Evidence map›Paper›PMID 39886596›Full record

ArticleJACS Au2025

Quantitative Prediction of Protein-Polyelectrolyte Binding Thermodynamics: Adsorption of Heparin-Analog Polysulfates to the SARS-CoV-2 Spike Protein RBD.

Lenard Neander, Cedric Hannemann, Roland R Netz, Anil Kumar Sahoo

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

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. Polysialosides Outperform Sulfated Analogs for Binding with SARS-CoV-2.Small (Weinheim an der Bergstrasse, Germany) · 2025
    Article
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

4 authors.

Lenard NeanderDepartment of Physics, Freie Universität Berlin, Arnimallee 14, Berlin 14195, Germany.
Cedric HannemannDepartment of Physics, Freie Universität Berlin, Arnimallee 14, Berlin 14195, Germany.ORCID https://orcid.org/0009-0005-2467-168X
Roland R NetzDepartment of Physics, Freie Universität Berlin, Arnimallee 14, Berlin 14195, Germany.ORCID https://orcid.org/0000-0003-0147-0162
Anil Kumar SahooDepartment of Physics, Freie Universität Berlin, Arnimallee 14, Berlin 14195, Germany.ORCID https://orcid.org/0000-0001-7769-4774

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interactions of polyelectrolytes (PEs) with proteins play a crucial role in numerous biological processes, such as the internalization of virus particles into host cells. Although docking, machine learning methods, and molecular dynamics (MD) simulations are utilized to estimate binding poses and binding free energies of small-molecule drugs to proteins, quantitative prediction of the binding thermodynamics of PE-based drugs presents a significant obstacle in computer-aided drug design. This is due to the sluggish dynamics of PEs caused by their size and strong charge-charge correlations. In this paper, we introduce advanced sampling methods based on a force-spectroscopy setup and theoretical modeling to overcome this barrier. We exemplify our method with explicit solvent all-atom MD simulations of the interactions between anionic PEs that show antiviral properties, namely heparin and linear polyglycerol sulfate (LPGS), and the SARS-CoV-2 spike protein receptor binding domain (RBD). Our prediction for the binding free-energy of LPGS to the wild-type RBD matches experimentally measured dissociation constants within thermal energy,

Identifiers

PMID39886596
PMCPMC11775700

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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.