dc.contributor.advisor | Vishveshwara, Saraswathi | |
dc.contributor.advisor | Chandra, Nagasuma | |
dc.contributor.author | Dighe, Anasuya | |
dc.date.accessioned | 2019-06-06T09:57:15Z | |
dc.date.available | 2019-06-06T09:57:15Z | |
dc.date.submitted | 2017 | |
dc.identifier.uri | https://etd.iisc.ac.in/handle/2005/4236 | |
dc.description.abstract | Molecular recognition between proteins and their associated ligands constitutes ligand-induced protein rewiring thereby enabling the formation of a stable protein-ligand complex. The studies presented in this thesis address the conformational plasticity inherent to proteins by virtue of which they adapt to diverse ligands and orchestrate complex biological processes like signal transduction, transcription and protein-protein interaction. Adopting network theory based formalisms for understanding protein-ligand associations involve deconstructing the three-dimensional structure of a protein in terms of nodes and edges. With this view, Protein Structure Networks (PSNs) of ligand-bound complexes are studied by considering their side-chain non-covalent interactions. Agonist and antagonist-bound G-Protein Coupled Receptors (GPCRs) are investigated to gain mechanistic insights into allostery and its role in signal transduction. The degree of similarity between PSNs of these complexes is quantified by means of Network Similarity Score (NSS). The physical nature of these networks is inspected by subjecting them to perturbations and major players in maintaining the stability of such networks are identified. Residue-wise groupings (at backbone and side-chain level) are obtained by applying graph spectral methods.
All-atom Molecular Dynamics (MD) simulations are carried out to gain a better understanding of protein-ligand binding by analysing conformational ensembles of these complexes. In this scenario, two members from a highly versatile ligand-inducible transcription factor superfamily, i.e., Nuclear Receptors (NR) are studied, that are known to exhibit extremes of ligand binding behavior ranging from promiscuity to specificity.
Diverse ligands are known to bind to proteins and the overall nature of their binding site is investigated. In particular, similarities among binding sites of diverse proteins are analysed by using PocketMatch. Percolation of these similarities to regions surrounding the binding site is reported and examples depicting this extended similarity are discussed.
Overall, studies presented in this thesis provide a structural perspective into the adaptability of proteins for recognizing diverse ligands and undergoing local or global re-organizations in their framework to regulate complex biological processes. | en_US |
dc.language.iso | en_US | en_US |
dc.relation.ispartofseries | G28681; | |
dc.rights | I grant Indian Institute of Science the right to archive and to make available my thesis or dissertation in whole or in part in all forms of media, now hereafter known. I retain all proprietary rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part
of this thesis or dissertation | en_US |
dc.subject | Protein-ligand Interactions | en_US |
dc.subject | Protein Ligand Interactions | en_US |
dc.subject | Protein Structure Networks (PSNs) | en_US |
dc.subject | Graph Theory | en_US |
dc.subject | Protein Side-chain Networks (PScN) | en_US |
dc.subject | Muscarinic Acetylcholine Receptors | en_US |
dc.subject | Muscarinic Receptor Cmplexes | en_US |
dc.subject | Protein-Protein Interactions | en_US |
dc.subject | Pregnane X Receptor | en_US |
dc.subject | G-Protein Coupled Receptors (GPCRs) | en_US |
dc.subject | Network Similarity Score (NSS) | en_US |
dc.subject.classification | Biochemistry | en_US |
dc.title | Studies on Dynamic Plasticity of Ligand Binding Sites in Proteins | en_US |
dc.type | Thesis | en_US |
dc.degree.name | PhD | en_US |
dc.degree.level | Doctoral | en_US |
dc.degree.grantor | Indian Institute of Science | en_US |
dc.degree.discipline | Faculty of Science | en_US |