Biomedical subjects

Stavros J Hamodrakas

Publications and source records attributed to Stavros J Hamodrakas.

18 recordsLinked to original sources

PubMed2006

Amyloid fibril formation propensity is inherent into the hexapeptide tandemly repeating sequence of the central domain of silkmoth chorion proteins of the A-family.

Peptide-analogues of the A and B families of silkmoth chorion proteins form amyloid fibrils under a variety of conditions [Iconomidou, V.A., Vriend, G. Hamodrakas, S.J. 2000. Amyloids protect the silkmoth oocyte and embryo. FEBS Lett. 479, 141-145; Iconomidou,V.A., Chryssikos, G.D.,Gionis, V., Vriend, G., Hoenger, A., Hamodrakas, S.J., 2001. Amyloid-like fibrils from an 18-residue peptide-analogue of a part of the central domain of the B-family of silkmoth chorion protein. FEBS Lett. 499, 268-273; Hamodrakas, S.J. Hoenger, A., Iconomidou, V. A., 2004 . Amyloid fibrillogenesis of silkmoth chorion protein peptide-analogues via a liquid crystalline intermediate phase. J. Struct. Biol. 145, 226-235.], which led us to propose that silkmoth chorion is a natural protective amyloid. In this study, we designed and synthesized two mutant peptide-analogues of the central conservative domain of the A family: (a) one, cA_m1, with a length half of that of the central domain of the A family, which folds and self-assembles, in various conditions, into amyloid fibrils very similar in properties and structure to the fibrils formed by the cA peptide, which corresponds to the entire length of the A family central domain [Iconomidou, V.A., Vriend, G. Hamodrakas, S.J. 2000. Amyloids protect the silkmoth oocyte and embryo. FEBS Lett. 479, 141-145.], in full support of our previous proposal, (b) the second, cA_m2, differing from cA_m1 at three positions, where three glutamates have replaced two valines and one alanine residues, does not form amyloid fibrils in any conditions. It appears that (a) the amyloidogenic properties of silkmoth chorion peptides are encoded into the tandemly repeating hexapeptides comprising the central domain of silkmoth chorion proteins, and, that (b) suitable mutations, properly and carefully designed, greatly affect the strong amyloidogenic properties inherent in certain aminoacid sequences and may inhibit amyloid formation.

Amino Acid Motifs↗

PubMed2006

Algorithms for incorporating prior topological information in HMMs: application to transmembrane proteins.

BACKGROUND: Hidden Markov Models (HMMs) have been extensively used in computational molecular biology, for modelling protein and nucleic acid sequences. In many applications, such as transmembrane protein topology prediction, the incorporation of limited amount of information regarding the topology, arising from biochemical experiments, has been proved a very useful strategy that increased remarkably the performance of even the top-scoring methods. However, no clear and formal explanation of the algorithms that retains the probabilistic interpretation of the models has been presented so far in the literature. RESULTS: We present here, a simple method that allows incorporation of prior topological information concerning the sequences at hand, while at the same time the HMMs retain their full probabilistic interpretation in terms of conditional probabilities. We present modifications to the standard Forward and Backward algorithms of HMMs and we also show explicitly, how reliable predictions may arise by these modifications, using all the algorithms currently available for decoding HMMs. A similar procedure may be used in the training procedure, aiming at optimizing the labels of the HMM's classes, especially in cases such as transmembrane proteins where the labels of the membrane-spanning segments are inherently misplaced. We present an application of this approach developing a method to predict the transmembrane regions of alpha-helical membrane proteins, trained on crystallographically solved data. We show that this method compares well against already established algorithms presented in the literature, and it is extremely useful in practical applications. CONCLUSION: The algorithms presented here, are easily implemented in any kind of a Hidden Markov Model, whereas the prediction method (HMM-TM) is freely available for academic users at http://bioinformatics.biol.uoa.gr/HMM-TM, offering the most advanced decoding options currently available.

Algorithms↗

PubMed2006

PredSL: a tool for the N-terminal sequence-based prediction of protein subcellular localization.

