In silico-aided design, build and test of synthetic proteins
| dc.availability.bitstream | embargoed | |
| dc.check.date | 2021-05-09 | |
| dc.contributor.advisor | Tangney, Mark | en |
| dc.contributor.author | Yallapragada, V. V. B. | |
| dc.date.accessioned | 2020-05-28T10:51:16Z | |
| dc.date.available | 2020-05-28T10:51:16Z | |
| dc.date.issued | 2019-12-20 | |
| dc.date.submitted | 2019-12-20 | |
| dc.description.abstract | Since the discovery of proteins in 1838, the field of protein engineering and our understanding of proteins have improved exponentially. Synthetic proteins have found applications in various biomedical, food and material-based settings. This rise in synthetic proteins was complemented with the parallel expansion in the availability of in silico tools for protein modelling. The complexity in the composition and design of synthetic proteins requires careful in silico validation to screen for potential pitfalls in the design. In silico tools for protein modelling and design have been used extensively to computationally validate the structure and functioning of the synthetic proteins prior to wet-lab testing. In this thesis, the workflow of design-model-build-test of synthetic proteins with novel applications in imaging is described. The in silico-aided design, screening and the in vitro testing of synthetic proteins targeting S. aureus surface antigen Clumping factor A are discussed in Chapter 2. In this chapter, a suitable candidate worthy of examining in a future in vivo setting was identified. During the in silico-aided screening, the complexity of data obtained from various in silico tools posed new challenges. This was termed as ‘the in silico myriad problem’. In Chapter 3, a mathematical strategy (Function2Form bridge) was tested to address the in silico myriad problem, by combining the scores of different design parameters pertaining to the synthetic protein being analysed into a single easily interpreted output describing overall performance. The strategy comprises 1. A mathematical strategy combining data from a myriad of in silico tools into an Overall Performance-score (a singular score informing on a user-defined overall performance); 2. The F2F-Plot, a graphical means of informing the wet-lab biologist holistically on designed construct suitability in the context of multiple parameters, highlighting scope for improvement. F2F bridge was implemented during the design process of all the synthetic proteins in Chapter 4 and Chapter 5. The synthetic protein design strategy used in Chapter 2 was implemented to design synthetic proteins targeting cancer cells, and to assess their potential as in vivo imaging agents in Chapter 4. For both MUC1 and ClfA targeted proteins, in vivo luminescence imaging studies involving systemic intravenous administration of proteins, validated synthetic protein specific accumulation at target cell locations within mice as evidenced by localised luminescence. Dose response studies indicated that luminescence output was both target cell and administered protein quantity related. In Chapter 5, a self-assembling protein ‘cage’ was designed, built and tested in vitro. An accompanying novel fluorescence-based protein-protein interaction reporting strategy was introduced, involving incorporation of cysteine residues at the interaction interface of monomeric proteins of the self-assembling protein cage. In silico tools were used to ensure the conformational and functional stability. FlAsH EDT2 (fluorescin arsenical hairpin binder-ethanedithiol) mediated fluorescence was used to confirm the self-assembly. This demonstrates the level of accuracy and detail that can be incorporated into synthetic protein design using in silico tools. In Chapter 6, the scope of introducing miniaturised optical devices to aid biological experimentation was explored. A novel handheld device for monitoring continuous bacterial growth, with prospects of measuring biofluorescence was developed. The device was tested using different bacterial strains and showed accuracy levels similar to a standard benchtop spectrophotometer. This thesis demonstrates the use of computational methods and various in silico tools for protein design. Modern day biomedical science demands novel concepts with deployable technology to assist their translation into user-based settings. In this thesis, various interdisciplinary concepts have been applied to deliver on a holistic end-goal. | en |
| dc.description.status | Not peer reviewed | en |
| dc.description.version | Accepted Version | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Yallapragada, V. V. B. 2019. In silico-aided design, build and test of synthetic proteins. PhD Thesis, University College Cork. | en |
| dc.identifier.endpage | 278 | en |
| dc.identifier.uri | https://hdl.handle.net/10468/10076 | |
| dc.language.iso | en | en |
| dc.publisher | University College Cork | en |
| dc.rights | © 2019, Venkata Vamsi Bharadwaj Yallapragada. | en |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | en |
| dc.subject | Synthetic biology | en |
| dc.subject | Protein design | en |
| dc.title | In silico-aided design, build and test of synthetic proteins | en |
| dc.type | Doctoral thesis | en |
| dc.type.qualificationlevel | Doctoral | en |
| dc.type.qualificationname | PhD - Doctor of Philosophy | en |
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