Дисертації з теми "Computational analyses protein"
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Croft, Edward. "Computational analyses of protein-ligand interactions." Thesis, University of York, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.265562.
Повний текст джерелаHaider, Kamran. "Computational analyses of protein-ligand interactions." Thesis, University of York, 2010. http://etheses.whiterose.ac.uk/1242/.
Повний текст джерелаHaberman, N. "Insights into protein-RNA complexes from computational analyses of iCLIP experiments." Thesis, University College London (University of London), 2017. http://discovery.ucl.ac.uk/1568450/.
Повний текст джерелаHenricson, Anna. "Analyses of protein evolution, function, and architecture." Stockholm, 2010. http://diss.kib.ki.se/2010/978-91-7409-753-5/.
Повний текст джерелаYan, Yongpan. "Computational analyses of microbial genomes operons, protein families and lateral gene transfer /." College Park, Md. : University of Maryland, 2005. http://hdl.handle.net/1903/2596.
Повний текст джерелаThesis research directed by: Cell Biology & Molecular Genetics. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
Rajapaksha, Suneth P. "Single Molecule Spectroscopy Studies of Membrane Protein Dynamics and Energetics by Combined Experimental and Computational Analyses." Bowling Green State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1337141955.
Повний текст джерелаChegancas, Rito Tiago Miguel. "Modelling and comparing protein interaction networks using subgraph counts." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:dcc0eb0d-1dd8-428d-b2ec-447a806d6aa8.
Повний текст джерелаJonsson, Pall Freyr. "Computational analysis of protein-protein interaction networks." Thesis, University College London (University of London), 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.439848.
Повний текст джерелаWang, Kai. "Novel computational methods for accurate quantitative and qualitative protein function prediction /." Thesis, Connect to this title online; UW restricted, 2005. http://hdl.handle.net/1773/11488.
Повний текст джерелаAnsari, Sam. "Analysis of protein-protein interactions : a computational approach /." Saarbrücken : VDM Verl. Dr. Müller, 2007. http://deposit.d-nb.de/cgi-bin/dokserv?id=2992987&prov=M&dok_var=1&dok_ext=htm.
Повний текст джерелаTaroni, Chiara. "Computational analysis of protein-carbohydrate interactions." Thesis, University College London (University of London), 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.300932.
Повний текст джерелаLavallée-Adam, Mathieu. "Protein-protein interaction confidence assessment and network clustering computational analysis." Thesis, McGill University, 2014. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=121237.
Повний текст джерелаLes interactions protéine-protéine représentent une source d'information essentielle à la compréhension des divers méchanismes biologiques de la cellule. Cependant, les expériences à haut débit qui identifient ces interactions, comme la purification par affinité, produisent un très grand nombre de faux-positifs. Des méthodes computationelles sont donc requises afin d'extraire de ces ensembles de données les interactions protéine-protéine de grande qualité. Toutefois, même lorsque filtrés, ces ensembles de données forment des réseaux très complexes à analyser. Ces réseaux d'interactions protéine-protéine sont d'une taille importante, d'une grande complexité et requièrent des approches computationelles sophistiquées afin d'en retirer des informations possédant une réelle portée biologique. L'objectif de cette thèse est d'explorer des algorithmes évaluant la qualité d'interactions protéine-protéine et de faciliter l'analyse des réseaux qu'elles composent. Ce travail de recherche est divisé en quatre principaux résultats: 1) une nouvelle approche bayésienne permettant la modélisation des contaminants provenant de la purification par affinité, 2) une nouvelle méthode servant à la découverte et l'évaluation de la qualité d'interactions protéine-protéine à l'intérieur de différents compartiments de la cellule, 3) un algorithme détectant les regroupements statistiquement significatifs de protéines partageant une même annotation fonctionnelle dans un réseau d'interactions protéine-protéine et 4) un outil computationel qui a pour but la découverte de motifs de séquences dans les régions 5' non traduites tout en évaluant le regroupement de ces motifs dans les réseaux d'interactions protéine-protéine.