The ability to predict the subcellular localization of a protein from its sequence is of great importance, as it provides information about the protein's function. We present a computational tool, PredSL, which utilizes neural networks, Markov chains, profile hidden Markov models, and scoring matrices for the prediction of the subcellular localization of proteins in eukaryotic cells from the N-terminal amino acid sequence. It aims to classify proteins into five groups: chloroplast, thylakoid, mitochondrion, secretory pathway, and "other". When tested in a five-fold cross-validation procedure, PredSL demonstrates 86.7% and 87.1% overall accuracy for the plant and non-plant datasets, respectively. Compared with TargetP, which is the most widely used method to date, and LumenP, the results of PredSL are comparable in most cases. When tested on the experimentally verified proteins of the Saccharomyces cerevisiae genome, PredSL performs comparably if not better than any available algorithm for the same task. Furthermore, PredSL is the only method capable for the prediction of these subcellular localizations that is available as a stand-alone application through the URL:http://bioinformatics.biol.uoa.gr/PredSL/.

Algorithms↗

PubMed2005

Prediction of the coupling specificity of GPCRs to four families of G-proteins using hidden Markov models and artificial neural networks.

MOTIVATION: G-protein coupled receptors are a major class of eukaryotic cell-surface receptors. A very important aspect of their function is the specific interaction (coupling) with members of four G-protein families. A single GPCR may interact with members of more than one G-protein families (promiscuous coupling). To date all published methods that predict the coupling specificity of GPCRs are restricted to three main coupling groups G(i/o), G(q/11) and G(s), not including G(12/13)-coupled or other promiscuous receptors. RESULTS: We present a method that combines hidden Markov models and a feed-forward artificial neural network to overcome these limitations, while producing the most accurate predictions currently available. Using an up-to-date curated dataset, our method yields a 94% correct classification rate in a 5-fold cross-validation test. The method predicts also promiscuous coupling preferences, including coupling to G(12/13), whereas unlike other methods avoids overpredictions (false positives) when non-GPCR sequences are encountered. AVAILABILITY: A webserver for academic users is available at http://bioinformatics.biol.uoa.gr/PRED-COUPLE2

Animals↗

PubMed2005

A method for the prediction of GPCRs coupling specificity to G-proteins using refined profile Hidden Markov Models.

BACKGROUND: G- Protein coupled receptors (GPCRs) comprise the largest group of eukaryotic cell surface receptors with great pharmacological interest. A broad range of native ligands interact and activate GPCRs, leading to signal transduction within cells. Most of these responses are mediated through the interaction of GPCRs with heterotrimeric GTP-binding proteins (G-proteins). Due to the information explosion in biological sequence databases, the development of software algorithms that could predict properties of GPCRs is important. Experimental data reported in the literature suggest that heterotrimeric G-proteins interact with parts of the activated receptor at the transmembrane helix-intracellular loop interface. Utilizing this information and membrane topology information, we have developed an intensive exploratory approach to generate a refined library of statistical models (Hidden Markov Models) that predict the coupling preference of GPCRs to heterotrimeric G-proteins. The method predicts the coupling preferences of GPCRs to Gs, Gi/o and Gq/11, but not G12/13 subfamilies. RESULTS: Using a dataset of 282 GPCR sequences of known coupling preference to G-proteins and adopting a five-fold cross-validation procedure, the method yielded an 89.7% correct classification rate. In a validation set comprised of all receptor sequences that are species homologues to GPCRs with known coupling preferences, excluding the sequences used to train the models, our method yields a correct classification rate of 91.0%. Furthermore, promiscuous coupling properties were correctly predicted for 6 of the 24 GPCRs that are known to interact with more than one subfamily of G-proteins. CONCLUSION: Our method demonstrates high correct classification rate. Unlike previously published methods performing the same task, it does not require any transmembrane topology prediction in a preceding step. A web-server for the prediction of GPCRs coupling specificity to G-proteins available for non-commercial users is located at http://bioinformatics.biol.uoa.gr/PRED-COUPLE.

Algorithms↗

PubMed2005

Unique features of the structural model of 'hard' cuticle proteins: implications for chitin-protein interactions and cross-linking in cuticle.

