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Nouvelles Methodes De Calcul Pour La Prediction Des Interactions Proteine Proteine Au Niveau Structural
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Book Synopsis Nouvelles méthodes de calcul pour la prédiction des interactions protéine-protéine au niveau structural by : Petr Popov
Download or read book Nouvelles méthodes de calcul pour la prédiction des interactions protéine-protéine au niveau structural written by Petr Popov and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Le docking moléculaire est une méthode permettant de prédire l'orientation d'une molécule donnée relativement à une autre lorsque celles-ci forment un complexe. Le premier algorithme de docking moléculaire a vu jour en 1990 afin de trouver de nouveaux candidats face à la protéase du VIH-1. Depuis, l'utilisation de protocoles de docking est devenue une pratique standard dans le domaine de la conception de nouveaux médicaments. Typiquement, un protocole de docking comporte plusieurs phases. Il requiert l'échantillonnage exhaustif du site d'interaction où les éléments impliqués sont considérées rigides. Des algorithmes de clustering sont utilisés afin de regrouper les candidats à l'appariement similaires. Des méthodes d'affinage sont appliquées pour prendre en compte la flexibilité au sein complexe moléculaire et afin d'éliminer de possibles artefacts de docking. Enfin, des algorithmes d'évaluation sont utilisés pour sélectionner les meilleurs candidats pour le docking. Cette thèse présente de nouveaux algorithmes de protocoles de docking qui facilitent la prédiction des structures de complexes protéinaires, une des cibles les plus importantes parmi les cibles visées par les méthodes de conception de médicaments. Une première contribution concerne l'algorithme Docktrina qui permet de prédire les conformations de trimères protéinaires triangulaires. Celui-ci prend en entrée des prédictions de contacts paire-à-paire à partir d'hypothèse de corps rigides. Ensuite toutes les combinaisons possibles de paires de monomères sont évalués à l'aide d'un test de distance RMSD efficace. Cette méthode à la fois rapide et efficace améliore l'état de l'art sur les protéines trimères. Deuxièmement, nous présentons RigidRMSD une librairie C++ qui évalue en temps constant les distances RMSD entre conformations moléculaires correspondant à des transformations rigides. Cette librairie est en pratique utile lors du clustering de positions de docking, conduisant à des temps de calcul améliorés d'un facteur dix, comparé aux temps de calcul des algorithmes standards. Une troisième contribution concerne KSENIA, une fonction d'évaluation à base de connaissance pour l'étude des interactions protéine-protéine. Le problème de la reconstruction de fonction d'évaluation est alors formulé et résolu comme un problème d'optimisation convexe. Quatrièmement, CARBON, un nouvel algorithme pour l'affinage des candidats au docking basés sur des modèles corps-rigides est proposé. Le problème d'optimisation de corps-rigides est vu comme le calcul de trajectoires quasi-statiques de corps rigides influencés par la fonction énergie. CARBON fonctionne aussi bien avec un champ de force classique qu'avec une fonction d'évaluation à base de connaissance. CARBON est aussi utile pour l'affinage de complexes moléculaires qui comportent des clashes stériques modérés à importants. Finalement, une nouvelle méthode permet d'estimer les capacités de prédiction des fonctions d'évaluation. Celle-ci permet d'évaluer de façon rigoureuse la performance de la fonction d'évaluation concernée sur des benchmarks de complexes moléculaires. La méthode manipule la distribution des scores attribués et non pas directement les scores de conformations particulières, ce qui la rend avantageuse au regard des critères standard basés sur le score le plus élevé. Les méthodes décrites au sein de la thèse sont testées et validées sur différents benchmarks protéines-protéines. Les algorithmes implémentés ont été utilisés avec succès pour la compétition CAPRI concernant la prédiction de complexes protéine-protéine. La méthodologie développée peut facilement être adaptée pour de la reconnaissance d'autres types d'interactions moléculaires impliquant par exemple des ligands, de l'ARN... Les implémentations en C++ des différents algorithmes présentés seront mises à disposition comme SAMSON Elements de la plateforme logicielle SAMSON sur http://www.samson-connect.net ou sur http://nano-d.inrialpes.fr/software.
