Structure of TcpG, the DsbA protein folding catalyst from Vibrio cholerae

The efficient and correct folding of bacterial disulfide bonded proteins in vivo is dependent upon a class of periplasmic oxidoreductase proteins called DsbA, after the Escherichia coli enzyme. In the pathogenic bacterium Vibrio cholerae, the DsbA homolog (TcpG) is responsible for the folding, maturation and secretion of virulence factors. Mutants in which the tcpg gene has been inactivated are avirulent; they no longer produce functional colonisation pill and they no longer secrete cholera toxin. TcpG is thus a suitable target for inhibitors that could counteract the virulence of this organism, thereby preventing the symptoms of cholera. The crystal structure of oxidized TcpG (refined at a resolution of 2.1 Angstrom) serves as a starting point for the rational design of such inhibitors. As expected, TcpG has the same fold as E. coli DsbA, with which it shares similar to 40% sequence identity. Ln addition, the characteristic surface features of DsbA are present in TcpG, supporting the notion that these features play a functional role. While the overall architecture of TcpG and DsbA is similar and the surface features are retained in TcpG, there are significant differences. For example, the kinked active site helix results from a three-residue loop in DsbA, but is caused by a proline in TcpG (making TcpG more similar to thioredoxin in this respect). Furthermore, the proposed peptide binding groove of TcpG is substantially shortened compared with that of DsbA due to a six-residue deletion. Also, the hydrophobic pocket of TcpG is more shallow and the acidic patch is much less extensive than that of E. coli DsbA. The identification of the structural and surface features that are retained or are divergent in TcpG provides a useful assessment of their functional importance in these protein folding catalysts and is an important prerequisite for the design of TcpG inhibitors. (C) 1997 Academic Press Limited.

The solution structure of C1-T1, a two-domain proteinase inhibitor derived from a circular precursor protein from Nicotiana alata

A two-domain portion of the proteinase inhibitor precursor from Nicotiana alata (NaProPI) has been expressed and its structure determined by NMR spectroscopy. NaProPI contains six almost identical 53 amino acid repeats that fold into six highly similar domains; however, the sequence repeats do nut coincide with the structural domains. Five of the structural domains comprise the C-terminal portion of one repeat and the N-terminal portion of the next. The sixth domain contains the C-terminal portion of the sixth repeat and the N-terminal portion of the first repeat. Disulphide bonds link these C and N-terminal fragments to generate the clasped-bracelet fold of NaProPI. The three-dimensional structure of NaProPI is not known, but it is conceivable that adjacent domains in NaProPI interact to generate the circular bracelet with the N and C termini in close enough proximity to facilitate formation of the disulphide bonds that form the clasp The expressed protein, examined in the current study, comprises residues 25-135 of NaProPI and encompasses the first two contiguous structural domains, namely the chymotrypsin inhibitor C1 and the trypsin inhibitor T1, joined by a five-residue linker, and is referred to as C1-T1. The tertiary structure of each domain in C1-T1 is identical to that found in the isolated inhibitors. However, no nuclear Overhauser effect contacts are observed between the two domains and the five-residue linker adopts an extended conformation. The absence of interactions between the domains indicates that adjacent domains do not specifically interact to drive the circularisation of NaProPI. These results are in agreement with recent data which describe similar PI precursors from other members of the Solanaceae having two, three, or four repeats. The lack of strong interdomain association is likely to be important for the function of individual inhibitors by ensuring that there is no masking of reactive sites upon release from the precursor. (C) 2001 Academic Press.

The Three-dimensional Solution Structure of NaD1, a New Floral Defensin from Nicotiana alata and its Application to a Homology Model of the Crop Defense Protein alfAFP

NMR spectroscopy and simulated annealing calculations have been used to determine the three-dimensional structure of NaD1, a novel antifungal and insecticidal protein isolated from the flowers of Nicotiana alata. NaD1 is a basic, cysteine-rich protein of 47 residues and is the first example of a plant defensin from flowers to be characterized structurally. Its three-dimensional structure consists of an a-helix and a triple-stranded anti-parallel beta-sheet that are stabilized by four intramolecular disulfide bonds. NaD1 features all the characteristics of the cysteine-stabilized up motif that has been described for a variety of proteins of differing functions ranging from antibacterial insect defensins and ion channel-perturbing scorpion toxins to an elicitor of the sweet taste response. The protein is biologically active against insect pests, which makes it a potential candidate for use in crop protection. NaD1 shares 31% sequence identity with alfAFP, an antifungal protein from alfalfa that confers resistance to a fungal pathogen in transgenic potatoes. The structure of NaD1 was used to obtain a homology model of alfAFP, since NaD1 has the highest level of sequence identity with alfAFP of any structurally characterized antifungal defensin. The structures of NaD1 and alfAFP were used in conjunction with structure - activity data for the radish defensin Rs-AFP2 to provide an insight into structure-function relationships. In particular, a putative effector site was identified in the structure of NaD1 and in the corresponding homology model of alfAFP. (C) 2002 Elsevier Science Ltd. All rights reserved.

