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Seq2Mol: Automatic design of de novo molecules conditioned by the target protein sequences through deep neural networks
The model generated compounds which are structurally different form the training set, while also being more similar to compounds known to bind to the two families of drug targets compared to a random set of molecules.
On-the-fly Prediction of Protein Hydration Densities and Free Energies using Deep Learning
These molecular interaction fields are mapped to the corresponding 3D image of hydration occupancy using a neural network based on an U-Net architecture.
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