955 resultados para In silico model


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Background: Expressed Sequence Tags (ESTs) are in general used to gain a first insight into gene activities from a species of interest. Subsequently, and typically based on a combination of EST and genome sequences, microarray-based expression analyses are performed for a variety of conditions. In some cases, a multitude of EST and microarray experiments are conducted for one species, covering different tissues, cell states, and cell types. Under these circumstances, the challenge arises to combine results derived from the different expression profiling strategies, with the goal to uncover novel information on the basis of the integrated datasets. Findings: Using our new analysis tool, MediPlEx (MEDIcago truncatula multiPLe EXpression analysis), expression data from EST experiments, oligonucleotide microarrays and Affymetrix GeneChips® can be combined and analyzed, leading to a novel approach to integrated transcriptome analysis. We have validated our tool via the identification of a set of well-characterized AM-specific and AM-induced marker genes, identified by MediPlEx on the basis of in silico and experimental gene expression profiles from roots colonized with AM fungi. Conclusions: MediPlEx offers an integrated analysis pipeline for different sets of expression data generated for the model legume Medicago truncatula. As expected, in silico and experimental gene expression data that cover the same biological condition correlate well. The collection of differentially expressed genes identified via MediPlEx provides a starting point for functional studies in plant mutants.

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Several aspects of photoperception and light signal transduction have been elucidated by studies with model plants. However, the information available for economically important crops, such as Fabaceae species, is scarce. In order to incorporate the existing genomic tools into a strategy to advance soybean research, we have investigated publicly available expressed sequence tag ( EST) sequence databases in order to identify Glycine max sequences related to genes involved in light-regulated developmental control in model plants. Approximately 38,000 sequences from open-access databases were investigated, and all bona fide and putative photoreceptor gene families were found in soybean sequence databases. We have identified G. max orthologs for several families of transcriptional regulators and cytoplasmic proteins mediating photoreceptor-induced responses, although some important Arabidopsis phytochrome-signaling components are absent. Moreover, soybean and Arabidopsis gene-family homologs appear to have undergone a distinct expansion process in some cases. We propose a working model of light perception, signal transduction and response-eliciting in G. max, based on the identified key components from Arabidopsis. These results demonstrate the power of comparative genomics between model systems and crop species to elucidate several aspects of plant physiology and metabolism.

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We introduce biomimetic in silico devices, and means for validation along with methods for testing and refining them. The devices are constructed from adaptable software components designed to map logically to biological components at multiple levels of resolution. In this report we focus on the liver; the goal is to validate components that mimic features of the lobule (the hepatic primary functional unit) and dynamic aspects of liver behavior, structure, and function. An assembly of lobule-mimetic devices represents an in silico liver. We validate against outflow profiles for sucrose administered as a bolus to isolated, perfused rat livers. Acceptable in silico profiles are experimentally indistinguishable from those of the in situ referent. This new technology is intended to provide powerful Dew tools for challenging our understanding of how biological functional units function in vivo.

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Besnoitia besnoiti is an apicomplexan parasite responsible for bovine besnoitiosis, a disease with a high prevalence in tropical and subtropical regions and re-emerging in Europe. Despite the great economical losses associated with besnoitiosis, this disease has been underestimated and poorly studied, and neither an effective therapy nor an efficacious vaccine is available. Protein disulfide isomerase (PDI) is an essential enzyme for the acquisition of the correct three-dimensional structure of proteins. Current evidence suggests that in Neosporacaninum and Toxoplasmagondii, which are closely related to B. besnoiti, PDI play an important role in host cell invasion, is a relevant target for the host immune response, and represents a promising drug target and/or vaccine candidate. In this work, we present the nucleotide sequence of the B. besnoiti PDI gene. BbPDI belongs to the thioredoxin-like superfamily (cluster 00388) and is included in the PDI_a family (cluster defined cd02961) and the PDI_a_PDI_a'_c subfamily (cd02995). A 3D theoretical model was built by comparative homology using Swiss-Model server, using as a template the crystallographic deduced model of Tapasin-ERp57 (PDB code 3F8U chain C). Analysis of the phylogenetic tree for PDI within the phylum apicomplexa reinforces the close relationship among B. besnoiti, N. caninum and T. gondii. When subjected to a PDI-assay based on the polymerisation of reduced insulin, recombinant BbPDI expressed in E. coli exhibited enzymatic activity, which was inhibited by bacitracin. Antiserum directed against recombinant BbPDI reacted with PDI in Western blots and by immunofluorescence with B. besnoiti tachyzoites and bradyzoites.