Maccallum, Robert Matthew. "Computational analysis of protein sequence and structure." Thesis, University College London (University of London), 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285202.
Повний текст джерелаKim, Wan Kyu. "Computational analysis of protein interactions and interfaces." Thesis, University of Cambridge, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.612782.
Повний текст джерелаHayashida, Morihiro. "Computational Analysis and Inference of Protein-Protein Interactions from Domain Information." 京都大学 (Kyoto University), 2005. http://hdl.handle.net/2433/68888.
Повний текст джерелаEnright, A. J. "Computational analysis of protein function within complete genomes." Thesis, University of Cambridge, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.598854.
Повний текст джерелаTerribilini, Michael Joseph. "Computational analysis and prediction of protein-RNA interactions." [Ames, Iowa : Iowa State University], 2008.
Знайти повний текст джерелаDi, Domenico Tomás. "Computational Analysis and Annotation of Proteome Data: Sequence, Structure, Function and Interactions." Doctoral thesis, Università degli studi di Padova, 2014. http://hdl.handle.net/11577/3423805.
Повний текст джерелаCon l'avvento delle tecnologie di sequenziamento moderne, la quantità di dati biologici disponibili ha cominciato a sfidare la nostra capacità di elaborarli. È diventato quindi essenziale sviluppare nuovi strumenti e tecniche capaci di produrre dei risultati basati su grandi moli di informazioni. Questa tesi si concentra sullo sviluppo di tali strumenti computazionali e dei metodi per lo studio dei dati proteici. Viene dapprima presento il lavoro svolto per la comprensione delle proteine intrinsecamente disordinate. Attraverso lo sviluppo di nuovi predittori di disordine, siamo stati in grado di sfruttare le fonti di dati attualmente disponibili per annotare qualsiasi proteina avente sequenza nota. Memorizzando queste predizioni, insieme ai dati provenienti da altre fonti, è stato creato MobiDB. Questa risorsa fornisce una visione completa sulle annotazioni di disordine disponibili per una qualsiasi proteina di interesse presente nel database UniProt. Sulla base delle osservazioni ottenute da questo strumento, è stato quindi creato un workflow di analisi dei dati con l'obiettivo di approfondire la nostra comprensione delle proteine intrinsecamente disordinate. La seconda parte della tesi si concentra sulle proteine ripetute. Il metodo RAPHAEL è stato sviluppato per contribuire nell'identificazione di strutture proteiche ripetute all'interno dei file PDB. Le strutture selezionate da questo strumento sono state poi catalogate manualmente utilizzando uno schema formale di classificazione, e pubblicate quindi come parte del database RepeatsDB. Infine, viene descritto lo sviluppo di strumenti basati su grafi per l'analisi di dati proteici. RING consente all'utente di visualizzare e studiare la struttura di una proteina come una rete di nodi collegati da tra loro da proprietà fisico-chimiche. Il secondo metodo, PANADA, consente all'utente di creare reti di similarità di proteine e di valutare la trasferibilità delle annotazioni funzionali tra cluster diversi.
McDonald, Ian Kevin. "Computational analysis of intramolecular interactions in proteins." Thesis, University College London (University of London), 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.338865.
Повний текст джерелаZotenko, Elena. "Computational methods in protein structure comparison and analysis of protein interaction networks." College Park, Md.: University of Maryland, 2007. http://hdl.handle.net/1903/7621.
Повний текст джерелаThesis research directed by: Dept. of Computer Science. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
Fink, Florian [Verfasser], and Elmar [Akademischer Betreuer] Lang. "Computational analysis of docked protein-protein complexes / Florian Fink. Betreuer: Elmar Lang." Regensburg : Universitätsbibliothek Regensburg, 2011. http://d-nb.info/1022819976/34.
Повний текст джерелаWróblewska, Liliana. "Refinement of reduced protein models with all-atom force fields." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/26606.