Cuticular proteins are one of the determinants of the physical properties of cuticle. A common consensus region (extended R&R Consensus) in these proteins binds to chitin, the other major component of cuticle. We previously predicted the preponderance of beta-pleated sheet in the consensus region and proposed its responsibility for the formation of helicoidal cuticle (Iconomidou et al., Insect Biochem. Mol. Biol. 29 (1999) 285). Subsequently, we verified experimentally the abundance of antiparallel beta-pleated sheet in the structure of cuticle proteins (Iconomidou et al., Insect Biochem. Mol. Biol. 31 (2001) 877). Homology modelling of soft (RR-1) cuticular proteins using bovine plasma retinol binding protein (RBP) as a template revealed an antiparallel beta-sheet half-barrel structure as the basic folding motif (Hamodrakas et al., Insect Biochem. Molec. Biol. 32 (2002) 1577). The RR-2 proteins characteristic of hard cuticle, have a far more conserved consensus and frequently more histidine residues. Extension of modelling to this class of consensus, in this work, reveals in detail several unique features of the proposed structural model to serve as a chitin binding structural motif, thus providing the basis for elucidating cuticle's overall architecture and chitin-protein interactions in cuticle.

Amino Acid Sequence↗

PubMed2005

Evaluation of methods for predicting the topology of beta-barrel outer membrane proteins and a consensus prediction method.

BACKGROUND: Prediction of the transmembrane strands and topology of beta-barrel outer membrane proteins is of interest in current bioinformatics research. Several methods have been applied so far for this task, utilizing different algorithmic techniques and a number of freely available predictors exist. The methods can be grossly divided to those based on Hidden Markov Models (HMMs), on Neural Networks (NNs) and on Support Vector Machines (SVMs). In this work, we compare the different available methods for topology prediction of beta-barrel outer membrane proteins. We evaluate their performance on a non-redundant dataset of 20 beta-barrel outer membrane proteins of gram-negative bacteria, with structures known at atomic resolution. Also, we describe, for the first time, an effective way to combine the individual predictors, at will, to a single consensus prediction method. RESULTS: We assess the statistical significance of the performance of each prediction scheme and conclude that Hidden Markov Model based methods, HMM-B2TMR, ProfTMB and PRED-TMBB, are currently the best predictors, according to either the per-residue accuracy, the segments overlap measure (SOV) or the total number of proteins with correctly predicted topologies in the test set. Furthermore, we show that the available predictors perform better when only transmembrane beta-barrel domains are used for prediction, rather than the precursor full-length sequences, even though the HMM-based predictors are not influenced significantly. The consensus prediction method performs significantly better than each individual available predictor, since it increases the accuracy up to 4% regarding SOV and up to 15% in correctly predicted topologies. CONCLUSIONS: The consensus prediction method described in this work, optimizes the predicted topology with a dynamic programming algorithm and is implemented in a web-based application freely available to non-commercial users at http://bioinformatics.biol.uoa.gr/ConBBPRED.

Algorithms↗

PubMed2004

A database for G proteins and their interaction with GPCRs.

BACKGROUND: G protein-coupled receptors (GPCRs) transduce signals from extracellular space into the cell, through their interaction with G proteins, which act as switches forming hetero-trimers composed of different subunits (alpha,beta,gamma). The alpha subunit of the G protein is responsible for the recognition of a given GPCR. Whereas specialised resources for GPCRs, and other groups of receptors, are already available, currently, there is no publicly available database focusing on G Proteins and containing information about their coupling specificity with their respective receptors. DESCRIPTION: gpDB is a publicly accessible G proteins/GPCRs relational database. Including species homologs, the database contains detailed information for 418 G protein monomers (272 Galpha, 87 Gbeta and 59 Ggamma) and 2782 GPCRs sequences belonging to families with known coupling to G proteins. The GPCRs and the G proteins are classified according to a hierarchy of different classes, families and sub-families, based on extensive literature searchs. The main innovation besides the classification of both G proteins and GPCRs is the relational model of the database, describing the known coupling specificity of the GPCRs to their respective alpha subunit of G proteins, a unique feature not available in any other database. There is full sequence information with cross-references to publicly available databases, references to the literature concerning the coupling specificity and the dimerization of GPCRs and the user may submit advanced queries for text search. Furthermore, we provide a pattern search tool, an interface for running BLAST against the database and interconnectivity with PRED-TMR, PRED-GPCR and TMRPres2D. CONCLUSIONS: The database will be very useful, for both experimentalists and bioinformaticians, for the study of G protein/GPCR interactions and for future development of predictive algorithms. It is available for academics, via a web browser at the URL: http://bioinformatics.biol.uoa.gr/gpDB.

