alignment, protein modeling, molecule edition and modification, and scoring matrices construction are described in detail. The methodology is based on the information contained in structural databases and takes into account the subtle conformational and sequence details that characterize different structures within a family. Using the matrices, the protein sequence databases can be easily scanned to locate putative partners of biological significance. The success of this methodology opens the way for the prediction of protein-protein interaction at genome scale.

Algorithms↗