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Title: Dynamics of ligand-protein interactions : impact on drug discovery
Author: Kamarainen, Outi Katriina
ISNI:       0000 0004 6493 7353
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2017
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Introducing a new drug to market is a lengthy and expensive process (typically 10-15 years and $1.7 billion). Better understanding of how and why a drug molecule binds to a target and what changes in the atomistic structure and chemistry could improve the binding affinity and shorten the process. In addition to structure-based approaches, the role of thermodynamics and molecular motions in binding selectivity and efficiency have attracted increasing attention. Whilst calorimetric methods can quantify total free energy and entropy change, it is difficult to estimate contributions from the different components of entropy, one of the largest unknowns being the magnitude of the configurational entropy. Molecular dynamics (MD) simulations of the drug and target protein can provide more details of the different atomistic movements contributing to the total entropy change, thus potentially providing valuable clues for lead optimisation. In this study we use the well characterised N-terminal domain of the Hsp90 chaperone protein as a model system to study the changes in conformational flexibility (configurational entropy) upon binding of small molecule inhibitors using MD simulations, NMR and ITC. We show that the two inhibitors studied cause different changes in the protein dynamics. These effects were seen with NMR relaxation dispersion methods and with MD but the dynamic changes however are not reflected in the global ITC parameters. Here the water is assumed to have a dominating effect in the overall entropy change. However, as some Hsp90 clients have been shown to preferentially interact with only one conformation of the protein, we propose that the changes seen with NMR and MD could be of interest for drug design. Manipulating the dynamics by small molecules could favour interaction with a subset of client proteins, without affecting the interaction of others, all together providing specificity and potentially allowing to design an ‘ideal’ drug that only prevents the folding of ‘bad’ cancer related proteins without affecting Hsp90 functions in the normal cells. As the MD simulations also reflect these dynamic changes, we propose that simulations could be also used as a screening tool for selecting which inhibitors could be taken for further development in the lab.
Supervisor: Harris, Sarah ; Zhuravleva, Anastasia Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available