Book Synopsis Calcul efficace de la structure des protéines à partir de contacts évolutifs by : Fabrice Allain
Download or read book Calcul efficace de la structure des protéines à partir de contacts évolutifs written by Fabrice Allain and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Les méthodes de prédiction structurale constituent une alternative relativement efficace aux approches expérimentales pour donner un premier aperçu du repliement natif d'une protéine. L'écart entre le nombre de structures et de séquences protéiques disponibles dans les bases de données ne cesse en effet de croître depuis l'arrivée des technologies de séquençage à haut débit. Cette forte croissance des informations génomiques a remis à l'ordre du jour des techniques modélisant les données capturées au cours de l'évolution. La conservation d'une fonction protéique impose de fortes contraintes sur les contacts impliqués dans le repliement et la fonction se traduisant par une trajectoire évolutive commune. Une fois détectées, ces interactions peuvent aider à modéliser la conformation d'une protéine. Les méthodes résolvant la structure tridimensionnelle des protéines à partir des données évolutives présentent encore plusieurs limitations notamment pour la détection des contacts faux positifs. Ces problèmes restent similaires à ceux rencontrés en détermination de structure par spectrométrie de Résonnance Magnétique Nucléaire où l'intégration des données est un processus clairement établit et en grande partie automatisé. Le logiciel ARIA (Ambiguous Restraints for Iterative Assignment) utilise le concept de contraintes de distances ambiguës et suit un processus itératif afin d'attribuer et d'affiner la liste des noyaux proches dans l'espace pour calculer un ensemble de modèles structuraux en accord avec les données. Ce travail a pour objectif d'adapter cette approche pour prédire de novo la structure d'une protéine en utilisant l'information évolutive.
Book Synopsis Protein Structure Prediction by : David Webster
Download or read book Protein Structure Prediction written by David Webster and published by Springer Science & Business Media. This book was released on 2008-02-03 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: The number of protein sequences grows each year, yet the number of structures deposited in the Protein Data Bank remains relatively small. The importance of protein structure prediction cannot be overemphasized, and this volume is a timely addition to the literature in this field. Protein Structure Prediction: Methods and Protocols is a departure from the normal Methods in Molecular Biology series format. By its very nature, protein structure prediction demands that there be a greater mix of theoretical and practical aspects than is normally seen in this series. This book is aimed at both the novice and the experienced researcher who wish for detailed inf- mation in the field of protein structure prediction; a major intention here is to include important information that is needed in the day-to-day work of a research scientist, important information that is not always decipherable in scientific literature. Protein Structure Prediction: Methods and Protocols covers the topic of protein structure prediction in an eclectic fashion, detailing aspects of pred- tion that range from sequence analysis (a starting point for many algorithms) to secondary and tertiary methods, on into the prediction of docked complexes (an essential point in order to fully understand biological function). As this volume progresses, the authors contribute their expert knowledge of protein structure prediction to many disciplines, such as the identification of motifs and domains, the comparative modeling of proteins, and ab initio approaches to protein loop, side chain, and protein prediction.
Book Synopsis Computational Methods for Protein Structure Prediction and Modeling by : Ying Xu
Download or read book Computational Methods for Protein Structure Prediction and Modeling written by Ying Xu and published by Springer Science & Business Media. This book was released on 2010-05-05 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume Two of this two-volume sequence presents a comprehensive overview of protein structure prediction methods and includes protein threading, De novo methods, applications to membrane proteins and protein complexes, structure-based drug design, as well as structure prediction as a systems problem. A series of appendices review the biological and chemical basics related to protein structure, computer science for structural informatics, and prerequisite mathematics and statistics.
