Discovering and exploiting hidden pockets at protein interfaces
dc.contributor.advisor
Michel, Julien
en
dc.contributor.advisor
Camp, Philip
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dc.contributor.author
Cuchillo, Rémi Jean-Michel José
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dc.contributor.sponsor
Engineering and Physical Sciences Research Council (EPSRC)
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dc.date.accessioned
2015-09-02T14:09:23Z
dc.date.available
2015-09-02T14:09:23Z
dc.date.issued
2015-06-30
dc.description.abstract
The number of three-dimensional structures of potential protein targets
available in several platforms such as the Protein Data Bank is subjected to a
constant increase over the last decades. This observation should be an additional
motivation to use structure-based methodologies in drug discovery. In the recent
years, different success stories of Structure Based Drug Design approach have
been reported. However, it has also been shown that a lack of druggability is
one of the major causes of failure in the development of a new compound.The
concept of druggability can be used to describe proteins with the capability to
bind drug-like compounds. A general consensus suggests that around 10% of
the human genome codes for molecular targets that can be considered as druggable.
Over the years, the protein druggability was studied with a particular
interest to capture structural descriptors in order to develop computational
methodologies for druggability assessment. Different computational methods
have been published to detect and evaluate potential binding sites at protein
surfaces. The majority of methods currently available are designed to assess
druggability of a static structure. However it is well known that sometimes a few
local rearrangements around the binding site can profoundly influence the affinity
of a small molecule to its target. The use of techniques such as molecular dynamics
(MD) or Metadynamics could be an interesting way to simulate those variations.
The goal of this thesis was to design a new computational approach, called
JEDI, for druggability assessment using a combination of empirical descriptors
that can be collected ‘on-the-fly’ during MD simulations. JEDI is a grid-based
approach able to perform the druggability assessment of a binding site in only a
few seconds making it one of the fastest methodologies in the field. Agreement
between computed and experimental druggability estimates is comparable to
literature alternatives. In addition, the estimator is less sensitive than existing
methodologies to small structural rearrangements and gives consistent druggability
predictions for similar structures of the same protein. Since the JEDI function is
continuous and differentiable, the druggability potential can be used as collective
variable to rapidly detect cryptic druggable binding sites in proteins with a variety
of MD free energy methods.
en
dc.identifier.uri
http://hdl.handle.net/1842/10521
dc.language.iso
en
dc.publisher
The University of Edinburgh
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dc.relation.hasversion
Julien Michel and Rémi Cuchillo. The impact of small molecule binding on the energy landscape of the intrinsically disordered protein C-myc. PloS ONE, 7(7):e41070, July 2012.
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dc.relation.hasversion
Rémi Cuchillo and Julien Michel. Mechanisms of small-molecule binding to intrinsically disordered proteins. Biochemical Society transactions, 40(5):1004– 1008, October 2012.
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dc.subject
druggability
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dc.subject
binding sites
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dc.subject
JEDI
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dc.subject
molecular dynamics
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dc.subject
MD simulations
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dc.title
Discovering and exploiting hidden pockets at protein interfaces
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dc.type
Thesis or Dissertation
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dc.type.qualificationlevel
Doctoral
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dc.type.qualificationname
PhD Doctor of Philosophy
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