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A computational framework for parallelised protein folding simulation and the investigation of protein stability
Thesis (MSc)--Stellenbosch University, 2025.
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Stellenbosch : Stellenbosch University
2025
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| _version_ | 1867613811263930368 |
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| access_status_str | Open Access |
| author | Koh, Tammara Poa Siang |
| author2 | Tromp, Gerard |
| author_browse | Koh, Tammara Poa Siang Tromp, Gerard |
| author_facet | Tromp, Gerard Koh, Tammara Poa Siang |
| author_sort | Koh, Tammara Poa Siang |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MSc)--Stellenbosch University, 2025. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/132586 |
| institution | Stellenbosch University (South Africa) |
| last_indexed | 2026-06-10T12:42:04.592Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/132586 A computational framework for parallelised protein folding simulation and the investigation of protein stability Koh, Tammara Poa Siang Tromp, Gerard Patterton, Hugh George Stellenbosch University. Faculty of Science. Centre for Bioinformatics & Computational Biology. Proteins -- Structure -- Computer simulation Computational biology Protein folding -- Computer simulation Molecular dynamics -- Computer simulation UCTD Thesis (MSc)--Stellenbosch University, 2025. Koh, T. P. S. 2025. A computational framework for parallelised protein folding simulation and the investigation of protein stability. Unpublished masters thesis. Stellenbosch: Stellenbosch University [online]. Available: https://scholar.sun.ac.za/items/33e8bff1-6565-43b8-840e-155dd0669e75 ENGLISH ABSTRACT: Prions are proteinaceous infectious particles that propagate and assemble to cause transmissible spongiform encephalopathies. Their ability to convert native proteins to their infectious isoforms without the involvement of nucleic acid but rather through a templated seeding process, that requires only an altered form of the host-encoded prion protein, has highlighted the significance of identifying and assessing the effect of mutations on the native state. To that effect, we have developed a computational framework that assesses the effect of a given mutation to the native state. A variety of tools were assessed for usage within the framework based on the purpose of the tool, its intended use, and limitations. Tools were selected for implementing mutations, assessing mutant structures and free energy value prediction. Rosetta’s fixed backbone application, Rosetta’s SimpleThreading mover and pmx were selected for the implementation of a mutation, GROMACS for simulating the mutants and Maestro for predicting free energy values of a mutant. These tools allow for the implementation of the mutation, making use of three methods, alchemical/non-physical perturbation, protein design and threading. The computational framework allows for both free energy simulations and standard molecular dynamics simulations to assess the effect of a mutant on the native structure. The M205A mutation of the human prion protein was executed using this framework and was found to have a destabilising effect, resulting in a ΔΔG value of 6.494 ± 0.37 kcal/mol for the free energy simulation, a Maestro prediction of 2.96 kcal/mol, and Rosetta scores of 790.66 and 749.75 Rosetta energy units for the fixed backbone and threader, respectively. These results correlate with the experimental result of 3.09 ± 0.28 kcal/mol implying that there is a destabilising effect from the M205A mutation. The framework, however, is not ideal for mass simulations involving multiple proteins and multiple mutants, either for the same or differing structures. This is due the differences in properties such as the hydrophobicity, secondary structure and size, among others, of differing proteins that may require different parameters. Given the nature of molecular dynamics simulations, which are resource intensive, parallelisation would be beneficial in reducing the time taken for simulations. However, due to resources and time, the GROMACS container could not be built for GPU usage. While the computational framework can assess a mutant on a single protein per execution, there are several aspects of the framework that can be improved on. Future work could focus on the inclusion of GPU usage with GROMACS, further automation of the computational framework to reduce the risk of human error, and the use of machine learning to possibly predict molecular dynamics parameters for input structures and mutations. Masters 2025-06-11T10:15:13Z 2025-06-11T10:15:13Z 2025-03 Thesis https://scholar.sun.ac.za/handle/10019.1/132586 Stellenbosch University x, 95 pages : illustrations application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Proteins -- Structure -- Computer simulation Computational biology Protein folding -- Computer simulation Molecular dynamics -- Computer simulation UCTD Koh, Tammara Poa Siang A computational framework for parallelised protein folding simulation and the investigation of protein stability |
| title | A computational framework for parallelised protein folding simulation and the investigation of protein stability |
| title_full | A computational framework for parallelised protein folding simulation and the investigation of protein stability |
| title_fullStr | A computational framework for parallelised protein folding simulation and the investigation of protein stability |
| title_full_unstemmed | A computational framework for parallelised protein folding simulation and the investigation of protein stability |
| title_short | A computational framework for parallelised protein folding simulation and the investigation of protein stability |
| title_sort | computational framework for parallelised protein folding simulation and the investigation of protein stability |
| topic | Proteins -- Structure -- Computer simulation Computational biology Protein folding -- Computer simulation Molecular dynamics -- Computer simulation UCTD |
| url | https://scholar.sun.ac.za/handle/10019.1/132586 |
| work_keys_str_mv | AT kohtammarapoasiang acomputationalframeworkforparallelisedproteinfoldingsimulationandtheinvestigationofproteinstability AT kohtammarapoasiang computationalframeworkforparallelisedproteinfoldingsimulationandtheinvestigationofproteinstability |