Databases, Protein↗

PubMed2004

cuticleDB: a relational database of Arthropod cuticular proteins.

BACKGROUND: The insect exoskeleton or cuticle is a bi-partite composite of proteins and chitin that provides protective, skeletal and structural functions. Little information is available about the molecular structure of this important complex that exhibits a helicoidal architecture. Scores of sequences of cuticular proteins have been obtained from direct protein sequencing, from cDNAs, and from genomic analyses. Most of these cuticular protein sequences contain motifs found only in arthropod proteins. DESCRIPTION: cuticleDB is a relational database containing all structural proteins of Arthropod cuticle identified to date. Many come from direct sequencing of proteins isolated from cuticle and from sequences from cDNAs that share common features with these authentic cuticular proteins. It also includes proteins from the Drosophila melanogaster and the Anopheles gambiae genomes, that have been predicted to be cuticular proteins, based on a Pfam motif (PF00379) responsible for chitin binding in Arthropod cuticle. The total number of the database entries is 445: 370 derive from insects, 60 from Crustacea and 15 from Chelicerata. The database can be accessed from our web server at http://bioinformatics.biol.uoa.gr/cuticleDB. CONCLUSIONS: CuticleDB was primarily designed to contain correct and full annotation of cuticular protein data. The database will be of help to future genome annotators. Users will be able to test hypotheses for the existence of known and also of yet unknown motifs in cuticular proteins. An analysis of motifs may contribute to understanding how proteins contribute to the physical properties of cuticle as well as to the precise nature of their interaction with chitin.

Amino Acid Motifs↗

PubMed2004

PRED-TMBB: a web server for predicting the topology of beta-barrel outer membrane proteins.

The beta-barrel outer membrane proteins constitute one of the two known structural classes of membrane proteins. Whereas there are several different web-based predictors for alpha-helical membrane proteins, currently there is no freely available prediction method for beta-barrel membrane proteins, at least with an acceptable level of accuracy. We present here a web server (PRED-TMBB, http://bioinformatics.biol.uoa.gr/PRED-TMBB) which is capable of predicting the transmembrane strands and the topology of beta-barrel outer membrane proteins of Gram-negative bacteria. The method is based on a Hidden Markov Model, trained according to the Conditional Maximum Likelihood criterion. The model was retrained and the training set now includes 16 non-homologous outer membrane proteins with structures known at atomic resolution. The user may submit one sequence at a time and has the option of choosing between three different decoding methods. The server reports the predicted topology of a given protein, a score indicating the probability of the protein being an outer membrane beta-barrel protein, posterior probabilities for the transmembrane strand prediction and a graphical representation of the assumed position of the transmembrane strands with respect to the lipid bilayer.

Bacterial Outer Membrane Proteins↗

PubMed2004

TMRPres2D: high quality visual representation of transmembrane protein models.

The 'TransMembrane protein Re-Presentation in 2-Dimensions' (TMRPres2D) tool, automates the creation of uniform, two-dimensional, high analysis graphical images/models of alpha-helical or beta-barrel transmembrane proteins. Protein sequence data and structural information may be acquired from public protein knowledge bases, emanate from prediction algorithms, or even be defined by the user. Several important biological and physical sequence attributes can be embedded in the graphical representation.

Amino Acid Sequence↗

PubMed2004

A Hidden Markov Model method, capable of predicting and discriminating beta-barrel outer membrane proteins.

