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

Thesis

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: Scantlebury, J

• DOI: 10.5287/ora-dezqjxbmg
• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: biology; graph; data augmentation; chemistry; molecule; molecular; deep learning; neural networks; gnn equivariant
• Subjects: Molecular biology; Neural networks (Computer science)