Повний текст джерелаSCARDONI, Giovanni. "Computational Analysis of Biological networks." Doctoral thesis, Università degli Studi di Verona, 2010. http://hdl.handle.net/11562/343983.
Повний текст джерелаThis thesis, treating both topological and dynamic points of view, concerns several aspects of biological networks analysis. Regarding the topological analysis of biological networks, the main contribution is the node-oriented point of view of the analysis. It means that instead of concentrating on global properties of the networks, we analyze them in order to extract properties of single nodes. An excellent method to face this problem is to use node centralities. Node centralities allow to identify nodes in a network having a relevant role in the network structure. This can not be enough if we are dealing with a biological network, since the role of a protein depends also on its biological activity that can be detected with lab experiments. Our approach is to integrate centralities analysis and data from biological experiments. A protocol of analysis have been produced, and the CentiScaPe tool for computing network centralities and integrating topological analysis with biological data have been designed and implemented. CentiScaPe have been applied to a human kino-phosphatome network and according to our protocol, kinases and phosphatases with highest centralities values have been extracted creating a new subnetwork of most central kinases and phosphatases. A lab experiment established which of this proteins presented high activation level and through CentiScaPe the proteins with both high centrality values and high activation level have been easily identified. The notion of node centralities interference have also been introduced to deal with central role of nodes in a biological network. It allow to identify which are the nodes that are more affected by the remotion of a particular node measuring the variation on their centralities values when such a node is removed from the network. The application of node centralities interference to the human kino-phosphatome revealed that different proteins affect centralities values of different nodes. Similarly to node centralities interference, the notion of centrality robustness of a node is introduced. This notion reveals if the central role of a node depends on other particular nodes in the network or if the node is ``robust'' in the sense that even if we remove or add other nodes the central role of the node remains almost unchanged. The dynamic aspects of biological networks analysis have been treated from an abstract interpretation point of view. Abstract interpretation is a powerful framework for the analysis of software and is excellent in deriving numerical properties of programs. Dealing with pathways, abstract interpretation have been adapted to the analysis of pathways simulation. Intervals domain and constants domain have been succesfully used to automatically extract information about reactants concentration. The intervals domain allow to determine the range of concentration of the proteins, and the constants domain have been used to know if a protein concentration become constant after a certain time. The other domain of analysis used is the congruences domain that, if applied to pathways simulation can easily identify regular oscillating behaviour in reactants concentration. The use of abstract interpretation allows to execute thousands of simulation and to completely and automatically characterize the behaviour of the pathways. In such a way it can be used also to solve the problem of parameters estimation where missing parameters can be detected with a brute force algorithm combined with the abstract interpretation analysis. The abstract interpretation approach have been succesfully applied to the mitotic oscillator pathway, characterizing the behaviour of the pathway depending on some reactants. To help the analysis of relation between reactants in the network, the notions of variables interference and variables abstract interference have been introduced and adapted to biological pathways simulation. They allow to find relations between properties of different reactants of the pathway. Using the abstract interference techniques we can say, for instance, which range of concentration of a protein can induce an oscillating behaviour of the pathway.
Zhan, Bill Shili. "Computational mutagenesis models for protein activity and stability analysis." Fairfax, VA : George Mason University, 2007. http://hdl.handle.net/1920/2989.
Повний текст джерелаTitle from PDF t.p. (viewed Jan. 22, 2008). Thesis director: Iosif I. Vaisman. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Bioinformatics. Vita: p. 140. Includes bibliographical references (p. 133-139). Also available in print.
Dobbins, Sara E. "Computational Studies of Protein Flexibility using Normal Mode Analysis." Thesis, Imperial College London, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.508940.
Повний текст джерелаNa, Insung. "Computational Analysis of Protein Intrinsic Disorder in Human Diseases." Thesis, University of South Florida, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10603424.