Integrating protein structural information

Dissertação apresentada para obtenção de Grau de Doutor em Bioquímica,Bioquímica Estrutural, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Structural prediction of peptides bound to MHC class I.

An ab initio structure prediction approach adapted to the peptide-major histocompatibility complex (MHC) class I system is presented. Based on structure comparisons of a large set of peptide-MHC class I complexes, a molecular dynamics protocol is proposed using simulated annealing (SA) cycles to sample the conformational space of the peptide in its fixed MHC environment. A set of 14 peptide-human leukocyte antigen (HLA) A0201 and 27 peptide-non-HLA A0201 complexes for which X-ray structures are available is used to test the accuracy of the prediction method. For each complex, 1000 peptide conformers are obtained from the SA sampling. A graph theory clustering algorithm based on heavy atom root-mean-square deviation (RMSD) values is applied to the sampled conformers. The clusters are ranked using cluster size, mean effective or conformational free energies, with solvation free energies computed using Generalized Born MV 2 (GB-MV2) and Poisson-Boltzmann (PB) continuum models. The final conformation is chosen as the center of the best-ranked cluster. With conformational free energies, the overall prediction success is 83% using a 1.00 Angstroms crystal RMSD criterion for main-chain atoms, and 76% using a 1.50 Angstroms RMSD criterion for heavy atoms. The prediction success is even higher for the set of 14 peptide-HLA A0201 complexes: 100% of the peptides have main-chain RMSD values < or =1.00 Angstroms and 93% of the peptides have heavy atom RMSD values < or =1.50 Angstroms. This structure prediction method can be applied to complexes of natural or modified antigenic peptides in their MHC environment with the aim to perform rational structure-based optimizations of tumor vaccines.

Splitting statistical potentials into meaningful scoring functions: testing the prediction of near-native structures from decoy conformations

Background: Recent advances on high-throughput technologies have produced a vast amount of protein sequences, while the number of high-resolution structures has seen a limited increase. This has impelled the production of many strategies to built protein structures from its sequence, generating a considerable amount of alternative models. The selection of the closest model to the native conformation has thus become crucial for structure prediction. Several methods have been developed to score protein models by energies, knowledge-based potentials and combination of both.Results: Here, we present and demonstrate a theory to split the knowledge-based potentials in scoring terms biologically meaningful and to combine them in new scores to predict near-native structures. Our strategy allows circumventing the problem of defining the reference state. In this approach we give the proof for a simple and linear application that can be further improved by optimizing the combination of Zscores. Using the simplest composite score () we obtained predictions similar to state-of-the-art methods. Besides, our approach has the advantage of identifying the most relevant terms involved in the stability of the protein structure. Finally, we also use the composite Zscores to assess the conformation of models and to detect local errors.Conclusion: We have introduced a method to split knowledge-based potentials and to solve the problem of defining a reference state. The new scores have detected near-native structures as accurately as state-of-art methods and have been successful to identify wrongly modeled regions of many near-native conformations.

Prediction of enzyme function by combining sequence similarity and protein interactions

Background: A number of studies have used protein interaction data alone for protein function prediction. Here, we introduce a computational approach for annotation of enzymes, based on the observation that similar protein sequences are more likely to perform the same function if they share similar interacting partners. Results: The method has been tested against the PSI-BLAST program using a set of 3,890 protein sequences from which interaction data was available. For protein sequences that align with at least 40% sequence identity to a known enzyme, the specificity of our method in predicting the first three EC digits increased from 80% to 90% at 80% coverage when compared to PSI-BLAST. Conclusion: Our method can also be used in proteins for which homologous sequences with known interacting partners can be detected. Thus, our method could increase 10% the specificity of genome-wide enzyme predictions based on sequence matching by PSI-BLAST alone.

Structure and function of a "yellow" protein from saliva of the sand fly Lutzomyia longipalpis that confers protective immunity against Leishmania major infection.

