PETrans: De Novo Drug Design with Protein-Specific Encoding Based on Transfer Learning.

ABSTRACT: Recent years have seen tremendous success in the design of novel drug molecules through deep generative models. Nevertheless, existing methods only generate drug-like molecules, which require additional structural optimization to be developed into actual drugs. In this study, a deep learning method for generating target-specific ligands was proposed. This method is useful when the dataset for target-specific ligands is limited. Deep learning methods can extract and learn features (representations) in a data-driven way with little or no human participation. Generative pretraining (GPT) was used to extract the contextual features of the molecule. Three different protein-encoding methods were used to extract the physicochemical properties and amino acid information of the target protein. Prot

SUBMITTER: Wang X 

PROVIDER: S-EPMC9865828 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature