MDeePred: novel multi-channel protein featurization for deep learning-based binding affinity prediction in drug discovery.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: Identification of interactions between bioactive small molecules and target proteins is crucial for novel drug discovery, drug repurposing and uncovering off-target effects. Due to the tremendous size of the chemical space, experimental bioactivity screening efforts require the aid of computational approaches. Although deep learning models have been successful in predicting bioactive compounds, effective and comprehensive featurization of proteins, to be given as input to deep neural networks, remains a challenge.

Authors

  • A S Rifaioglu
    Department of Computer Engineering, Middle East Technical University, Ankara, Turkey.
  • R Cetin Atalay
    Graduate School of Informatics, Middle East Technical University, Ankara, Turkey.
  • D Cansen Kahraman
    Graduate School of Informatics, Middle East Technical University, Ankara, Turkey.
  • T Doğan
    Department of Computer Engineering, Hacettepe University, Ankara, Turkey.
  • M Martin
    European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, Hinxton, UK.
  • V Atalay
    Department of Computer Engineering, Middle East Technical University, Ankara, Turkey.