Book Synopsis Introduction to Protein Structure Prediction by : Huzefa Rangwala
Download or read book Introduction to Protein Structure Prediction written by Huzefa Rangwala and published by John Wiley & Sons. This book was released on 2011-03-16 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: A look at the methods and algorithms used to predict protein structure A thorough knowledge of the function and structure of proteins is critical for the advancement of biology and the life sciences as well as the development of better drugs, higher-yield crops, and even synthetic bio-fuels. To that end, this reference sheds light on the methods used for protein structure prediction and reveals the key applications of modeled structures. This indispensable book covers the applications of modeled protein structures and unravels the relationship between pure sequence information and three-dimensional structure, which continues to be one of the greatest challenges in molecular biology. With this resource, readers will find an all-encompassing examination of the problems, methods, tools, servers, databases, and applications of protein structure prediction and they will acquire unique insight into the future applications of the modeled protein structures. The book begins with a thorough introduction to the protein structure prediction problem and is divided into four themes: a background on structure prediction, the prediction of structural elements, tertiary structure prediction, and functional insights. Within those four sections, the following topics are covered: Databases and resources that are commonly used for protein structure prediction The structure prediction flagship assessment (CASP) and the protein structure initiative (PSI) Definitions of recurring substructures and the computational approaches used for solving sequence problems Difficulties with contact map prediction and how sophisticated machine learning methods can solve those problems Structure prediction methods that rely on homology modeling, threading, and fragment assembly Hybrid methods that achieve high-resolution protein structures Parts of the protein structure that may be conserved and used to interact with other biomolecules How the loop prediction problem can be used for refinement of the modeled structures The computational model that detects the differences between protein structure and its modeled mutant Whether working in the field of bioinformatics or molecular biology research or taking courses in protein modeling, readers will find the content in this book invaluable.
Book Synopsis Exploitation des algorithmes génétiques pour la prédiction de structures protéine-protéine by : Thomas Bourquard
Download or read book Exploitation des algorithmes génétiques pour la prédiction de structures protéine-protéine written by Thomas Bourquard and published by . This book was released on 2009 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: Les fonctions de la majorité des protéines sont surbordonnées à l’interaction avec un ou plusieurs partenaires : acide nucléiques, autres protéines,... La plupart de ces interactions sont transitoires, difficiles à détecter expérimentalement et leur structures sont souvent impossible à obtenir. C’est pourquoi la prédiction in silico de l’existence des ces interactions et la structure du complexe résultant ont été l’objet de nombreuses études depuis plus d’une décennie maintenant. Pour autant les protéines sont des objets complexes et les méthodes informatiques classiques sont trop « gourmandes » en temps pour l’exploration à grande échelle de l’interactome des différents organismes. Dans ce contexte de développement d’une méthode de docking protéine-protéine haut débit nous présenterons ici l’implémentation d’une nouvelle méthode d’amarrage, celle-ci est basée sur : L’utilisation de deux types de formalismes : les tessellations de Voronoï et Laguerre permettant la manipulation de modèles géométriques simplifiés permettant une bonne modélisation des complexes et des temps de calcul plus raisonnable qu’en représentation atomique. L’utilisation et l’optimisation d’algorithmes d’apprentissage (algorithmes génétiques) permettant d’isoler les conformations les plus pertinentes entre deux partenaires protéiques. Une méthode d’évaluation basée le clustering de méta-attributs calculés au niveau de l’interface permettant de trier au mieux ce sous-ensemble de conformations candidates.