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Summary: Lipophilicity plays an important role in the determination and the comprehension of the pharmacokinetic behavior of drugs. It is usually expressed by the partition coefficient (log P) in the n-octanol/water system. The use of an additional solvent system (1,2-dichlorethane/water) is necessary to obtain complementary information, as the log Poct values alone are not sufficient to explain ail biological properties. The aim of this thesis is to develop tools allowing to predict lipophilicity of new drugs and to analyze the information yielded by those log P values. Part I presents the development of theoretical models used to predict lipophilicity. Chapter 2 shows the necessity to extend the existing solvatochromic analyses in order to predict correctly the lipophilicity of new and complex neutral compounds. In Chapter 3, solvatochromic analyses are used to develop a model for the prediction of the lipophilicity of ions. A global model was obtained allowing to estimate the lipophilicity of neutral, anionic and cationic solutes. Part II presents the detailed study of two physicochemical filters. Chapter 4 shows that the Discovery RP Amide C16 stationary phase allows to estimate lipophilicity of the neutral form of basic and acidic solutes, except of lipophilic acidic solutes. Those solutes present additional interactions with this particular stationary phase. In Chapter 5, 4 different IANI stationary phases are investigated. For neutral solutes, linear data are obtained whatever the IANI column used. For the ionized solutes, their retention is due to a balance of electrostatic and hydrophobie interactions. Thus no discrimination is observed between different series of solutes bearing the same charge, from one column to an other. Part III presents two examples illustrating the information obtained thanks to Structure-Properties Relationships (SPR). Comparing graphically lipophilicity values obtained in two different solvent systems allows to reveal the presence of intramolecular effects .such as internai H-bond (Chapter 6). SPR is used to study the partitioning of ionizable groups encountered in Medicinal Chemistry (Chapter7). Résumé La lipophilie joue un .rôle important dans la détermination et la compréhension du comportement pharmacocinétique des médicaments. Elle est généralement exprimée par le coefficient de partage (log P) d'un composé dans le système de solvants n-octanol/eau. L'utilisation d'un deuxième système de solvants (1,2-dichloroéthane/eau) s'est avérée nécessaire afin d'obtenir des informations complémentaires, les valeurs de log Poct seules n'étant pas suffisantes pour expliquer toutes les propriétés biologiques. Le but de cette thèse est de développer des outils permettant de prédire la lipophilie de nouveaux candidats médicaments et d'analyser l'information fournie par les valeurs de log P. La Partie I présente le développement de modèles théoriques utilisés pour prédire la lipophilie. Le chapitre 2 montre la nécessité de mettre à jour les analyses solvatochromiques existantes mais inadaptées à la prédiction de la lipophilie de nouveaux composés neutres. Dans le chapitre 3, la même méthodologie des analyses solvatochromiques est utilisée pour développer un modèle permettant de prédire la lipophilie des ions. Le modèle global obtenu permet la prédiction de la lipophilie de composés neutres, anioniques et cationiques. La Partie II présente l'étude approfondie de deux filtres physicochimiques. Le Chapitre 4 montre que la phase stationnaire Discovery RP Amide C16 permet la détermination de la lipophilie de la forme neutre de composés basiques et acides, à l'exception des acides très lipophiles. Ces derniers présentent des interactions supplémentaires avec cette phase stationnaire. Dans le Chapitre 5, 4 phases stationnaires IAM sont étudiées. Pour les composés neutres étudiés, des valeurs de rétention linéaires sont obtenues, quelque que soit la colonne IAM utilisée. Pour les composés ionisables, leur rétention est due à une balance entre des interactions électrostatiques et hydrophobes. Donc aucune discrimination n'est observée entre les différentes séries de composés portant la même charge d'une colonne à l'autre. La Partie III présente deux exemples illustrant les informations obtenues par l'utilisation des relations structures-propriétés. Comparer graphiquement la lipophilie mesurée dans deux différents systèmes de solvants permet de mettre en évidence la présence d'effets intramoléculaires tels que les liaisons hydrogène intramoléculaires (Chapitre 6). Cette approche des relations structures-propriétés est aussi appliquée à l'étude du partage de fonctions ionisables rencontrées en Chimie Thérapeutique (Chapitre 7) Résumé large public Pour exercer son effet thérapeutique, un médicament doit atteindre son site d'action en quantité suffisante. La quantité effective de médicament atteignant le site d'action dépend du nombre d'interactions entre le médicament et de nombreux constituants de l'organisme comme, par exemple, les enzymes du métabolisme ou les membranes biologiques. Le passage du médicament à travers ces membranes, appelé perméation, est un paramètre important à optimiser pour développer des médicaments plus puissants. La lipophilie joue un rôle clé dans la compréhension de la perméation passive des médicaments. La lipophilie est généralement exprimée par le coefficient de partage (log P) dans le système de solvants (non miscibles) n-octanol/eau. Les valeurs de log Poct seules se sont avérées insuffisantes pour expliquer la perméation à travers toutes les différentes membranes biologiques du corps humain. L'utilisation d'un système de solvants additionnel (le système 1,2-dichloroéthane/eau) a permis d'obtenir les informations complémentaires indispensables à une bonne compréhension du processus de perméation. Un grand nombre d'outils expérimentaux et théoriques sont à disposition pour étudier la lipophilie. Ce travail de thèse se focalise principalement sur le développement ou l'amélioration de certains de ces outils pour permettre leur application à un champ plus large de composés. Voici une brève description de deux de ces outils: 1)La factorisation de la lipophilie en fonction de certaines propriétés structurelles (telle que le volume) propres aux composés permet de développer des modèles théoriques utilisables pour la prédiction de la lipophilie de nouveaux composés ou médicaments. Cette approche est appliquée à l'analyse de la lipophilie de composés neutres ainsi qu'à la lipophilie de composés chargés. 2)La chromatographie liquide à haute pression sur phase inverse (RP-HPLC) est une méthode couramment utilisée pour la détermination expérimentale des valeurs de log Poct.

