Computational Evaluation and Structure-based Design for Potentiation of Nicotine Vaccines
| dc.contributor.author | Saylor, Kyle Lucas | en |
| dc.contributor.committeechair | Zhang, Chenming | en |
| dc.contributor.committeemember | Luo, Xin | en |
| dc.contributor.committeemember | Senger, Ryan S. | en |
| dc.contributor.committeemember | Meng, Xiang-Jin | en |
| dc.contributor.department | Biological Systems Engineering | en |
| dc.date.accessioned | 2020-10-09T08:00:26Z | en |
| dc.date.available | 2020-10-09T08:00:26Z | en |
| dc.date.issued | 2020-10-08 | en |
| dc.description.abstract | 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. | en |
| dc.description.abstractgeneral | 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. | en |
| dc.description.degree | Doctor of Philosophy | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:27563 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/100314 | en |
| dc.language.iso | en | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | nicotine vaccine | en |
| dc.subject | virus-like particle | en |
| dc.subject | physiologically-based pharmacokinetic model | en |
| dc.subject | epitope prediction | en |
| dc.subject | structural vaccinology | en |
| dc.title | Computational Evaluation and Structure-based Design for Potentiation of Nicotine Vaccines | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Biological Systems Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Doctor of Philosophy | en |
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