LJM11, an abundant salivary protein from the sand fly Lutzomyia longipalpis, belongs to the insect "yellow" family of proteins. In this study, we immunized mice with 17 plasmids encoding L. longiplapis salivary proteins and demonstrated that LJM11 confers protective immunity against Leishmania major infection. This protection correlates with a strong induction of a delayed type hypersensitivity (DTH) response following exposure to L. longipalpis saliva. Additionally, splenocytes of exposed mice produce IFN-γ upon stimulation with LJM11, demonstrating the systemic induction of Th1 immunity by this protein. In contrast to LJM11, LJM111, another yellow protein from L. longipalpis saliva, does not produce a DTH response in these mice, suggesting that structural or functional features specific to LJM11 are important for the induction of a robust DTH response. To examine these features, we used calorimetric analysis to probe a possible ligand binding function for the salivary yellow proteins. LJM11, LJM111, and LJM17 all acted as high affinity binders of prohemostatic and proinflammatory biogenic amines, particularly serotonin, catecholamines, and histamine. We also determined the crystal structure of LJM11, revealing a six-bladed β-propeller fold with a single ligand binding pocket located in the central part of the propeller structure on one face of the molecule. A hypothetical model of LJM11 suggests a positive electrostatic potential on the face containing entry to the ligand binding pocket, whereas LJM111 is negative to neutral over its entire surface. This may be the reason for differences in antigenicity between the two proteins.

Prediction of cross-recognition of peptide-HLA A2 by Melan-A-specific cytotoxic T lymphocytes using three-dimensional quantitative structure-activity relationships.

The cross-recognition of peptides by cytotoxic T lymphocytes is a key element in immunology and in particular in peptide based immunotherapy. Here we develop three-dimensional (3D) quantitative structure-activity relationships (QSARs) to predict cross-recognition by Melan-A-specific cytotoxic T lymphocytes of peptides bound to HLA A*0201 (hereafter referred to as HLA A2). First, we predict the structure of a set of self- and pathogen-derived peptides bound to HLA A2 using a previously developed ab initio structure prediction approach [Fagerberg et al., J. Mol. Biol., 521-46 (2006)]. Second, shape and electrostatic energy calculations are performed on a 3D grid to produce similarity matrices which are combined with a genetic neural network method [So et al., J. Med. Chem., 4347-59 (1997)] to generate 3D-QSAR models. The models are extensively validated using several different approaches. During the model generation, the leave-one-out cross-validated correlation coefficient (q (2)) is used as the fitness criterion and all obtained models are evaluated based on their q (2) values. Moreover, the best model obtained for a partitioned data set is evaluated by its correlation coefficient (r = 0.92 for the external test set). The physical relevance of all models is tested using a functional dependence analysis and the robustness of the models obtained for the entire data set is confirmed using y-randomization. Finally, the validated models are tested for their utility in the setting of rational peptide design: their ability to discriminate between peptides that only contain side chain substitutions in a single secondary anchor position is evaluated. In addition, the predicted cross-recognition of the mono-substituted peptides is confirmed experimentally in chromium-release assays. These results underline the utility of 3D-QSARs in peptide mimetic design and suggest that the properties of the unbound epitope are sufficient to capture most of the information to determine the cross-recognition.

Structure-function analysis of the human TFIIB-related factor II protein reveals an essential role for the C-terminal domain in RNA polymerase III transcription.

The transcription factors TFIIB, Brf1, and Brf2 share related N-terminal zinc ribbon and core domains. TFIIB bridges RNA polymerase II (Pol II) with the promoter-bound preinitiation complex, whereas Brf1 and Brf2 are involved, as part of activities also containing TBP and Bdp1 and referred to here as Brf1-TFIIIB and Brf2-TFIIIB, in the recruitment of Pol III. Brf1-TFIIIB recruits Pol III to type 1 and 2 promoters and Brf2-TFIIIB to type 3 promoters such as the human U6 promoter. Brf1 and Brf2 both have a C-terminal extension absent in TFIIB, but their C-terminal extensions are unrelated. In yeast Brf1, the C-terminal extension interacts with the TBP/TATA box complex and contributes to the recruitment of Bdp1. Here we have tested truncated Brf2, as well as Brf2/TFIIB chimeric proteins for U6 transcription and for assembly of U6 preinitiation complexes. Our results characterize functions of various human Brf2 domains and reveal that the C-terminal domain is required for efficient association of the protein with U6 promoter-bound TBP and SNAP(c), a type 3 promoter-specific transcription factor, and for efficient recruitment of Bdp1. This in turn suggests that the C-terminal extensions in Brf1 and Brf2 are crucial to specific recruitment of Pol III over Pol II.

