No description available.

Proteins govern practically every process in living organisms through inhibiting, activating, or acting on other proteins in different ways. With the large and growing number of known interactions through high throughput screening technologies, experimental determination of atomic-level details of these interactions is nigh impossible. Computational methods such as docking can speed up efforts of understanding these interactions. However, several issues ought to be addressed before docking can replace experimental methods. This thesis describes work on assessment of the state of the art in docking methods, implementation of a machine learning algorithm to improve model ranking and integration of docking with template-based modeling to expand its usage with a special focus on antibody-antigen interactions. Firstly, the performance of docking methods was rigorously assessed by using a diverse set of protein complexes with a special focus on ClusPro, one of the leading rigid-body docking servers. Different strengths and potential areas of improvement for ClusPro and rigid-body docking methods in general were highlighted. Secondly, one of the major short-comings of docking noted in the first project, poor ranking of good models, was addressed. A regression-based machine learning algorithm was introduced to improve the ranking. Finally, a server was developed to tackle the challenge of epitope mapping by integrating template-based modeling with docking. An intuitive ensemble approach to scoring residue likelihood using docking poses and different homologues is shown to yield great success. In addition to shifting docking’s purpose of conformational search to interface identification, this server also allows users to start with protein sequence inputs. / 2022-09-28T00:00:00Z

No description available.

Thesis (Ph. D.)--University of Washington, 2004. / Vita. Includes bibliographical references (leaves 72-83).

O Vírus Zika é um arbovírus pertencente à família Flaviviridae e ao gênero Flavivirus, é constituído por RNA de cadeia simples senso positivo e foi primeiramente descrito em 1947 na floresta de Ziika, em Uganda. Este estudo, visa mapear os epitopos do Vírus Zika (ZIKV), experimento que nos permite avaliar e compreender a resposta imune do hospedeiro contra o vírus por meio da detecção de regiões imunodominantes nas proteínas virais. O processo de identificação dos epitopos de ZIKV foi realizado pela técnica de spot synthesis, que se baseia em arranjos de peptídeos relacionados às proteínas do ZIKV. Amostras de soro de pacientes residentes em áreas endêmicas de arboviroses, mães e bebês que apresentaram sintomatologia típica foram selecionadas e triadas pelo método de ELISA e PCR real time. Sequências de referência do vírus foram submetidas a análises in sílico, para a determinação das áreas de interação na superfície da proteína e suas características antigênicas, para efeito de comparação com a resposta observada pelas amostras. Os experimentos evidenciaram um alta antigenicidade nas proteínas estruturais do vírus, e em nas não-estruturais 1,3 e 5. / The Zika virus is an arbovirus belonging to the genus Flavivirus of the Flaviridae family. It consists of single-stranded positive-sense RNA and was first described in 1947 in the Ziika Forest in Uganda. This study aims to map the Zika virus (ZIKV) epitopes, in an experimental design that allows us to evaluate and understand the immune response of the host against the virus by detecting immunodominant regions in the viral proteins. The process of identification of the ZIKV epitopes was performed by the spot synthesis technique, which is based on peptide arrangements related to the ZIKV proteins. Serum samples from patients living in arboviruses endemic areas, mothers and infants presenting typical symptoms were selected and screened by ELISA and real time PCR. Reference sequences of the virus were submitted to in silico analyzes to determine the interaction areas on the surface of the protein and its antigenic characteristics, for comparison with the response observed by using serum samples. The experiments demonstrated a high antigenicity in the structural proteins of the virus, and in the non-structural proteins 1, 3 and 5.

Plasmodium vivax Duffy binding protein (DBP) is an essential ligand for reticulocyte invasion making it a premier asexual blood stage vaccine candidate. However, strain-specific immunity due to DBPII allelic variation may complicate vaccine efficacy, suggesting that an effective DBPII vaccine needs to target immune responses to conserved epitopes that are potential targets of strain-transcending neutralizing immunity. Anti DBPII monoclonal antibodies, which were previously characterized by COS7 cell binding assay as inhibitory and non-inhibitory to DBPII-erythrocyte binding, were mapped to DBPII gene fragment libraries using phage display. Inhibitory mAb 3C9 binds to a conserved conformation-dependent epitope in subdomain 3 while non-inhibitory mAb 3D10 binds to a linear epitope in subdomain 1 of DBPII. More definitive epitope mapping of mAb 3D10 was achieved using a random peptide library displayed on phage. Since DBP region II is mostly made up of alpha-helices, we used a randomized helical scaffold library, the Affibody library, displayed on phage, to determine epitope of conformation-dependent antibodies. The immunogenicity of the identified epitopes was evaluated in mice and the immune sera evaluated for binding to DBPII by ELISA and inhibition of DBPII-erythrocyte binding by the COS7 cell assay. Immune serum from the mAb3C9 epitope blocked DBPII-erythrocyte, suggesting this epitope could be a good subunit vaccine target.

