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


Rifaioglu A. S. , Atalay R. C. , KAHRAMAN D. C. , DOĞAN T. , Martin M., Atalay V.

BIOINFORMATICS, vol.37, no.5, pp.693-704, 2021 (Journal Indexed in SCI) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 37 Issue: 5
  • Publication Date: 2021
  • Doi Number: 10.1093/bioinformatics/btaa858
  • Title of Journal : BIOINFORMATICS
  • Page Numbers: pp.693-704

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.