Response to "Caution: Fundamental data quality issues underlying intelligent prediction of enzyme optimal pH".

Fundamental data quality issues were confirmed in enzyme datasets, with discrepancies found in several entries used for machine learning prediction of enzyme optimal pH.

• Why it matters: Accurate biochemical data are crucial for reliable enzyme property predictions, yet current datasets contain errors that can compromise model validity and scientific conclusions.
• What they did: The authors re-examined six protein entries by tracing their annotated pH values to original literature, revealing incorrect experimental values, misassignments, and missing activity data.
• The result: These findings highlight the importance of rigorous literature-based curation to improve dataset reliability, enabling the development of more accurate enzyme pH prediction models.