Evidence map›Paper›PMID 41450622›Full record

ArticleJACS Au2025

WatCon: A Python Tool for Analysis of Conserved Water Networks Across Protein Families.

Alfie-Louise R Brownless, Travis Harrison-Rawn, Shina C L Kamerlin

Abstract read
In one paragraph

Article in JACS Au, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Alfie-Louise R BrownlessSchool of Chemistry and Biochemistry, Georgia Institute of Technology, 901 Atlantic Drive NW, Atlanta, Georgia 30332-0400, United States.
Travis Harrison-RawnSchool of Chemistry and Biochemistry, Georgia Institute of Technology, 901 Atlantic Drive NW, Atlanta, Georgia 30332-0400, United States.
Shina C L KamerlinSchool of Chemistry and Biochemistry, Georgia Institute of Technology, 901 Atlantic Drive NW, Atlanta, Georgia 30332-0400, United States.ORCID https://orcid.org/0000-0002-3190-1173

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Water structure is crucially important to protein function and catalysis and can be conserved throughout related proteins despite differences in sequence. The complex hydrogen-bonding networks formed by water molecules and protein residues have been studied extensively, and graph-theory-based methods have frequently been used to describe these networks. Although there exist a number of tools which can be used to track water positions and networks, corresponding methods for easily analyzing complex water network structure across related proteins are limited. To address this challenge, we present here a new tool, WatCon, an open-source Python package which can be used to analyze water positions and water network structure across protein families using both dynamic and static structural information. Importantly, WatCon can be used to classify conservation of water networks, characterize water networks across structures, and project subsequent results for easy visual interpretation. To illustrate WatCon usage, we provide five example applications illustrating WatCon analyses of static structures, dynamic trajectories, and cross-family analysis. This in turn showcases the utility of WatCon for enhancing our understanding of biochemical systems, predicting water hotspots of potential relevance to protein engineering and predicting pathogenic mutations. WatCon can be downloaded at https://github.com/kamerlinlab/WatCon and is available under the GNU General Public License v3.0.

Indexed as

Graph TheoryProtein StructureProtein Tyrosine PhosphatasesWater ConservationWater Networks

Identifiers

PMID41450622
PMCPMC12728608

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LicenceCC BY
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Registered trials

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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.