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Megazol (7) is a 5-nitroimidazole that is highly active against Trypanosoma cruzi and Trypanosoma brucei, as well as drug-resistant forms of trypanosomiasis. Compound 7 is not used clinically due to its mutagenic and genotoxic properties, but has been largely used as a lead compound. Here, we compared the activity of 7 with its 4H-1,2,4-triazole bioisostere (8) in bloodstream forms of T. brucei and T. cruzi and evaluated their activation by T. brucei type I nitroreductase (TbNTR) enzyme. We also analysed the cytotoxic and genotoxic effects of these compounds in whole human blood using Comet and fluorescein diacetate/ethidium bromide assays. Although the only difference between 7 and 8 is the substitution of sulphur (in the thiadiazole in 7) for nitrogen (in the triazole in 8), the results indicated that 8 had poorer antiparasitic activity than 7 and was not genotoxic, whereas 7 presented this effect. The determination of Vmax indicated that although 8 was metabolised more rapidly than 7, it bounds to the TbNTR with better affinity, resulting in equivalent kcat/KM values. Docking assays of 7 and 8 performed within the active site of a homology model of the TbNTR indicating that 8 had greater affinity than 7.

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Abstract : The existence of a causal relationship between the spatial distribution of living organisms and their environment, in particular climate, has been long recognized and is the central principle of biogeography. In turn, this recognition has led scientists to the idea of using the climatic, topographic, edaphic and biotic characteristics of the environment to predict its potential suitability for a given species or biological community. In this thesis, my objective is to contribute to the development of methodological improvements in the field of species distribution modeling. More precisely, the objectives are to propose solutions to overcome limitations of species distribution models when applied to conservation biology issues, or when .used as an assessment tool of the potential impacts of global change. The first objective of my thesis is to contribute to evidence the potential of species distribution models for conservation-related applications. I present a methodology to generate pseudo-absences in order to overcome the frequent lack of reliable absence data. I also demonstrate, both theoretically (simulation-based) and practically (field-based), how species distribution models can be successfully used to model and sample rare species. Overall, the results of this first part of the thesis demonstrate the strong potential of species distribution models as a tool for practical applications in conservation biology. The second objective this thesis is to contribute to improve .projections of potential climate change impacts on species distributions, and in particular for mountain flora. I develop and a dynamic model, MIGCLIM, that allows the implementation of dispersal limitations into classic species distribution models and present an application of this model to two virtual species. Given that accounting for dispersal limitations requires information on seed dispersal, distances, a general methodology to classify species into broad dispersal types is also developed. Finally, the M~GCLIM model is applied to a large number of species in a study area of the western Swiss Alps. Overall, the results indicate that while dispersal limitations can have an important impact on the outcome of future projections of species distributions under climate change scenarios, estimating species threat levels (e.g. species extinction rates) for a mountainous areas of limited size (i.e. regional scale) can also be successfully achieved when considering dispersal as unlimited (i.e. ignoring dispersal limitations, which is easier from a practical point of view). Finally, I present the largest fine scale assessment of potential climate change impacts on mountain vegetation that has been carried-out to date. This assessment involves vegetation from 12 study areas distributed across all major western and central European mountain ranges. The results highlight that some mountain ranges (the Pyrenees and the Austrian Alps) are expected to be more affected by climate change than others (Norway and the Scottish Highlands). The results I obtain in this study also indicate that the threat levels projected by fine scale models are less severe than those derived from coarse scale models. This result suggests that some species could persist in small refugias that are not detected by coarse scale models. Résumé : L'existence d'une relation causale entre la répartition des espèces animales et végétales et leur environnement, en particulier le climat, a été mis en évidence depuis longtemps et est un des principes centraux en biogéographie. Ce lien a naturellement conduit à l'idée d'utiliser les caractéristiques climatiques, topographiques, édaphiques et biotiques de l'environnement afin d'en prédire la qualité pour une espèce ou une communauté. Dans ce travail de thèse, mon objectif est de contribuer au développement d'améliorations méthodologiques dans le domaine de la modélisation de la distribution d'espèces dans le paysage. Plus précisément, les objectifs sont de proposer des solutions afin de surmonter certaines limitations des modèles de distribution d'espèces dans des applications pratiques de biologie de la conservation ou dans leur utilisation pour évaluer l'impact potentiel des changements climatiques sur l'environnement. Le premier objectif majeur de mon travail est de contribuer à démontrer le potentiel des modèles de distribution d'espèces pour des applications pratiques en biologie de la conservation. Je propose une méthode pour générer des pseudo-absences qui permet de surmonter le problème récurent du manque de données d'absences fiables. Je démontre aussi, de manière théorique (par simulation) et pratique (par échantillonnage de terrain), comment les modèles de distribution d'espèces peuvent être utilisés pour modéliser et améliorer l'échantillonnage des espèces rares. Ces résultats démontrent le potentiel des modèles de distribution d'espèces comme outils pour des applications de biologie de la conservation. Le deuxième objectif majeur de ce travail est de contribuer à améliorer les projections d'impacts potentiels des changements climatiques sur la flore, en particulier dans les zones de montagnes. Je développe un modèle dynamique de distribution appelé MigClim qui permet de tenir compte des limitations de dispersion dans les projections futures de distribution potentielle d'espèces, et teste son application sur deux espèces virtuelles. Vu que le fait de prendre en compte les limitations dues à la dispersion demande des données supplémentaires importantes (p.ex. la distance de dispersion des graines), ce travail propose aussi une méthode de classification simplifiée des espèces végétales dans de grands "types de disperseurs", ce qui permet ainsi de d'obtenir de bonnes approximations de distances de dispersions pour un grand nombre d'espèces. Finalement, j'applique aussi le modèle MIGCLIM à un grand nombre d'espèces de plantes dans une zone d'études des pré-Alpes vaudoises. Les résultats montrent que les limitations de dispersion peuvent avoir un impact considérable sur la distribution potentielle d'espèces prédites sous des scénarios de changements climatiques. Cependant, quand les modèles sont utilisés pour évaluer les taux d'extinction d'espèces dans des zones de montages de taille limitée (évaluation régionale), il est aussi possible d'obtenir de bonnes approximations en considérant la dispersion des espèces comme illimitée, ce qui est nettement plus simple d'un point dé vue pratique. Pour terminer je présente la plus grande évaluation à fine échelle d'impact potentiel des changements climatiques sur la flore des montagnes conduite à ce jour. Cette évaluation englobe 12 zones d'études réparties sur toutes les chaines de montages principales d'Europe occidentale et centrale. Les résultats montrent que certaines chaines de montagnes (les Pyrénées et les Alpes Autrichiennes) sont projetées comme plus sensibles aux changements climatiques que d'autres (les Alpes Scandinaves et les Highlands d'Ecosse). Les résultats obtenus montrent aussi que les modèles à échelle fine projettent des impacts de changement climatiques (p. ex. taux d'extinction d'espèces) moins sévères que les modèles à échelle large. Cela laisse supposer que les modèles a échelle fine sont capables de modéliser des micro-niches climatiques non-détectées par les modèles à échelle large.

