ArticleCommunications chemistry2025
Superwater as a generative AI framework to predict water molecule positions on protein structures.
Article in Communications chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- The Advantages of AI for Computational Protein Studies and Looking Ahead at the Next Challenges: Single Structures Are Not Enough.Journal of molecular biology · 2026Review
- A Risk-Tiered Validation Framework for Artificial Intelligence in Drug Discovery: From Reproducibility to Clinical Translation.International journal of molecular sciences · 2026Review
- WatCon: A Python Tool for Analysis of Conserved Water Networks Across Protein Families.JACS Au · 2025Article
- SuperMetal: a generative AI framework for rapid and precise metal ion location prediction in proteins.Journal of cheminformatics · 2025Article
- Accelerated Hydration Site Localization and Thermodynamic Profiling.Journal of chemical information and modeling · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Water molecules play a significant role in maintaining protein structural stability and facilitating molecular interactions. Accurate prediction of water molecule positions around protein structures is essential for understanding their biological roles and has significant implications for protein engineering and drug discovery. Here, we introduce SuperWater, a novel generative AI framework that integrates a score-based diffusion model with equivariant graph neural networks to predict water molecule placements around proteins with high accuracy. SuperWater surpasses existing methods, delivering state-of-the-art performance in both crystal water coverage and prediction precision, achieving water localization within 0.3 ± 0.06 Å of experimentally validated positions. We demonstrate the capabilities of SuperWater through case studies involving protein hydration, protein-ligand binding, and protein-protein binding sites. This framework can be adapted for various applications, including structural biology, binding site prediction, multi-body docking, and water-mediated drug design.
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Registered trials
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