Evidence map›Paper›PMID 41606988›Full record

ArticleBiophysical journal2026

Predicting water at the protein interface in cryo-EM structures from MD-excess chemical potential.

Qinfang Sun, Sriram Aiyer, Avik Biswas, Allan Haldane, Sompriya Chatterjee, Nobuyuki Matubayasi, Dmitry Lyumkis, Ronald M Levy

Abstract read
In one paragraph

Article in Biophysical journal, 2026. 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

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

8 authors.

Qinfang SunCenter for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania; Department of Chemistry, Temple University, Philadelphia, Pennsylvania.
Sriram AiyerThe Salk Institute for Biological Studies, La Jolla, California.
Avik BiswasThe Salk Institute for Biological Studies, La Jolla, California; Department of Physics, University of California, San Diego, La Jolla, California.
Allan HaldaneCenter for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania; Department of Physics, Temple University, Philadelphia, Pennsylvania.
Sompriya ChatterjeeCenter for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania; Department of Chemistry, Temple University, Philadelphia, Pennsylvania; Material Science Institute, University of Oregon, Eugene, Oregon.
Nobuyuki MatubayasiDivision of Chemical Engineering, Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, Japan.
Dmitry LyumkisThe Salk Institute for Biological Studies, La Jolla, California; Graduate School of Biological Sciences, Department of Molecular Biology, University of California, San Diego, La Jolla, California. Electronic address: dlyumkis@salk.edu.
Ronald M LevyCenter for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania; Department of Chemistry, Temple University, Philadelphia, Pennsylvania; Department of Physics, Temple University, Philadelphia, Pennsylvania. Electronic address: ronlevy@temple.edu.

Funding

Structural Biology CoreU54AI170855 · NIAID · SEATTLE CHILDREN'S HOSPITAL · PI Bruce Edward Torbett · 2022 to 2026
$36.7M
Structural basis for activity of and resistance to HIV integrase inhibitorsU01AI136680 · NIAID · SALK INSTITUTE FOR BIOLOGICAL STUDIES · PI LYUMKIS, DMITRY · 2022 to 2025
$3.4M
Mechanisms of HIV fitness and drug resistance inferred from high-resolution molecular dynamics and sequence co-variation modelsR01AI178849 · NIAID · TEMPLE UNIV OF THE COMMONWEALTH · PI Ronald Levy · 2023 to 2026
$2.7M
Novel mechanism of integrase (IN) resistance to Dolutegravir through epistatic interactions between IN and the nucleocapsid and polypurine tract regions of HIV-1R01AI146017 · NIAID · EMORY UNIVERSITY · PI HACHIYA, ATSUKO, LYUMKIS, DMITRY · 2019 to 2023
$2.6M
NIAID NIH HHS R01 AI146017NIAID NIH HHS R01 AI178849NIAID NIH HHS U01 AI136680NIAID NIH HHS U54 AI170855
6 · The paper itself

Abstract

Predicting the positions of water molecules at the protein interface remains a formidable challenge in structural biology, fueling active research in this field. Here, we present a novel approach based on molecular dynamics (MD) simulations that utilize statistical thermodynamic signatures of water at protein interfaces that can be used to improve the accuracy of water placement in maps derived by cryogenic electron microscopy (cryo-EM). We employ an analysis based on the excess chemical potential, or the work to transfer (WT) a water molecule from the bulk to the interface. WT is a measure of the thermodynamic balance between the interaction energy of an interfacial water molecule with the protein and its free energy of interaction with all the other solvent molecules. WT is proportional to the log ratio of the local density of water molecules at the protein interface to the bulk density. Using apoferritin as a benchmark system, we found that 85% of the top 100 water locations with the most favorable excess chemical potential values are observed in one or more structures whose locations were determined from high-resolution cryo-EM maps deposited in the Protein Data Bank (PDB). Seventy percent of the top 200 water locations indexed by excess chemical potential were also observed in PDB structures derived from the cryo-EM maps. The MD simulations are performed without experimental density restraints, yet the water positions with favorable WT values correlate strongly with their corresponding position within experimentally defined maps. This work paves the way for the development of a cryo-EM water placement and refinement tool that integrates MD simulations of the excess chemical potential with cryo-EM data for accurate modeling of water networks.

Indexed as

ApoferritinsCryoelectron MicroscopyMolecular Dynamics SimulationProteinsWaterProtein ConformationThermodynamicsApoferritinsProteinsWater

Identifiers

PMID41606988
PMCPMC13059003

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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.