ArticleJournal of chemical information and modeling2022
Conserved Water Networks Identification for Drug Design Using Density Clustering Approaches on Positional and Orientational Data.
Article in Journal of chemical information and modeling, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 14 citations in OpenAlex.
- Cooperative stabilization mechanism and electrostatic evolution in the zero dimensional arsenolite cluster aggregates: a first principles investigation.RSC advances · 2026Article
- A Multi-Step Computational Workflow for Screening and Prioritizing SHP2-Binding Molecules.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Thermodynamic Data Remain a Hot Tip for Decoding Binding Affinity and Water Impact on Protein-Ligand Complex Formation to Assist Lead Optimization.Journal of medicinal chemistry · 2026Review
- WatCon: A Python Tool for Analysis of Conserved Water Networks Across Protein Families.JACS Au · 2025Article
- Cheminformatic analysis of protein surfaces provides binding site insights and informs identification strategies.Future medicinal chemistry · 2025Article
- Effect of a Low Electrostatic Environment on the Helical Structures of Peptides and Proteins Using Flexible Water Models: An In Silico Study.ACS omega · 2025Article
- Structural basis of frizzled 7 activation and allosteric regulation.Nature communications · 2024Article
- An integrative structural study of the human full-length RAD52 at 2.2 Å resolution.Communications biology · 2024Article
- WatFinder: a ProDy tool for protein-water interactions.Bioinformatics (Oxford, England) · 2024Article
- Identifying Metal Binding Sites in Proteins Using Homologous Structures, the MADE Approach.Journal of chemical information and modeling · 2023Article
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Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This work describes the development and testing of a method for the identification and classification of conserved water molecules and their networks from molecular dynamics (MD) simulations. The conserved waters in the active sites of proteins influence protein-ligand binding. Recently, several groups have argued that a water network formed from conserved waters can be used to interpret the thermodynamic signature of the binding site. We implemented a novel methodology in which we apply the complex approach to categorize water molecules extracted from the MD simulation trajectories using clustering approaches. The main advantage of our methodology as compared to current state of the art approaches is the inclusion of the information on the orientation of hydrogen atoms to further inform the clustering algorithm and to classify the conserved waters into different subtypes depending on how strongly certain orientations are preferred. This information is vital for assessing the stability of water networks. The newly developed approach is described in detail as well as validated against known results from the scientific literature including comparisons with the experimental data on thermolysin, thrombin, and
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Registered trials
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.