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higppim's Introduction

HiGPPIM - A Hierarchical Graph Neural Network Framework for Predicting Protein-Protein Interaction Modulators with Functional Group Information and Hypergraph Structure

1. overview

image

2. Prerequisites

  • python 3.9.0
  • pytorch 1.12.0
  • networkx 3.1
  • numpy 1.23.5
  • pandas 2.0.0
  • rdkit 2022.9.5
  • torch-cluster 1.6.0+pt112cu113
  • torch-geometric 2.3.0
  • torch-scatter 2.1.0+pt112cu113
  • torch-sparse 0.6.16+pt112cu113

3. Datasets

For PPIM identification tasks, PPI families include Bcl2-Like/Bak-Bax, Bromo Domain/Histone, CD4/gp120, LEDGF/IN, LFA/ICAM, Mdm2-Like/P53, Ras_SOS1, and XIAP/Smac.

For PPIM potency prediction tasks, PPI families include Bcl2-Like/Bak-Bax, Bromo Domain/Histone, CD4/gp120, LEDGF/IN, LFA/ICAM, Mdm2-Like/P53, and XIAP/Smac.

4. Usage

python main.py --dataset bcl2_bak --task classification --batch_size 32 --lr 0.0001 --gpu 0

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