BACKGROUND: Integral membrane proteins constitute about 20-30% of all proteins in the fully sequenced genomes. They come in two structural classes, the alpha-helical and the beta-barrel membrane proteins, demonstrating different physicochemical characteristics, structure and localization. While transmembrane segment prediction for the alpha-helical integral membrane proteins appears to be an easy task nowadays, the same is much more difficult for the beta-barrel membrane proteins. We developed a method, based on a Hidden Markov Model, capable of predicting the transmembrane beta-strands of the outer membrane proteins of gram-negative bacteria, and discriminating those from water-soluble proteins in large datasets. The model is trained in a discriminative manner, aiming at maximizing the probability of correct predictions rather than the likelihood of the sequences. RESULTS: The training has been performed on a non-redundant database of 14 outer membrane proteins with structures known at atomic resolution; it has been tested with a jacknife procedure, yielding a per residue accuracy of 84.2% and a correlation coefficient of 0.72, whereas for the self-consistency test the per residue accuracy was 88.1% and the correlation coefficient 0.824. The total number of correctly predicted topologies is 10 out of 14 in the self-consistency test, and 9 out of 14 in the jacknife. Furthermore, the model is capable of discriminating outer membrane from water-soluble proteins in large-scale applications, with a success rate of 88.8% and 89.2% for the correct classification of outer membrane and water-soluble proteins respectively, the highest rates obtained in the literature. That test has been performed independently on a set of known outer membrane proteins with low sequence identity with each other and also with the proteins of the training set. CONCLUSION: Based on the above, we developed a strategy, that enabled us to screen the entire proteome of E. coli for outer membrane proteins. The results were satisfactory, thus the method presented here appears to be suitable for screening entire proteomes for the discovery of novel outer membrane proteins. A web interface available for non-commercial users is located at: http://bioinformatics.biol.uoa.gr/PRED-TMBB, and it is the only freely available HMM-based predictor for beta-barrel outer membrane protein topology.

Databases, Protein↗

PubMed2004

Conformational analysis of peptide analogues of silkmoth chorion protein segments using CD, NMR and molecular modelling.

Silkmoth proteins secreted from the follicular cells that surround the oocyte form a large extracellular assembly which is important for protecting and sustaining the structure of the oocyte and the developing embryo. These proteins have been classified into two major families (A and B). Sequence analysis showed conservation of a central domain containing long stretches of six amino acid residue repeats in both families, which have been suggested to be organized in beta-sheet structures. In this work NMR and CD spectra, as well as molecular calculations, have been used to investigate the conformational properties of two synthetic peptides (A and B), analogues of parts of the central domain of silkmoth chorion proteins of the A and B families, respectively. These peptides consist of three tandem repeats of the six-residue basic motif. Analysis of CD spectra of the two peptides in aqueous solutions and mixtures with organic solvents revealed beta-sheet and turn structural elements with a percentage higher than 40%. NOESY spectra at low temperatures (263-273 K) show sequential nOe connectivities (i, i + 1), indicative of a relative flexibility. The presence of HNi-HNi+1 cross-peaks and medium Halphai-HNi+1 connectivities, chemical shift deviations and temperature coefficient data provide, for the first time, experimental evidence that local folded structures around Gly residues occur in peptide segments of chorion proteins in solution. Simulated annealing calculations were used to examine the conformational space of the peptides and to probe the initial steps of amyloid fibril formation in the case of chorion proteins.

Amino Acid Sequence↗

PubMed2004

waveTM: wavelet-based transmembrane segment prediction.

waveTM is a web tool for the prediction of transmembrane segments in alpha-helical membrane proteins. Prediction is performed by a dynamic programming algorithm on wavelet-denoised 'hydropathy' signals. Users submit a protein sequence and receive interactively the results. Topology prediction can also be obtained in conjunction with the algorithm OrienTM. A web server that implements the waveTM algorithm is freely available at http://bioinformatics.biol.uoa.gr/waveTM.

Algorithms↗

PubMed2003

GeneViTo: visualizing gene-product functional and structural features in genomic datasets.

BACKGROUND: The availability of increasing amounts of sequence data from completely sequenced genomes boosts the development of new computational methods for automated genome annotation and comparative genomics. Therefore, there is a need for tools that facilitate the visualization of raw data and results produced by bioinformatics analysis, providing new means for interactive genome exploration. Visual inspection can be used as a basis to assess the quality of various analysis algorithms and to aid in-depth genomic studies. RESULTS: GeneViTo is a JAVA-based computer application that serves as a workbench for genome-wide analysis through visual interaction. The application deals with various experimental information concerning both DNA and protein sequences (derived from public sequence databases or proprietary data sources) and meta-data obtained by various prediction algorithms, classification schemes or user-defined features. Interaction with a Graphical User Interface (GUI) allows easy extraction of genomic and proteomic data referring to the sequence itself, sequence features, or general structural and functional features. Emphasis is laid on the potential comparison between annotation and prediction data in order to offer a supplement to the provided information, especially in cases of "poor" annotation, or an evaluation of available predictions. Moreover, desired information can be output in high quality JPEG image files for further elaboration and scientific use. A compilation of properly formatted GeneViTo input data for demonstration is available to interested readers for two completely sequenced prokaryotes, Chlamydia trachomatis and Methanococcus jannaschii. CONCLUSIONS: GeneViTo offers an inspectional view of genomic functional elements, concerning data stemming both from database annotation and analysis tools for an overall analysis of existing genomes. The application is compatible with Linux or Windows ME-2000-XP operating systems, provided that the appropriate Java Runtime Environment is already installed in the system.