Master of Science / Department of Diagnostic Medicine/Pathobiology / Raymond R. R. Rowland / African swine fever is a hemorrhagic disease of domestic pigs caused by African swine fever virus (ASFV), a double-stranded DNA virus and the only member of the family Asfarviridae. The structure of this multilayer virion contains more than 34 proteins including the protein p72 which is the major capsid protein. A single conformational neutralizing epitope has been identified on p72, but information on the other antigenic regions (epitopes) is lacking. The objective of this study was to identify p72 epitopes using polyclonal swine sera and a panel of monoclonal antibodies with the ultimate goal being the development of a blocking ELISA assay for the detection of anti-ASFV antibodies. The segment of the p72 protein from amino acids 1 to 345 was divided into five overlapping fragments which were then commercially synthesized. These fragments were cloned into the pHUE expression vector and transformed into Escherichia coli competent cells. The recombinant proteins were expressed in vitro, purified, and used as antigens in indirect ELISAs and western blots to test monoclonal antibodies and polyclonal swine sera. The monoclonal antibodies were produced against the p72 protein based on the ASFV Georgia/07 strain. The polyclonal sera were obtained from pigs immunized with a defective alphavirus replicon particle, RP-sHA-p72, expressing a recombinant protein composed of the extracellular domain of the ASFV HA protein together with the whole p72 protein. The polyclonal sera reacted to p72 in two distinct regions: between amino acids 1 and 83 and between amino acids 250 and 280. The anti-p72 reactive monoclonal antibodies reacted with p72 in three regions: between amino acids 100 and 171, amino acids 180 and 250, and amino acids 280 and 345. Fine mapping with oligopeptides allowed for the identification of six different linear epitopes. Among the monoclonal antibodies selected for blocking assay development, two have been shown to be promising candidates for further evaluation using sera from ASFV-infected pigs.

No description available.

Le développement des anticorps thérapeutiques s'est rapidement accéléré dans les 10 dernières années et concerne un nombre croissant de pathologies. La connaissance de l'épitope, à savoir la région de la cible à laquelle l'anticorps se fixe, est essentielle pour la compréhension des effets fonctionnels de ce dernier. Nous avons développé une méthode in silico, MAbTope, qui permet une prédiction précise de cet épitope, quand bien même aucune structure 3D de l'anticorps d’intérêt n'est résolue. Cette méthode se base sur une méthode d'amarrage protéine-protéine développée auparavant dans l’équipe BIOS. Le jeu d'apprentissage a été fortement enrichi en complexes anticorps-cibles, de nouvelles fonctions de score spécifiques ont été mises au point, et le plus important, l'objectif de l'apprentissage-machine a été modifié pour optimiser non plus la conformation de !'assemblage, mais la prédiction de l'épitope. Nous montrons que la méthode qui en résulte permet une prédiction précise et robuste de l'épitope, que la structure 3D de l'anticorps soit connue ou non. Nous montrons également comment les prédictions peuvent être facilement exploitées pour la validation expérimentale. Enfin, nous montrons comment la méthode peut être utilisée pour étudier à haut-débit le recouvrement d'épitopes par des anticorps ayant la même cible. / The development of therapeutic antibodies has been rapidly increasing in the last 10 years, with application to an increasing number of pathologies. The knowledge of the epitope, the region of the antigen to which the antibody binds, is crucial for understanding its functional effects. We have developed an in silico method, MAbTope, which allows the accurate prediction of the epitope, regardless of the availability of the 3D structure of the antibody of interest. This method is based on a protein-protein docking method previously developed in the BIOS group. The learning dataset was enlarged in antibody-antigen complexes, new specific scoring functions have been designed, and very importantly, the objective of machine-learning was switched from the conformational perspective towards the epitope determination perspective. We show that the resulting method allows robust and accurate prediction, whether or not the 3D structure of the antibody is available. We also show how the predictions can be easily exploited for experimental validation. Finally, we show how this method can be used for high-throughput epitope binning.

Even though our understanding of mechanisms such as protein folding and molecular recognition is relatively poor, antibodies and alternative affinity proteins with entirely novel functions are today generated in a routine manner. The reason for this success is an engineering approach generally known as directed evolution. Directed evolution has provided researchers with a tool for circumventing our limited knowledge and hence the possibility to create novel molecules that by no means could have been designed today. The approach is based on construction of high-complexity combinatorial libraries from which protein variants with desired properties can be selected. Engineered proteins are already indispensable tools in nearly all areas of life science and the recent advent of mainly monoclonal antibodies as therapeutic agents has directed even more attention to the field of combinatorial protein engineering. In this thesis, I present the underlying research efforts of six original papers. The overall objective of the studies has been to develop and investigate a new staphylococcal surface display method for protein engineering and protein characterization. The technology is based on display of recombinant proteins on surface of the Gram-positive bacteria Staphylococcus carnosus. In two initial studies, two key issues were addressed in order to improve the protein engineering method in regard to affinity discrimination ability and transformation efficiency. The successful results enabled investigation of the staphylococcal display system for de novo generation of affibody molecules from large combinatorial libraries. In this study, a high-complexity protein library was for the first time displayed on surface of Gram-positive bacteria and by means of fluorescence-activated cell sorting, specific affinity proteins for tumor necrosis factor-alpha were isolated. Moreover, in following papers, the staphylococcal display method was further improved and investigated for affinity determination, soluble protein production and epitope mapping purposes in order to facilitate downstream characterizations of generated affinity proteins. Taken together, in these studies we have demonstrated that the staphylococcal display system is a powerful alternative to existing technologies for protein engineering and protein characterization. / QC 20100809