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 ...
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Authors
Contributors
+ Deane, C
- Institution:
- University of Oxford
- Division:
- MPLS
- Department:
- Statistics
- Role:
- Supervisor
- ORCID:
- 0000-0003-1388-2252
+ Von Delft, F
- Institution:
- University of Oxford
- Role:
- Supervisor
- ORCID:
- 0000-0003-0378-0017
+ Morris, G
- Institution:
- University of Oxford
- Division:
- MPLS
- Department:
- Statistics
- Role:
- Examiner
- ORCID:
- 0000-0003-1731-8405
+ Colwell, L
- Role:
- Examiner
+ Biotechnology and Biological Sciences Research Council
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
- Language:
-
English
- Keywords:
- Subjects:
- Deposit date:
-
2023-07-11
Terms of use
- Copyright holder:
- Scantlebury, J
- Copyright date:
- 2023
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