Book Synopsis Protein Structure Prediction : A Practical Approach by : Michael J. E. Sternberg
Download or read book Protein Structure Prediction : A Practical Approach written by Michael J. E. Sternberg and published by Oxford University Press, USA. This book was released on 1996-11-28 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-dimensional structure of proteins is a key factor in their biological activity. There is an increasing need to be able to predict the structure of a protein once its amino-acid sequence is known; this book presents practical methods of achieving that ambitious aim, using the latest computer modelling algorithms. - ;The prediction of the three-dimensional structure of a protein from its sequence is a problem faced by an ever-increasing number of biological scientists as they strive to utilize genetic information. The increasing sizes of the sequence and structural databases, the improvements in computing power, and the deeper understanding of the principles of protein structure have led to major developments in the field in the last few years. This book presents practical computer-based methods using the latest computer modelling algorithms. -
Book Synopsis Prediction of Protein Structures, Functions, and Interactions by : Janusz M. Bujnicki
Download or read book Prediction of Protein Structures, Functions, and Interactions written by Janusz M. Bujnicki and published by John Wiley & Sons. This book was released on 2008-12-23 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: The growing flood of new experimental data generated by genome sequencing has provided an impetus for the development of automated methods for predicting the functions of proteins that have been deduced by sequence analysis and lack experimental characterization. Prediction of Protein Structures, Functions and Interactions presents a comprehensive overview of methods for prediction of protein structure or function, with the emphasis on their availability and possibilities for their combined use. Methods of modeling of individual proteins, prediction of their interactions, and docking of complexes are put in the context of predicting gene ontology (biological process, molecular function, and cellular component) and discussed in the light of their contribution to the emerging field of systems biology. Topics covered include: first steps of protein sequence analysis and structure prediction automated prediction of protein function from sequence template-based prediction of three-dimensional protein structures: fold-recognition and comparative modelling template-free prediction of three-dimensional protein structures quality assessment of protein models prediction of molecular interactions: from small ligands to large protein complexes macromolecular docking integrating prediction of structure, function, and interactions Prediction of Protein Structures, Functions and Interactions focuses on the methods that have performed well in CASPs, and which are constantly developed and maintained, and are freely available to academic researchers either as web servers or programs for local installation. It is an essential guide to the newest, best methods for prediction of protein structure and functions, for researchers and advanced students working in structural bioinformatics, protein chemistry, structural biology and drug discovery.
Book Synopsis Computational Methods for Protein Structure Prediction and Modeling by : Ying Xu
Download or read book Computational Methods for Protein Structure Prediction and Modeling written by Ying Xu and published by Springer Science & Business Media. This book was released on 2007-08-24 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume One of this two-volume sequence focuses on the basic characterization of known protein structures, and structure prediction from protein sequence information. Eleven chapters survey of the field, covering key topics in modeling, force fields, classification, computational methods, and structure prediction. Each chapter is a self contained review covering definition of the problem and historical perspective; mathematical formulation; computational methods and algorithms; performance results; existing software; strengths, pitfalls, challenges, and future research.
Book Synopsis Development of Structure-based Computational Methods for Prediction and Design of Protein-protein Interactions by : Brian Gregory Pierce
Download or read book Development of Structure-based Computational Methods for Prediction and Design of Protein-protein Interactions written by Brian Gregory Pierce and published by . This book was released on 2008 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Protein-protein interactions play a key role in the functioning of cells and pathways, and understanding these interactions on a physical and structural level can help greatly in developing therapeutics for diseases. The large amount of protein structures available presents an immense opportunity to model and predict protein interactions using computational techniques. Here we describe the development of algorithms to predict protein complex structures (referred to as protein docking) and to design proteins to improve their interaction affinities. We also present experimental results validating our protein design approach. The protein docking work we present includes the symmetric multimer docking program M-ZDOCK as well as ZRANK which rescores docking predictions using a weighted potential. Both programs have been successful when applied to docking benchmarks and in the CAPRI experiment. In addition, we have used the M-ZDOCK program to produce a tetrameric model for a disease-associated protein, the latent nuclear antigen of the Kaposi's sarcoma-associated herpesvirus. We have also developed a protein design algorithm to improve the binding between two proteins, given their complex structure This was applied to a T cell receptor (TCR) to enhance its binding to the Major Histocompatibility Complex and peptide. Several of the point mutations predicted by our algorithm were verified experimentally to bind several times stronger than wild type; we then combined these mutations to produce a TCR with approximately 100-fold affinity improvement. Further testing of combinations of TCR point mutations has led to striking results regarding the kinetics and cooperativity of the mutations. Finally, we have used our protein design algorithm to predict designability of protein complexes from the Protein Data Bank, and identified the complex between CD4 and HIV gp120 as a target for future structure-based design efforts. Preliminary results for this project are given.