Повний текст джерелаThere are different conformational states of proteins characterized by different Gibbs free energy levels, manifested in folding-unfolding dynamics, for example. Recently, a set of protein states, which require relatively small amount of folding energies, emerged as subjects of intensive research, and proteins or regions characterized by the presence of these states have been termed as ‘Intrinsically Disordered Proteins’ (IDP) and ‘Intrinsically Disordered Protein Regions’ (IDPR), respectively. Predisposition for intrinsic disorder of a query protein is encoded in its amino acid sequence and composition, and can be rather accurately predicted using several intrinsic disorder algorithms. Since pathology of many human diseases can be driven by proteins characterized by high intrinsic disorder scores, research on various disease-associated proteins is often started with the analysis of their intrinsic disorder propensities. In this work, I utilized computational approaches based on the concept of intrinsic disorder to address three health-related issues. To this end, I developed a novel computational platform for disorder-based drug discovery and applied this tool for finding inhibitors of the cancer-related MBD2-NuRD complex, utilized molecular dynamic simulations to explain the effects of mutations on the functionality of the X-linked protoporphyria-related protein ALAS, and used bioinformatics tools to examine the effects of cardiomyopathy-related mutations in cardiac troponin.
Since the complex between the Methyl-CpG-binding domain protein 2 (MBD2) and the Nucleosome Remodeling Deacetylase complex (NuRD) specifically binds to the mCpG-island and blocks tumor suppressor gene expression, finding an inhibitor of this MBD2-NuRD complex is hypothesized to be important for the development of novel anti-cancer drugs. I found that the site, which is responsible for the MBD2 interaction with the transcriptional repressor p66-α (p66α, which is a part of the NuRD complex), is characterized by a specific disorder-to-order transition pattern, this pattern showed a remarkable similarity to the disorder-to-order pattern of the Myc transcription factor binding site for the Max transcription factor. Importantly, several inhibitors of the Myc-Max interaction targeting the disorder-to-order transition site of Myc were previously described. By applying molecular docking at the disorder-to-order transition site of MBD2, two compounds were identified and further evaluated through molecular dynamics simulations. Anti-leukemia and anti-metastasis effectiveness of these compounds was demonstrated in dedicated in vitro and in vivo experiments conducted by our collaborators.
In relation to the defective protein associated with the X-linked protoporphyria (XLPP), the hepta-variant of mouse erythroid 5-aminolevulinate synthase (mALAS2), previously shown to be characterized by a remarkable acceleration of the reaction rate, was investigated through molecular dynamics simulations. In this study, a loop to β-strand transition was observed, and this observation was crucial for a better understanding of the previously described rate-enhancing effects of seven simultaneous variations in the active loop site of this protein.
Finally, a wide spectrum of bioinformatics tools was applied to carefully analyze a potential role of intrinsic disorder in a set of cardiomyopathy-related mutations in the components of human cardiac troponin. This analysis revealed that, in comparison with the wild type troponin, chains containing the disease-associated mutations were typically characterized by a local decrease in intrinsic disorder propensity. These mutations affected some disorder-based protein-protein interaction sites and caused remarkable rearrangements of the complex pattern of post-translational modifications.
Therefore, this work illustrates that inclusion of the protein intrinsic disorder analysis into the arsenal of techniques used by the biomedical researchers represents an important and promising approach that provides novel inputs for the better understanding of protein behavior in relation to human disease at the molecular level. Techniques and methods developed and utilized in this study will significantly contribute to future biomedical research.
Zhang, Wei. "Computational simulation of biological systems studies on protein folding and protein structure prediction /." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file 2.84Mb, 184 p, 2005. http://wwwlib.umi.com/dissertations/fullcit/3181881.
Повний текст джерелаMilburn, Duncan. "Computational analysis of the functional sites in proteins." Thesis, University College London (University of London), 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325850.
Повний текст джерелаSiu, Wing-yan, and 蕭穎欣. "Multiple structural alignment for proteins." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B4068748X.
