Use this URL to cite or link to this record in EThOS:
Title: Application of simulation methods for the identification of allosteric binding site in human glucokinase
Author: Vahdati, Nadia
ISNI:       0000 0004 2695 4283
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2010
Availability of Full Text:
Access from EThOS:
Access from Institution:
Allosteric binding site, in generic terms, refers to a binding site distinct from the active site, where binding of an effector can enhance or decrease enzyme‟s activity. From a drug design point of view targeting allosteric binding sites can offer advantages in terms of selectivity, saturability, and the opportunity for discovering new chemotypes. Current known allosteric drugs have often been identified by chance with high-throughput screening. Although experimental methods can be successful in identifying such binding sites, owing to the cost and time associated with experiments, it would be useful to be able to aid the prediction of the location of such alternative binding sites with computational methods. In this thesis two computational approaches, molecular dynamics (MD) and normal mode analysis (NMA) have been applied to an allosteric enzyme human glucokinase (GLK) for which known allosteric activators have been discovered, as a test-case. First an X-ray structure, bound to glucose and an allosteric activator, has been examined as a benchmark. The apo form of the enzyme has also been studied for further understanding of the dynamics of this enzyme in an unbound form. We then turned our attention to an X-ray structure, bound only to glucose, where the allosteric binding site is not visible. This allowed for a real scenario where the allosteric binding site is not observed in the static structure in the absence of a suitable activator and for which we aimed to reveal the binding site. In this system we have successfully revealed the allosteric binding site and would have been able to predict the location with reasonable confidence.
Supervisor: Essex, Jonathan Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: QD Chemistry