Spelling suggestions: "subject:"epitope prediction"" "subject:"épitope prediction""
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Systematic characterisation of HLA Class II ligand binding specificity by quantitative matricesSturniolo, Tiziana Concetta January 1998 (has links)
No description available.
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Computational Evaluation and Structure-based Design for Potentiation of Nicotine VaccinesSaylor, Kyle Lucas 08 October 2020 (has links)
Existing therapeutic options for the alleviation of nicotine addiction have been largely ineffective at stemming the tide of tobacco use. Immunopharmacotherapy, or vaccination, is a promising, alternate therapy that is currently being explored. Results from previous studies indicate that nicotine vaccines (NVs) are effective in subjects that achieve high drug-specific antibody titers, though overall efficacy has not been observed. Consequently, improvement of these vaccines is necessary before they can achieve approval for human use. In this report, three separate approaches towards NV potentiation are explored.
The first approach applied physiologically-based pharmacokinetic (PBPK) modeling to better assess NV potential. Rat and human physiological and pharmacological parameters were obtained from literature and used to construct compartmentalized models for nicotine and cotinine distribution. These models were then calibrated and validated using data obtained from literature. The final models verified the therapeutic potential of the NV concept, identified four key parameters associated with vaccine success, and established correlates for success that could be used to evaluate future NVs prior to clinical trials.
In the second approach, conjugate NV scaffoldings were engineered by using wild-type (WT) and chimeric human papilloma (HPV) 16 L1 protein virus-like particles (VLPs). The chimeric protein was created by removing the last 34 C-terminal residues from the WT protein and then incorporating a multi-epitope insert that could universally target major histocompatibility complex (MHC) class II molecules. The proteins were subsequently expressed in E. coli and purified using a multi-step process. Comparisons between the separation outcomes revealed that the insert was able to modulate individual process outcomes and improve overall yield without inhibiting VLP assembly.
In the third approach, commonly used carrier proteins were computationally mined for their MHC class II epitope content using human leukocyte antigen (HLA) population frequency data and MHC epitope prediction software. The most immunogenic epitopes were concatenated with interspacing cathepsin cleavage sequences and the resulting protein was re-evaluated using the earlier methods. This work represents the first ever in silico design of chimeric antigens that could potentially target all of the major HLA DQ and HLA DR allotypes found in humans. / Doctor of Philosophy / Existing treatment options for addressing nicotine addiction have been largely ineffective at preventing tobacco use. Vaccination, on the other hand, is a promising, alternate treatment option that is currently being explored. Previous studies have shown that nicotine vaccines (NVs) are effective in the subjects that respond well to the vaccine. Effectiveness in the majority of vaccine recipients, however, has not been observed. Consequently, improvement of these vaccines is necessary before they can be used in humans. In this report, three separate approaches for improving NV effectiveness are explored.
The first approach applied physiologically-based pharmacokinetic (PBPK) modeling to better assess NV potential. Parameters were obtained from literature and used to construct models that could predict NV effectiveness in rats and humans. These models were then calibrated and validated using data obtained from literature. The final models verified that NVs could work if certain conditions were met, identified four key parameters associated with vaccine success, and allowed for estimation of NV efficacy prior to their evaluation in humans.
In the second approach, protein carriers for conjugate NVs were constructed using the human papilloma (HPV) 16 L1 protein. This protein is known for its ability to form virus-like particles (VLPs). Both a modified and an unmodified (wild-type) protein were constructed. The modified HPV 16 L1 protein was created by replacing the last 34 C-terminal amino acids with a polypeptide insert that could enhance the immunogenicity of the vaccine. The modified and unmodified proteins were then expressed in E. coli and purified. Results indicated that the insert was able to modulate individual process outcomes and improve overall process yield without preventing VLP assembly.
In the third approach, commonly used carrier proteins were computationally mined for their MHC class II epitope content using human gene frequency data and MHC epitope prediction software. The epitopes that were predicted to be the most immunogenic were linked together with interspacing protease recognition sequences and the immunogenicity of the resulting protein was re-evaluated using the prediction software. This work represents the first computational design of antigens that could potentially allow a vaccine to be effective in a large portion of human population regardless of the genetic variability.
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The in silico prediction of foot-and-mouth disease virus (FMDV) epitopes on the South African territories (SAT)1, SAT2 and SAT3 serotypesMukonyora, Michelle 24 January 2017 (has links)
Foot-and-mouth disease (FMD) is a highly contagious and economically
important disease that affects even-toed hoofed mammals. The FMD virus
(FMDV) is the causative agent of FMD, of which there are seven clinically
indistinguishable serotypes. Three serotypes, namely, South African
Territories (SAT)1, SAT2 and SAT3 are endemic to southern Africa and are
the most antigenically diverse among the FMDV serotypes. A negative
consequence of this antigenic variation is that infection or vaccination with
one virus may not provide immune protection from other strains or it may only
confer partial protection. The identification of B-cell epitopes is therefore key
to rationally designing cross-reactive vaccines that recognize the
immunologically distinct serotypes present within the population.
Computational epitope prediction methods that exploit the inherent physicochemical properties of epitopes in their algorithms have been
proposed as a cost and time-effective alternative to the classical experimental
methods. The aim of this project is to employ in silico epitope prediction
programmes to predict B-cell epitopes on the capsids of the SAT serotypes.
Sequence data for 18 immunologically distinct SAT1, SAT2 and SAT3 strains from across southern Africa were collated. Since, only one SAT1 virus has
had its structure elucidated by X-ray crystallography (PDB ID: 2WZR),
homology models of the 18 virus capsids were built computationally using
Modeller v9.12. They were then subjected to energy minimizations using the
AMBER force field. The quality of the models was evaluated and validated
stereochemically and energetically using the PROMOTIF and ANOLEA
servers respectively. The homology models were subsequently used as input
to two different epitope prediction servers, namely Discotope1.0 and Ellipro.
Only those epitopes predicted by both programmes were defined as epitopes.
Both previously characterised and novel epitopes were predicted on the SAT
strains. Some of the novel epitopes are located on the same loops as
experimentally derived epitopes, while others are located on a putative novel antigenic site, which is located close to the five-fold axis of symmetry. A
consensus set of 11 epitopes that are common on at least 15 out of 18 SAT
strains was collated. In future work, the epitopes predicted in this study will be
experimentally validated using mutagenesis studies. Those found to be true
epitopes may be used in the rational design of broadly reactive SAT vaccines / Life and Consumer Sciences / M. Sc. (Life Sciences)
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