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Multi-modal co-attention for drug-target interaction annotation and Its Application to SARS-CoV-2

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CoaDTI

Multi-modal co-attention for drug-target interaction annotation and Its Application to SARS-CoV-2

Abstract

Environment

The test was conducted in the linux server with GTX2080Ti and the running environment is as follows:

  • python 3.7
  • pytorch 1.7.1
  • rdkit
  • pytorch geometric 1.6.3
  • Cuda 10.0.130

Data

  1. Human and c.elegans dataset are available at \url{https://github.com/masashitsubaki/CPI_prediction/tree/master/dataset}.
  2. Binding_DB dataset is available at \url{https://github.com/IBM/InterpretableDTIP}.
  3. The data of SARS-CoV-2 Main protease (Mpro) in complex with GC373 is available at \url{https://www.rcsb.org/structure/6WTK}. The data of SARS-CoV-2 Main protease (Mpro) in complex with ML188 is avalable at \url{https://www.rcsb.org/structure/7L0D}.

How to run

CoaDTI

  1. Run ./code/data_prepare.py to preprocess the dataset.
  2. Run ./code/train.py to train the CoaDTI.

CoaDTI-pro

  1. Run ./code/data_prepare.py to preprocess the dataset.
  2. Run ./code/train.py to train the CoaDTI-pro.

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Multi-modal co-attention for drug-target interaction annotation and Its Application to SARS-CoV-2

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