Evidence map›Paper›PMID 19597941›Full record

ArticleJournal of computer-aided molecular design2009

Molecular dynamics simulation of S100B protein to explore ligand blockage of the interaction with p53 protein.

Zhigang Zhou, Yumin Li

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of computer-aided molecular design, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 33% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. RSC advances · 2020
    Article
  2. Review
  3. Review
  4. 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

2 authors at 2 institutions in 1 country.

Zhigang ZhouDepartment of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN 47907, USA. zhou@pharmacy.purdue.edu
Yumin Li
East Carolina University · USPurdue University West Lafayette · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As a tumor suppressor, p53 plays an important role in cancer suppression. The biological function of p53 as a tumor suppressor is disabled when it binds to S100B. Developing the ligands to block the S100B-p53 interaction has been proposed as one of the most important approaches to the development of anti-cancer agents. We screened a small compound library against the binding interface of S100B and p53 to identify potential compounds to interfere with the interaction. The ligand-binding effect on the S100B-p53 interaction was explored by molecular dynamics at the atomic level. The results show that the ligand bound between S100B and p53 propels the two proteins apart by about 2 A compared to the unligated S100B-p53 complex. The binding affinity of S100B and p53 decreases by ~8.5-14.6 kcal/mol after a ligand binds to the interface from the original unligated state of the S100B-p53 complex. Ligand-binding interferes with the interaction of S100B and p53. Such interference could impact the association of S100B and p53, which would free more p53 protein from the pairing with S100B and restore the biological function of p53 as a tumor suppressor. The analysis of the binding mode and ligand structural features would facilitate our effort to identify and design ligands to block S100B-p53 interaction effectively. The results from the work suggest that developing ligands targeting the interface of S100B and p53 could be a promising approach to recover the normal function of p53 as a tumor suppressor.

Indexed as

Molecular Dynamics SimulationLigandsModels, MolecularNerve Growth FactorsProtein BindingS100 Calcium Binding Protein beta SubunitS100 ProteinsTumor Suppressor Protein p53LigandsNerve Growth FactorsS100 Calcium Binding Protein beta SubunitS100 ProteinsTumor Suppressor Protein p53

Identifiers

PMID19597941
OpenAlexW2091737818

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.