Mol-GPT

[Aspirit]

Description:
Mol-BERT is a molecular representation learning model designed to process chemical structures using SMILES notation. The model learns from millions of molecular structures and their properties, making it useful for predicting molecular bioactivity, toxicity, solubility, and other physicochemical properties. It enhances drug discovery pipelines by enabling structure-based virtual screening and lead optimization.

Topic Creator Motivation:
Discuss how Mol-BERT is used for molecular property predictions, virtual screening, and cheminformatics. Engage with others to share methods, datasets, and optimization techniques.

[Author]

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