Bacterial Proton-Translocating ATPases↗

PubMed2003

FT-Raman spectroscopy as diagnostic tool of Congo red binding to amyloids.

Chorion is the major component of silkmoth eggshell. More than 95% of its dry mass consists of the A and B families of low molecular weight structural proteins, which have remarkable mechanical and chemical properties protecting the oocyte and developing embryo from environmental hazards. We present data from FT-Raman spectroscopy of silkmoth chorion and amyloid-like fibrils formed from peptide analogues of chorion proteins, both unstained and stained by Congo red. The results show that FT-Raman spectroscopy is not a straightforward diagnostic tool for the specific interactions of Congo red with amyloids: a dilute aqueous solution of the Congo red dye at pH 5.5 and a thin solid film of the dye cast from this solution exhibit the same "diagnostic" Raman shifts relative to the neat Congo red dry powder as do amyloid fibrils formed from peptide analogues of chorion proteins stained by Congo red. An important consequence of this finding is that these shifts of the Raman active modes of Congo red are probably due to the formation of supramolecular dye aggregates in the presence of water. Therefore, this is not an appropriate diagnostic test for Congo red binding to amyloids.

Animals↗

PubMed2002

2,4-Diamino-5-(1-naphthyl)-3,5-diaza-1-azoniaspiro[5.5]undeca-1,3-diene chloride.

The title salt, C(18)H(22)N(5)(+).Cl(-), is a member of a new series of lipophilic 4,6-diamino spiro-s-triazines which are potent inhibitors of dihydrofolate reductase. The protonated triazine ring deviates from planarity, whereas the cyclohexane ring adopts a chair conformation. A rather unusual hydrogen-bonding scheme exists in the crystal. There is a centrosymmetric arrangement involving two amino groups and two triazine ring N atoms, with graph-set R(2)(2)(8) and an N.N distance of 3.098 (3) A, flanked by two additional R(3)(2)(8) systems, involving two amino groups, a triazine ring N atom and a Cl(-) anion, with N.Cl distances in the range 3.179 (2)-3.278 (2) A. Furthermore, the Cl(-) anion, the protonated triazine ring N atom and an amino group form a hydrogen-bonding system with graph-set R(2)(1)(6).

Crystallography↗

PubMed2002

A structural model of the chitin-binding domain of cuticle proteins.

The nature of the interaction of insect cuticular proteins and chitin is unknown even though about half of the cuticular proteins sequenced thus far share a consensus region that has been predicted to be the site of chitin binding. We previously predicted the preponderance of beta-pleated sheet in the consensus region and proposed its responsibility for the formation of helicoidal cuticle (Iconomidou et al., Insect Biochem. Mol. Biol. 29 (1999) 285). Consequently, we have also verified experimentally the abundance of antiparallel beta-pleated sheet in the structure of cuticle proteins (Iconomidou et al., Insect Biochem. Mol. Biol. 31 (2001) 877). In this work, based on sequence and secondary structure similarity of cuticle proteins, and especially that of the consensus motif, to that of bovine plasma retinol binding protein (RBP), we propose by homology modelling an antiparallel beta-sheet half-barrel structure as the basic folding motif of cuticle proteins. This folding motif may provide the template for elucidating cuticle protein-chitin interactions in detail and reveal the precise geometrical formation of cuticle's helicoidal architecture. This predicted motif is another example where nature utilizes an almost flat protein surface covered by aromatic side chains to interact with the polysaccharide chains of chitin.

Amino Acid Sequence↗