ArticleJournal of chemical information and modeling2024
HydraProt: A New Deep Learning Tool for Fast and Accurate Prediction of Water Molecule Positions for Protein Structures.
Article in Journal of chemical information and modeling, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 23 citations in OpenAlex.
- 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
- Predicting water at the protein interface in cryo-EM structures from MD-excess chemical potential.Biophysical journal · 2026Article
- Recombinant Antifreeze Protein Type I as a Potential Peptide-Based Anti-Fouling Material for Biomedical Surfaces.Macromolecular bioscience · 2026Article
- Intrinsically Disordered Polypeptides-Based Stealth Materials Enable Enhanced Photothermal Cancer Therapy Using an In Situ Fiber-Based Penetrating Laser System.Small science · 2026Article
- Direct evidence of acid-driven protein desolvation.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- WatCon: A Python Tool for Analysis of Conserved Water Networks Across Protein Families.JACS Au · 2025Article
- Superwater as a generative AI framework to predict water molecule positions on protein structures.Communications chemistry · 2025Article
- Synthesis and Computational Evaluation ofACS omega · 2025Article
- SuperMetal: a generative AI framework for rapid and precise metal ion location prediction in proteins.Journal of cheminformatics · 2025Article
- De Novo Hydration of Cryo-EM Reconstructions through Molecular Dynamics Simulations of the Excess Chemical Potential.bioRxiv : the preprint server for biology · 2025Article
- Cardaria draba subspecies Shalepensis exerts in vitro and in silico inhibition of α-glucosidase, TRP1, and DLD-1 proliferation.Scientific reports · 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
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Water molecules are integral to the structural stability of proteins and vital for facilitating molecular interactions. However, accurately predicting their precise position around protein structures remains a significant challenge, making it a vibrant research area. In this paper, we introduce HydraProt (deep Hydration of Proteins), a novel methodology for predicting precise positions of water molecule oxygen atoms around protein structures, leveraging two interconnected deep learning architectures: a 3D U-net and a Multi-Layer Perceptron (MLP). Our approach starts by introducing a coarse voxel-based representation of the protein, which allows for rapid sampling of candidate water positions via the 3D U-net. These water positions are then assessed by embedding the water-protein relationship in the Euclidean space by means of an MLP. Finally, a postprocessing step is applied to further refine the MLP predictions. HydraProt surpasses existing state-of-the-art approaches in terms of precision and recall and has been validated on large data sets of protein structures. Notably, our method offers rapid inference runtime and should constitute the method of choice for protein structure studies and drug discovery applications. Our pretrained models, data, and the source code required to reproduce these results are accessible at https://github.com/azamanos/HydraProt.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.