Thesis icon

Thesis

Deep neural networks for pose validation, affinity prediction, and input attribution

Abstract:

The search for drug molecules which bind strongly to specific proteins is an integral part of the drug discovery process. To this end, virtual screening algorithms which aim to screen a large number of potential binders in silico have been developed. These use scoring functions to assess the probability that a computationally predicted binding pose is correct, and to predict the binding affinity. More recently, research has turned to deep learning-based scoring functions which use binding ...

Expand abstract

Actions

Access Document

Files:

Authors

More by this author
Division:
MPLS
Department:
Statistics
Role:
Author

Contributors

Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Supervisor
ORCID:
0000-0003-1388-2252
Institution:
University of Oxford
Role:
Supervisor
ORCID:
0000-0003-0378-0017
Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Examiner
ORCID:
0000-0003-1731-8405
Role:
Examiner


More from this funder
Funder identifier:
http://dx.doi.org/10.13039/501100000268
Grant:
BB/S507611/1
Programme:
Interdisciplinary Biosciences DTP


DOI:
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford

Terms of use


Views and Downloads

Views and downloads will return soon






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP