Drug Smile String

SMILES strings are simplified representations of molecular structures used extensively in cheminformatics. Current research focuses on leveraging these strings for various tasks, including drug classification using natural language processing techniques and de novo molecule generation via recurrent and convolutional neural networks. These advancements improve drug discovery by enabling more efficient prediction of drug-target binding affinity and reaction outcomes, ultimately accelerating the development of new therapeutics. The development of novel SMILES-based representations, such as root-aligned SMILES, further enhances the accuracy and efficiency of these predictive models.