Evidence map›Paper›PMID 37252099›Full record

ArticleRSC medicinal chemistry2023

Improving binding entropy by higher ligand symmetry? - A case study with human matriptase.

Stefan J Hammerschmidt, Hannah Maus, Annabelle C Weldert, Michael Gütschow, Christian Kersten

Open access · greenAbstract read
In one paragraph

Article in RSC medicinal chemistry, 2023. 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
0.6field-weighted citation impact, top 31% of its field
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, 4 citations in OpenAlex.

  1. 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

5 authors at 2 institutions in 1 country.

Stefan J HammerschmidtInstitute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Staudingerweg 5 55128 Mainz Germany kerstec@uni-mainz.de.ORCID https://orcid.org/0000-0002-0769-8435
Hannah MausInstitute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Staudingerweg 5 55128 Mainz Germany kerstec@uni-mainz.de.ORCID https://orcid.org/0000-0002-3512-5626
Annabelle C WeldertInstitute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Staudingerweg 5 55128 Mainz Germany kerstec@uni-mainz.de.ORCID https://orcid.org/0009-0001-5016-0286
Michael GütschowPharmaceutical Institute, Pharmaceutical & Medicinal Chemistry, University of Bonn An der Immenburg 4 53121 Bonn Germany.ORCID https://orcid.org/0000-0002-9376-7897
Christian KerstenInstitute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Staudingerweg 5 55128 Mainz Germany kerstec@uni-mainz.de.ORCID https://orcid.org/0000-0001-9976-7639
Johannes Gutenberg University Mainz · DEUniversity of Bonn · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding different contributions to the binding entropy of ligands is of utmost interest to better predict affinity and the thermodynamic binding profiles of protein-ligand interactions and to develop new strategies for ligand optimization. To these means, the largely neglected effects of introducing higher ligand symmetry, thereby reducing the number of energetically distinguishable binding modes on binding entropy using the human matriptase as a model system, were investigated. A set of new trivalent phloroglucinol-based inhibitors that address the roughly symmetric binding site of the enzyme was designed, synthesized, and subjected to isothermal titration calorimetry. These highly symmetric ligands that can adopt multiple indistinguishable binding modes exhibited high entropy-driven affinity in line with affinity-change predictions.

Identifiers

PMID37252099
PMCPMC10211324
OpenAlexW4367278908

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.