Повний текст джерелаBaldan, Nikita <1996>. "Computational analysis of NaV1.7 protein variants and tool for 3D visualization of protein structures." Master's Degree Thesis, Università Ca' Foscari Venezia, 2020. http://hdl.handle.net/10579/17572.
Повний текст джерелаGanapathy, Ashwin. "Computational analysis of protein identification using peptide mass fingerprinting approach /." free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p1426056.
Повний текст джерелаBartoli, Lisa <1980>. "Computational methods for the analysis of protein structure and function." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1225/1/Bartoli_Lisa_tesi.pdf.
Повний текст джерелаBartoli, Lisa <1980>. "Computational methods for the analysis of protein structure and function." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1225/.
Повний текст джерелаAllan, Robert Douglas. "Computational analysis and experimental characterisation of natural antiparallel coiled-coil motifs." Thesis, University of Sussex, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343369.
Повний текст джерелаJoughin, Brian Alan. "Novel methods in computational analysis and design of protein-protein interactions : applications to phosphoregulated interactions." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/38630.
Повний текст джерелаIncludes bibliographical references (p. 107-130).
This thesis presents a number of novel computational methods for the analysis and design of protein-protein complexes, and their application to the study of the interactions of phosphopeptides with phosphopeptide-binding domain interactions. A novel protein-protein interaction type, the action-at-a-distance interaction, is described in the complex of the TEM1 P-lactamase with the 3-lactamase inhibitor protein (BLIP). New action-at-a-distance interactions were designed on the surface of BLIP and computed to enhance the affinity of that complex. A new method is described for the characterization and prediction of protein ligand-binding sites. This method was used to analyze the phosphoresidue-contacting sites of known phosphopeptide-binding domains, and to predict the sites of phosphoresidue-contact on some protein domains for which the correct site was not known. The design of a library of variant WW domains that is predicted to be enriched in domains that might have specificity for "pS/pT-Q" peptide ligands is detailed. General methods for designing libraries of degenerate oligonucleotides for expressing protein libraries as accurately as possible are given, and applied to the described WW domain variant library.
by Brian Alan Joughin.
Ph.D.
Mazandu, Gaston Kuzamunu. "Data integration for the analysis of uncharacterized proteins in Mycobacterium tuberculosis." Doctoral thesis, University of Cape Town, 2010. http://hdl.handle.net/11427/11590.
Повний текст джерелаIncludes bibliographical references (leaves 126-150).
Mycobacterium tuberculosis is a bacterial pathogen that causes tuberculosis, a leading cause of human death worldwide from infectious diseases, especially in Africa. Despite enormous advances achieved in recent years in controlling the disease, tuberculosis remains a public health challenge. The contribution of existing drugs is of immense value, but the deadly synergy of the disease with Human Immunodeficiency Virus (HIV) or Acquired Immunodeficiency Syndrome (AIDS) and the emergence of drug resistant strains are threatening to compromise gains in tuberculosis control. In fact, the development of active tuberculosis is the outcome of the delicate balance between bacterial virulence and host resistance, which constitute two distinct and independent components. Significant progress has been made in understanding the evolution of the bacterial pathogen and its interaction with the host. The end point of these efforts is the identification of virulence factors and drug targets within the bacterium in order to develop new drugs and vaccines for the eradication of the disease.
Wróblewska, Liliana. "Refinement of reduced protein models with all-atom force fields." Atlanta, Ga. : Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/26606.
Повний текст джерелаCommittee Chair: Skolnick, Jeffrey; Committee Member: Fernandez, Facundo; Committee Member: Jordan, King; Committee Member: McDonald, John; Committee Member: Sherrill, David. Part of the SMARTech Electronic Thesis and Dissertation Collection.