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Background: Current advances in genomics, proteomics and other areas of molecular biology make the identification and reconstruction of novel pathways an emerging area of great interest. One such class of pathways is involved in the biogenesis of Iron-Sulfur Clusters (ISC). Results: Our goal is the development of a new approach based on the use and combination of mathematical, theoretical and computational methods to identify the topology of a target network. In this approach, mathematical models play a central role for the evaluation of the alternative network structures that arise from literature data-mining, phylogenetic profiling, structural methods, and human curation. As a test case, we reconstruct the topology of the reaction and regulatory network for the mitochondrial ISC biogenesis pathway in S. cerevisiae. Predictions regarding how proteins act in ISC biogenesis are validated by comparison with published experimental results. For example, the predicted role of Arh1 and Yah1 and some of the interactions we predict for Grx5 both matches experimental evidence. A putative role for frataxin in directly regulating mitochondrial iron import is discarded from our analysis, which agrees with also published experimental results. Additionally, we propose a number of experiments for testing other predictions and further improve the identification of the network structure. Conclusion: We propose and apply an iterative in silico procedure for predictive reconstruction of the network topology of metabolic pathways. The procedure combines structural bioinformatics tools and mathematical modeling techniques that allow the reconstruction of biochemical networks. Using the Iron Sulfur cluster biogenesis in S. cerevisiae as a test case we indicate how this procedure can be used to analyze and validate the network model against experimental results. Critical evaluation of the obtained results through this procedure allows devising new wet lab experiments to confirm its predictions or provide alternative explanations for further improving the models.