Contribution of electrostatic interactions, compactness and quaternary structure to protein thermostability: lessons from structural genomics of Thermotoga maritima.

Studies of the structural basis of protein thermostability have produced a confusing picture. Small sets of proteins have been analyzed from a variety of thermophilic species, suggesting different structural features as responsible for protein thermostability. Taking advantage of the recent advances in structural genomics, we have compiled a relatively large protein structure dataset, which was constructed very carefully and selectively; that is, the dataset contains only experimentally determined structures of proteins from one specific organism, the hyperthermophilic bacterium Thermotoga maritima, and those of close homologs from mesophilic bacteria. In contrast to the conclusions of previous studies, our analyses show that oligomerization order, hydrogen bonds, and secondary structure play minor roles in adaptation to hyperthermophily in bacteria. On the other hand, the data exhibit very significant increases in the density of salt-bridges and in compactness for proteins from T.maritima. The latter effect can be measured by contact order or solvent accessibility, and network analysis shows a specific increase in highly connected residues in this thermophile. These features account for changes in 96% of the protein pairs studied. Our results provide a clear picture of protein thermostability in one species, and a framework for future studies of thermal adaptation.

A maximum likelihood framework for protein design

Affiliation: Claudia Kleinman, Nicolas Rodrigue & Hervé Philippe : Département de biochimie, Faculté de médecine, Université de Montréal

Nuclear magnetic resonance structure of the nucleic acid-binding domain of severe acute respiratory syndrome coronavirus nonstructural protein 3

The nuclear magnetic resonance (NMR) structure of a globular domain of residues 1071 to 1178 within the previously annotated nucleic acid-binding region (NAB) of severe acute respiratory syndrome coronavirus nonstructural protein 3 (nsp3) has been determined, and N- and C-terminally adjoining polypeptide segments of 37 and 25 residues, respectively, have been shown to form flexibly extended linkers to the preceding globular domain and to the following, as yet uncharacterized domain. This extension of the structural coverage of nsp3 was obtained from NMR studies with an nsp3 construct comprising residues 1066 to 1181 [ nsp3(1066-1181)] and the constructs nsp3(1066-1203) and nsp3(1035-1181). A search of the protein structure database indicates that the globular domain of the NAB represents a new fold, with a parallel four-strand beta-sheet holding two alpha-helices of three and four turns that are oriented antiparallel to the beta-strands. Two antiparallel two-strand beta-sheets and two 3(10)-helices are anchored against the surface of this barrel-like molecular core. Chemical shift changes upon the addition of single-stranded RNAs (ssRNAs) identified a group of residues that form a positively charged patch on the protein surface as the binding site responsible for the previously reported affinity for nucleic acids. This binding site is similar to the ssRNA-binding site of the sterile alpha motif domain of the Saccharomyces cerevisiae Vts1p protein, although the two proteins do not share a common globular fold.

Prediction of novel and analogous folds using fragment assembly and fold recognition

A number of new and newly improved methods for predicting protein structure developed by the Jones–University College London group were used to make predictions for the CASP6 experiment. Structures were predicted with a combination of fold recognition methods (mGenTHREADER, nFOLD, and THREADER) and a substantially enhanced version of FRAGFOLD, our fragment assembly method. Attempts at automatic domain parsing were made using DomPred and DomSSEA, which are based on a secondary structure parsing algorithm and additionally for DomPred, a simple local sequence alignment scoring function. Disorder prediction was carried out using a new SVM-based version of DISOPRED. Attempts were also made at domain docking and “microdomain” folding in order to build complete chain models for some targets.

Assembling novel protein folds from super-secondary structural fragments

The results of applying a fragment-based protein tertiary structure prediction method to the prediction of 14 CASP5 target domains are described. The method is based on the assembly of supersecondary structural fragments taken from highly resolved protein structures using a simulated annealing algorithm. A number of good predictions for proteins with novel folds were produced, although not always as the first model. For two fold recognition targets, FRAGFOLD produced the most accurate model in both cases, despite the fact that the predictions were not based on a template structure. Although clear progress has been made in improving FRAGFOLD since CASP4, the ranking of final models still seems to be the main problem that needs to be addressed before the next CASP experiment