Zeng, Bo Verfasser], Dmitrij [Akademischer Betreuer] Frishman, Dmitrij [Gutachter] Frishman, and Dieter [Gutachter] [Langosch. "Computational analysis and prediction of protein interaction sites in transmembrane proteins / Bo Zeng ; Gutachter: Dmitrij Frishman, Dieter Langosch ; Betreuer: Dmitrij Frishman." München : Universitätsbibliothek der TU München, 2019. http://d-nb.info/118563794X/34.
Повний текст джерелаDyer, Matthew David. "Pathosystems Biology: Computational Prediction and Analysis of Host-Pathogen Protein Interaction Networks." Diss., Virginia Tech, 2003. http://hdl.handle.net/10919/28141.
Повний текст джерелаPh. D.
Dyer, Matthew D. "Pathosystems Biology: Computational Prediction and Analysis of Host-Pathogen Protein Interaction Networks." Diss., Virginia Tech, 2008. http://hdl.handle.net/10919/28141.
Повний текст джерелаPh. D.
Dahl, Anna Caroline E. "Membrane protein mechanotransduction : computational studies and analytics development." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:67798647-8ed5-46e0-bde9-c71235fe70ba.
Повний текст джерелаPark, Daniel K. (Daniel Kyu). "Web servers, databases, and algorithms for the analysis of protein interaction networks." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/79146.
Повний текст джерелаThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (p. 41-44).
Understanding the cell as a system has become one of the foremost challenges in the post-genomic era. As a result of advances in high-throughput (HTP) methodologies, we have seen a rapid growth in new types of data at the whole-genome scale. Over the last decade, HTP experimental techniques such as yeast two-hybrid assays and co-affinity purification couple with mass spectrometry have generated large amounts of data on protein-protein interactions (PPI) for many organisms. We focus on the sub-domain of systems biology related to understanding the interactions between proteins that ultimately drive all cellular processes. Representing PPIs as a protein interaction network has proved to be a powerful tool for understanding PPIs at the systems level. In this representation, each node represents a protein and each edge between two nodes represents a physical interaction between the corresponding two proteins. With this abstraction, we present algorithms for the prediction and analysis of such PPI networks as well as web servers and databases for their public availability: 1. In many organisms, the coverage of experimental determined PPI data remains relatively noisy and limited. Given two protein sequences, we describe an algorithm, called Struct2Net, to predict if two proteins physically interact, using insights from structural biology and logistic regression. Furthermore, we create a community-wide web-resource that predicts interactions between any protein sequence pair and provides proteome-wide pre-computed PPI predictions for Homo sapiens, Drosophila melanogaster, and Saccharomyces cerevisiae. 2. Comparative analysis of PPI networks across organisms can provide valuable insights into evolutionary conservation. We describe an algorithm, called IsoRank, for global alignment of multiple PPI networks. The algorithm first constructs an eigenvalue problem that models the network and sequence similarity constraints. The solution of the problem describes a k partite graph that is further processed to find the alignments. Furthermore, we create a communitywide web database, called IsoBase, that provides network alignments and orthology mappings for the most commonly studied eukaryotic model organisms: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, and Saccharomyces cerevisiae.
by Daniel K. Park.
S.M.
Sweeney, Deacon John. "A Computational Tool for Biomolecular Structure Analysis Based On Chemical and Enzymatic Modification of Native Proteins." Wright State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=wright1316440232.
Повний текст джерелаGawalapu, Ravi Kumar Root Douglas. "Fluorescence labeling and computational analysis of the strut of myosin's 50 kDa cleft." [Denton, Tex.] : University of North Texas, 2007. http://digital.library.unt.edu/permalink/meta-dc-3974.
Повний текст джерелаDubey, Anshul. "Search and Analysis of the Sequence Space of a Protein Using Computational Tools." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/14115.
Повний текст джерелаHurley, M. G. "Analysis and prediction of the protein folding nucleus using computational and experimental techniques." Thesis, University of Cambridge, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.604825.
Повний текст джерелаGunnarsson, Ida. "Deriving Protein Networks by Combining Gene Expression and Protein Chip Analysis." Thesis, University of Skövde, Department of Computer Science, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-706.
Повний текст джерелаIn order to derive reliable protein networks it has recently been suggested that the combination of information from both gene and protein level is required. In this thesis a combination of gene expression and protein chip analysis was performed when constructing protein networks. Proteins with high affinity to the same substrates and encoded by genes with high correlation is here thought to constitute reliable protein networks. The protein networks derived are unfortunately not as reliable as were hoped for. According to the tests performed, the method derived in this thesis does not perform more than slightly better than chance. However, the poor results can depend on the data used, since mismatching and shortage of data has been evident.
Guo, Weihua. "Computational Modeling of Planktonic and Biofilm Metabolism." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/79669.
Повний текст джерелаPh. D.
Sirota, Leite Fernanda. "Role of the amino acid sequences in domain swapping of the B1 domain of protein G by computation analysis." Doctoral thesis, Universite Libre de Bruxelles, 2007. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210657.
Повний текст джерелаThe stability of the wt and quadruple mutant GB1 monomers was assessed using the software DESIGNER, a fully automatic procedure that selects amino acid sequences likely to stabilize a given backbone structure (Wernisch et al. 2000). Results suggest that 3 of the mutations (L5V, F30V, A34F) have a destabilizing effect. The first mutation (L5V) forms destabilizing interactions with surrounding residues, while the second (F30V) is engaged in unfavorable interactions with the protein backbone, consequently causing local strain. Although the A34F substitution itself is found to contribute favorably to the stability of the monomer, this is achieved only at the expense of forcing the wild type W43 into a highly strained conformation concomitant with the formation of unfavorable interactions with both W43 and V54.
Finally, we also provide evidence that A34F mutation stabilizes the swapped dimer structure. Although we were unable to perform detailed protein design calculations on the dimer, due to the lower accuracy of the model, inspection of its 3D structure reveals that the 34F side chains pack against one another in the core of the swapped structure, thereby forming extensive non-native interactions that have no counterparts in the individual monomers. Their replacement by the much smaller Ala residue is suggested to be significantly destabilizing by creating a large internal cavity, a phenomenon, well known to be destabilizing in other proteins. Our analysis hence proposes that the A34F mutation plays a dual role, that of destabilizing the GB1 monomer structure while stabilizing the swapped dimer conformation.
In addition to the above study, molecular dynamics simulations of the wild type and modeled quadruple mutant GB1 structures were carried out at room and elevated temperatures (450 K) in order to sample the conformational landscape of the protein near its native monomeric state, and to characterize the deformations that occur during early unfolding. This part of the study was aimed at investigating the influence of the amino acid sequence on the conformational properties of the GB1 monomer and the possible link between these properties and the swapping process. Analysis of the room temperature simulations indicates that the mutant GB1 monomer fluctuates more than its wild type counter part. In addition, we find that the C-terminal beta-hairpin is pushed away from the remainder of the structure, in agreement with the fact that this hairpin is the structural element that is exchanged upon domain swapping. The simulations at 450 K reveal that the mutant protein unfolds more readily than the wt, in agreement with its decreased stability. Also, among the regions that unfold early is the alpha-helix C-terminus, where 2 out of the 4 mutations reside. NMR experiments by our collaborators have shown this region to display increased flexibility in the monomeric state of the quadruple mutant.
Our atomic scale investigation has thus provided insights into how sequence modifications can foster domain swapping of GB1. Our findings indicate that the role of the amino acid substitutions is to decrease the stability of individual monomers while at the same time increase the stability of the swapped dimer, through the formation of non-native interactions. Both roles cooperate to foster swapping.
Doctorat en sciences, Spécialisation biologie moléculaire
info:eu-repo/semantics/nonPublished
Gawalapu, Ravi Kumar. "Fluorescence labeling and computational analysis of the strut of myosin's 50 kDa cleft." Thesis, University of North Texas, 2007. https://digital.library.unt.edu/ark:/67531/metadc3974/.
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