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

Rifaioglu, A. S.; Atalay, R. Cetin; Kahraman, D. Cansen; Dogan, T.; Martin, M.; Atalay, V


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        "affiliation": "Middle East Tech Univ, Grad Sch Informat, Ankara, Turkey", 
        "name": "Kahraman, D. Cansen"
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      {
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        "affiliation": "European Bioinformat Inst EMBL EBI, European Mol Biol Lab, Cambridge, Hinxton, England", 
        "name": "Martin, M."
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      {
        "affiliation": "Middle East Tech Univ, Dept Comp Engn, Ankara, Turkey", 
        "name": "Atalay, V"
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    "description": "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.", 
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    "title": "MDeePred: novel multi-channel protein featurization for deep learning-based binding affinity prediction in drug discovery"
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