MEHC-Curation: Un marco de Python para la curación de conjuntos de datos moleculares de alta calidad

High-quality molecular data sets are vital for reliable Quantitative Structure-Activity Relationship (QSAR) modeling and drug discovery. However, many molecular databases contain inaccuracies, such as invalid structures and duplicates, that compromise model performance and reproducibility. Current curation tools require substantial domain expertise and involve complex procedures, creating barriers for newcomers and nonexpert users. To address this, we developed MEHC-curation, a user-friendly Python framework that simplifies molecular data set curation for all researchers. This tool allows users to easily curate SMILES strings, transforming an intricate process into a straightforward operation. Built on established protocols, it employs a three-stage pipeline (Validation, Cleaning, and Normalization) with integrated duplicate removal and error tracking. MEHC-curation is accessible to all researchers and can be easily integrated into drug discovery and QSAR workflows, delivering high-quality results without requiring specialized expertise.