Author: Bo Ram Beck; Bonggun Shin; Yoonjung Choi; Sungsoo Park; Keunsoo Kang
Title: Predicting commercially available antiviral drugs that may act on the novel coronavirus (2019-nCoV), Wuhan, China through a drug-target interaction deep learning model Document date: 2020_2_2
ID: cszqykpu_8
Snippet: Molecule transformer-drug target interaction (MT-DTI) was used to predict binding affinity values between commercially available antiviral drugs and target proteins. Briefly, the natural language processing (NLP) based Bidirectional Encoder Representations from Transformers (BERT) framework is a core algorithm of the model with good performance and robust results in diverse drug-target interaction datasets through pretraining with 'chemical langu.....
Document: Molecule transformer-drug target interaction (MT-DTI) was used to predict binding affinity values between commercially available antiviral drugs and target proteins. Briefly, the natural language processing (NLP) based Bidirectional Encoder Representations from Transformers (BERT) framework is a core algorithm of the model with good performance and robust results in diverse drug-target interaction datasets through pretraining with 'chemical language' SMILES of approximately 1,000,000,000 compounds.
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