Book Synopsis Modélisation et score de complexes protéine-ARN by : Adrien Guilhot-Gaudeffroy
Download or read book Modélisation et score de complexes protéine-ARN written by Adrien Guilhot-Gaudeffroy and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cette thèse présente des résultats dans le domaine de la prédiction d'interactions protéine-ARN. C'est un domaine de recherche très actif, pour lequel la communauté internationale organise régulièrement des compétitions pour évaluer différentes techniques de prédictions in silico d'interactions protéine-protéine et protéine-ARN sur des données benchmarks (CAPRI, Critical Assessment of PRedictedInteractions), par prédiction en aveugle et en temps limité. Dans ce cadre, de nombreuses approches reposant sur des techniques d'apprentissage supervisé ont récemment obtenus de très bons résultats.Nos travaux s'inscrivent dans cette démarche.Nous avons travaillé sur des jeux de données de 120 complexes protéine-ARN extraits de la PRIDB non redondante (Protein-RNA Interface DataBase, banque de données de référence pour les interactions protéine-ARN). La méthodologie de prédiction d'interactions protéine-ARN a aussi été testée sur 40 complexes issus de benchmarks de l'état de l'art et indépendants des complexes de la PRIDB non redondante. Le faible nombre de structures natives et la difficulté de générer in silico des structures identiques à la solution in vivo nous a conduit à mettre en place une stratégie de génération de candidats par perturbation de l'ARN partenaire d'un complexe protéine-ARN natif. Les candidats ainsi obtenus sont considérés comme des conformations presque-natives si elles sont suffisamment proches du natif. Les autres candidats sont des leurres. L'objectif est de pouvoir identifier les presque natifs parmi l'ensemble des candidats potentiels, par apprentissage supervisé d'une fonction de score.Nous avons conçu pour l'évaluation des fonctions de score une méthodologie de validation croisée originale appelée le leave-"one-pdb"-out, où il existe autant de strates que de complexes protéine-ARN et où chaque strate est constituée des candidats générés à partir d'un complexe. L'une des approches présentant les meilleures performances à CAPRI est l'approche RosettaDock, optimisée pour la prédiction d'interactions protéine-protéine. Nous avons étendu la fonction de score native de RosettaDock pour résoudre la problématique protéine-ARN. Pour l'apprentissage de cette fonction de score, nous avons adapté l'algorithme évolutionnaire ROGER (ROC-based Genetic LearnER) à l'apprentissage d'une fonction logistique. Le gain obtenu par rapport à la fonction native est significatif.Nous avons aussi mis au point d'autres modèles basés sur des approches de classifieurs et de métaclassifieurs, qui montrent que des améliorations sont encore possibles.Dans un second temps, nous avons introduit et mis en oeuvre une nouvelle stratégie pour l'évaluation des candidats qui repose sur la notion de prédiction multi-échelle. Un candidat est représenté à la fois au niveau atomique, c'est-à-dire le niveau de représentation le plus détaillé, et au niveau dit “gros-grain”où nous utilisons une représentation géométrique basée sur des diagrammes de Voronoï pour regrouper ensemble plusieurs composants de la protéine ou de l'ARN. L'état de l'art montre que les diagrammes de Voronoï ont déjà permis d'obtenir de bons résultats pour la prédiction d'interactions protéine-protéine. Nous en évaluons donc les performances après avoir adapté le modèle à la prédiction d'interactions protéine-ARN. L'objectif est de pouvoir rapidement identifier la zone d'interaction (épitope) entre la protéine et l'ARN avant d'utiliser l'approche atomique, plus précise,mais plus coûteuse en temps de calcul. L'une des difficultés est alors de pouvoir générer des candidats suffisamment diversifiés. Les résultats obtenus sont prometteurs et ouvrent desperspectives intéressantes. Une réduction du nombre de paramètres impliqués de même qu'une adaptation du modèle de solvant explicite pourraient en améliorer les résultats.
