Proteins play an important role in the function of biological systems. Developing a thorough understanding of the dynamics, structure and function is a goal of many biological spectroscopists. One commonly used tool for probing different features and properties of proteins and polypeptides is infrared (IR) spectroscopy. The spectra obtained however lacks resolution due to broad, featureless peaks that are hard to interpret. Overlapping of the bands is also an issue, especially from the amide I region; an important region that is sensitive to secondary structure elements of proteins. Isotope labelling of residues of interest is a solution to disentangle the band profiles, however the technique lacks any meaningful insight regarding coupling between different local sites. For the past few decades, 2D IR (an analogue of its NMR counterpart) has been used in various experiments to improve the quality of 1D IR by spreading the signal to a second frequency domain, thus revealing coupling interactions. The technique has helped reveal different relationships between the secondary structural elements of proteins or between protein-ligand complexes. The main challenge so far has been the computational requirement needed to compute the 2D IR signals of large proteins. This is due to the nonlinear response function scaling with the fourth power of the number of residues involved in the calculations. Moreover, convolution of the bands is still an issue as the number of residues grows, albeit not so much compared with 1D IR. In this thesis, we utilize the exciton approach and molecular dynamics (MD) simulations to compute the 1D and 2D IR signals of small peptides, globular proteins and [Leu]-Enkephalin in the presence of three opioid receptors of interest. The work presented in this thesis complements previous experiments on globular proteins and the behaviour of [Leu]-enkephalin and aims to provide more insight into the behaviour of such systems under the conditions outlined.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:706399 |
| Date | January 2017 |
| Creators | Husseini, Fouad |
| Publisher | University of Nottingham |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://eprints.nottingham.ac.uk/39902/ |
Page generated in 0.0061 seconds