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Almost identical polyglutamine-containing proteins with unknown structures have been found in human, mouse and rat genomes (GenBank AJ277365, AF525300, AY879229). We infer that an identical new gene (RING) finger domain of real interest is located in each C-terminal segment. A three-dimensional (3-D) model was generated by remote homology modeling and the functional implications are discussed. The model consists of 65 residues from terminal position 707 to 772 of the human protein with a total length of 796 residues. The 3-D model predicts a ubiquitin-protein ligase (E3) as a binding site for ubiquitin-conjugating enzyme (E2). Both enzymes are part of the ubiquitin pathway to label unwanted proteins for subsequent enzymatic degradation. The molecular contact specificities are suggested for both the substrate recognition and the residues at the possible E2-binding surface. The predicted structure, of a ubiquitin-protein ligase (E3, enzyme class number 6.3.2.19, CATH code 3.30.40.10.4) may contribute to explain the process of ubiquitination. The 3-D model supports the idea of a C3HC4-RING finger with a partially new pattern. The putative E2-binding site is formed by a shallow hydrophobic groove on the surface adjacent to the helix and one zinc finger (L722, C739, P740, P741, R744). Solvent-exposed hydrophobic amino acids lie around both zinc fingers (I717, L722, F738, or P765, L766, V767, V733, P734). The 3-D structure was deposited in the protein databank theoretical model repository (2B9G, RCSB Protein Data Bank, NJ).

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L'insuffisance cardiaque est une maladie à grande incidence dont le traitement définitif est difficile. Les pompes d'assistance ventriculaire ont été proposées comme thérapie alternative à long terme, mais la technologie est relativement jeune et selon son design, axial ou centrifuge, le dispositif favorise soit l'hémolyse, soit la stagnation de l'écoulement sanguin. Les pompes à écoulement mixte, combinant certaines propriétés des deux types, ont été proposées comme solution intermédiaire. Pour évaluer leurs performances, nous avons effectué des comparaisons numériques entre huit pompes, deux axiales, deux centrifuges, et quatre mixtes, en employant un modèle Windkessel du système cardiovasculaire avec paramètres optimisés pour l'insuffisance cardiaque résolu avec une méthode Radau IIA3, une méthode de résolution de système d'équations différentielles ordinaires L-stable appartenant à la famille des méthodes Runge-Kutta implicites. Nos résultats semblent suggérer que les pompes d'assistance mixtes ne démontrent qu'un léger avantage comparativement aux autres types en terme de performance optimale dans le cas de l'insuffisance cardiaque, mais il faudrait effectuer plus d'essais numériques avec un modèle plus complet, entre autres avec contrôles nerveux implémentés.

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Blumeria graminis is an economically important obligate plant-pathogenic fungus, whose entire genome was recently sequenced and manually annotated using ab initio in silico predictions [7]. Employing large scale proteogenomic analysis we are now able to verify independently the existence of proteins predicted by 24% of open reading frame models. We compared the haustoria and sporulating hyphae proteomes and identified 71 proteins exclusively in haustoria, the feeding and effector-delivery organs of the pathogen. These proteins are ‘significantly smaller than the rest of the protein pool and predicted to be secreted. Most do not share any similarities with Swiss–Prot or Trembl entries nor possess any identifiable Pfam domains. We used a novel automated prediction pipeline to model the 3D structures of the proteins, identify putative ligand binding sites and predict regions of intrinsic disorder. This revealed that the protein set found exclusively in haustoria is significantly less disordered than the rest of the identified Blumeria proteins or random (and representative) protein sets generated from the yeast proteome. For most of the haustorial proteins with unknown functions no good templates could be found, from which to generate high quality models. Thus, these unknown proteins present potentially new protein folds that can be specific to the interaction of the pathogen with its host.