Book Synopsis Structure-based Algorithms for Protein-protein Interaction Prediction by : Raghavendra Hosur
Download or read book Structure-based Algorithms for Protein-protein Interaction Prediction written by Raghavendra Hosur and published by . This book was released on 2012 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Protein-protein interactions (PPIs) play a central role in all biological processes. Akin to the complete sequencing of genomes, complete descriptions of interactomes is a fundamental step towards a deeper understanding of biological processes, and has a vast potential to impact systems biology, genomics, molecular biology and therapeutics. PPIs are critical in maintenance of cellular integrity, metabolism, transcription/ translation, and cell-cell communication. This thesis develops new methods that significantly advance our efforts at structure- based approaches to predict PPIs and boost confidence in emerging high-throughput (HTP) data. The aims of this thesis are, 1) to utilize physicochemical properties of protein interfaces to better predict the putative interacting regions and increase coverage of PPI prediction, 2) increase confidence in HTP datasets by identifying likely experimental errors, and 3) provide residue-level information that gives us insights into structure-function relationships in PPIs. Taken together, these methods will vastly expand our understanding of macromolecular networks. In this thesis, I introduce two computational approaches for structure-based proteinprotein interaction prediction: iWRAP and Coev2Net. iWRAP is an interface threading approach that utilizes biophysical properties specific to protein interfaces to improve PPI prediction. Unlike previous structure-based approaches that use single structures to make predictions, iWRAP first builds profiles that characterize the hydrophobic, electrostatic and structural properties specific to protein interfaces from multiple interface alignments. Compatibility with these profiles is used to predict the putative interface region between the two proteins. In addition to improved interface prediction, iWRAP provides better accuracy and close to 50% increase in coverage on genome-scale PPI prediction tasks. As an application, we effectively combine iWRAP with genomic data to identify novel cancer related genes involved in chromatin remodeling, nucleosome organization and ribonuclear complex assembly - processes known to be critical in cancer. Coev2Net addresses some of the limitations of iWRAP, and provides techniques to increase coverage and accuracy even further. Unlike earlier sequence and structure profiles, Coev2Net explicitly models long-distance correlations at protein interfaces. By formulating interface co-evolution as a high-dimensional sampling problem, we enrich sequence/structure profiles with artificial interacting homologus sequences for families which do not have known multiple interacting homologs. We build a spanning-tree based graphical model induced by the simulated sequences as our interface profile. Cross-validation results indicate that this approach is as good as previous methods at PPI prediction. We show that Coev2Net's predictions correlate with experimental observations and experimentally validate some of the high-confidence predictions. Furthermore, we demonstrate how analysis of the predicted interfaces together with human genomic variation data can help us understand the role of these mutations in disease and normal cells.
Book Synopsis Protein Structure Prediction by : Mohammed Zaki
Download or read book Protein Structure Prediction written by Mohammed Zaki and published by Humana Press. This book was released on 2010-11-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers elements of both the data-driven comparative modeling approach to structure prediction and also recent attempts to simulate folding using explicit or simplified models. Despite the unsolved mystery of how a protein folds, advances are being made in predicting the interactions of proteins with other molecules. Also rapidly advancing are the methods for solving the inverse folding problem, the problem of finding a sequence to fit a structure. This book focuses on the various computational methods for prediction, their successes and their limitations, from the perspective of their most well known practitioners.
