Skip to content

Code for Binding Affinity Prediction with Graph Neural Networks

Notifications You must be signed in to change notification settings

Eereenah/gnn-thesis

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 
 
 

Repository files navigation

Binding Affinity Prediction with Graph Neural Networks

  • The repository contains the notebooks for the final chapter of my Master's Thesis.

  • The notebooks contain the implementation of a novel fusion-based architecture, which combines a graph neural network (AttentiveFP) and biologically-motivated learned protein embeddings (ProtTransBert) for drug-target interaction prediction. The model architecture is outlined below: proteinafp

The model is benchmarked on Davis and KIBA standard datasets, as well as on an in-house dataset of ~400K de novo generated molecules against 6 targets.

Releases

No releases published

Packages

No packages published