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Fig. 1 | Journal of Cheminformatics

Fig. 1

From: Multi-PLI: interpretable multi‐task deep learning model for unifying protein–ligand interaction datasets

Fig. 1

Schematic overview of our method. The proposed model consists of two parts: protein/ligand feature extraction from sequence/SMILES and interaction prediction by shared and task-specific layers. The tasks are defined as: binary classification (protein-ligand binding or not) and regression (protein-ligand binding affinity). The main datasets consist of two regression sets and four classification sets, in which PDBbind and DUD-E have structural data. Four independent sets are used to test the generalizability of the model

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