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Serines proteinases inhibitors (PIs) are widely distributed in nature and are able to inhibit both in vitro and in vivo enzymatic activites. Seed PIs in than leguminous are classified in seven families, Bowman-Birk and Kunitz type families that most studied representing an important role in the first line of defense toward insects pests. Some Kunitz type inhibitors possess activities serine and cysteine for proteinases named bifunctional inhibitor, as ApTKI the inhibitor isolate from seed of Adenanthera pavonina. The A. pavonina inhibitor presenting the uncommon property and was used for interaction studies between proteinases serine (trypsin) and cysteine (papain). In order to determinate the in vitro interaction of ApTKI against enzymes inhibitor purification was carried cut by using chromatographic techniques and inhibition assays. The 3D model of the bifunctional inhibitor ApTKI was constructed SWISS-MODEL program by homology modeling using soybean trypsin inhibitor (STI, pdb:1ba7), as template which presented 40% of identity to A. pavonina inhibitor. Model quality was evaluated by PROCHECK program. Moreover in silico analyzes of formed complex between the enzymes and ApTKI was evaluated by HEX 4.5 program. In vitro results confirmed the inhibitory assays, where the inhibitor presented the ability to simultaneously inhibit trypsin and papain. The residues encountered in the inhibitor model of folder structural three-dimensional that make contact to enzymes target coud explain the specificity pattern against serine and cysteine proteinases

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Chitin is an important structural component of the cellular wall of fungi and exoskeleton of many invertebrate plagues, such as insects and nematodes. In digestory systems of insects it forms a named matrix of peritrophic membrane. One of the most studied interaction models protein-carbohydrate is the model that involves chitin-binding proteins. Among the involved characterized domains already in this interaction if they detach the hevein domain (HD), from of Hevea brasiliensis (Rubber tree), the R&R consensus domain (R&R), found in cuticular proteins of insects, and the motif called in this study as conglicinin motif (CD), found in the cristallography structure of the β-conglicinin bounded with GlcNac. These three chitin-binding domains had been used to determine which of them could be involved in silico in the interaction of Canavalia ensiformis and Vigna unguiculata vicilins with chitin, as well as associate these results with the WD50 of these vicilins for Callosobruchus maculatus larvae. The technique of comparative modeling was used for construction of the model 3D of the vicilin of V. unguiculata, that was not found in the data bases. Using the ClustalW program it was gotten localization of these domains in the vicilins primary structure. The domains R&R and CD had been found with bigger homology in the vicilins primary sequences and had been target of interaction studies. Through program GRAMM models of interaction ( dockings ) of the vicilins with GlcNac had been gotten. The results had shown that, through analysis in silico, HD is not part of the vicilins structures, proving the result gotten with the alignment of the primary sequences; the R&R domain, although not to have structural similarity in the vicilins, probably it has a participation in the activity of interaction of these with GlcNac; whereas the CD domain participates directly in the interaction of the vicilins with GlcNac. These results in silico show that the amino acid number, the types and the amount of binding made for the CD motif with GlcNac seem to be directly associates to the deleterious power that these vicilins show for C. maculatus larvae. This can give an initial step in the briefing of as the vicilins interact with alive chitin in and exert its toxic power for insects that possess peritrophic membrane

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Protein-protein interactions (PPIs) are essential for understanding the function of biological systems and have been characterized using a vast array of experimental techniques. These techniques detect only a small proportion of all PPIs and are labor intensive and time consuming. Therefore, the development of computational methods capable of predicting PPIs accelerates the pace of discovery of new interactions. This paper reports a machine learning-based prediction model, the Universal In Silico Predictor of Protein-Protein Interactions (UNISPPI), which is a decision tree model that can reliably predict PPIs for all species (including proteins from parasite-host associations) using only 20 combinations of amino acids frequencies from interacting and non-interacting proteins as learning features. UNISPPI was able to correctly classify 79.4% and 72.6% of experimentally supported interactions and non-interacting protein pairs, respectively, from an independent test set. Moreover, UNISPPI suggests that the frequencies of the amino acids asparagine, cysteine and isoleucine are important features for distinguishing between interacting and non-interacting protein pairs. We envisage that UNISPPI can be a useful tool for prioritizing interactions for experimental validation. © 2013 Valente et al.