Book Synopsis Computational Methods for Protein-protein Interface Prediction by : Benjamin Tribelhorn
Download or read book Computational Methods for Protein-protein Interface Prediction written by Benjamin Tribelhorn and published by . This book was released on 2013 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: Protein-protein interactions underlie all biological processes and are a field of study that has wide implications throughout many other fields including medicine, genetics, biology, and ecology. Proteins are the building blocks and primary actors of life. They work together to accomplish virtually every task within a cell, including, metabolism, signal propagation, immune responses, and cell signaling. This problem is a logical successor to the Human Genome Project: now that we know so much about the DNA of living organisms, how do we advance our knowledge? The Human Genome and other DNA sequencing efforts have provided complete genetic sequences for more than 180 living organisms. However, these efforts fall short of describing or predicting life processes because the sequence of a protein is not enough to elucidate its function. Knowing this, the National Institute of Health started the Protein Structure Initiative, which seeks to increase knowledge of protein structure and has led to an increase in the number of known proteins structures. Unfortunately, even these efforts fall short as there are over 80,000 known protein structures but the function of many is completely unknown. The fledgling field of interface prediction seeks to use this wealth of structural information to be able to describe protein function and drastically increase our understanding of life processes. Presented herein is a novel methodology for solving the protein-protein interface prediction problem leveraging a variety of Computer Science techniques. Specifically detailed is a process for decomposing this 3-dimensional problem into a feature extraction and classification problem using algorithms from computer vision and machine learning.
Book Synopsis Computational Prediction of Protein-Protein Interaction by : Ranjan Kumar Barman
Download or read book Computational Prediction of Protein-Protein Interaction written by Ranjan Kumar Barman and published by LAP Lambert Academic Publishing. This book was released on 2011-12 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt: Protein-protein interactions are extremely valuable towards protein functions and cellular processes or we can say that protein-protein interactions play an important role in living cells. Therefore, if we can control the interactions between proteins, as a result, we can control some functionality of cells. Main functionality of a protein is carried out by its domains. So, domain is a structural or/and functional unit of protein. Behind protein-protein interactions there exist some domain-domain interactions. Therefore, under standing protein-protein interaction at domain level gives a global view of protein-protein interaction network.In this book, we have made an attempt to infer domain-domain interactions from interacting and non-interacting protein pairs then we have predicted protein-protein interactions based on inferred domain-domain interactions.
Book Synopsis Analyse Évolutive, Prédiction Structurale Et Inhibition Des Interactions Protéine-protéine by : Jessica Andreani
Download or read book Analyse Évolutive, Prédiction Structurale Et Inhibition Des Interactions Protéine-protéine written by Jessica Andreani and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Protein-protein interactions are of fundamental importance in virtually all cellular processes. This PhD thesis has focused on the analysis and prediction of these interactions through the combined use of structural data and evolutionary information. In a study of over 1,000 couples of homologous interfaces extracted from a database developed in our team, we uncovered astonishing plasticity in the way interface structure evolves, although we identified some rather invariant features which provide tracks for extracting meaningful information from multiple sequence alignments of binding partners. Consequently, we developed a coarse-grained interface scoring function using a multi-body statistical potential coupled to evolution. This scoring function improves the prediction of protein interfaces and was used among other methods on two practical cases of protein docking. Finally, we developed a robust computational protocol to rationalize the design of peptidic interaction inhibitors.
Book Synopsis Prédiction de la structure des protéines par homologie by : Jonathan Mark Levin
Download or read book Prédiction de la structure des protéines par homologie written by Jonathan Mark Levin and published by . This book was released on 1989 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ce travail présente de nouvelles méthodes pour extraire des informations structurales à partir d'une séquence en acides aminés et l'application de ces méthodes à la modélisation des protéines. Nous avons mis au point un algorithme d'alignement multiple pour des séquences protéiques basé sur l'algorithme de Needleman et Wunsch, mais qui n'est pas limité par le nombre et la taille des séquences protéiques à aligner. Nous avons développé une méthode de prédiction des structures secondaires, la Méthode des Homologues, basée sur les similarités entre peptides, qui prédit correctement 63% des résidus d'acides aminés, pour trois états. Cette méthode prédit correctement 87% des résidus d'une protéine homologue avec une protéine de la base de données. Nous avons utilisé un modèle simplifié de la chaîne polypeptique pour déterminer les limites des calculs par minimisation de l'énergie. Nous avons appliqué ces techniques à la modélisation des protéines de choc thermique (HSP90), du domaine liant l'ADN des protéines régulatrices FixK et Fnr et du domaine liant l'hème de la nitrate réductase de tabac.
