Evidence map›Paper›PMID 39678601›Full record

ArticleAmerican journal of translational research2024

MMP9 in pan-cancer and computational study to screen for MMP9 inhibitors.

Xianjie Ai, Xinyu Wang, Taotao Ren, Zhong Li, Bo Wu, Ming Li

Abstract read
In one paragraph

Article in American journal of translational research, 2024. 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. 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

6 authors.

Xianjie AiLower Extremity Division, Orthopedic Trauma Department, Honghui Hospital, Xi'an Jiaotong University Youyi East Road No. 555, Beilin District, Xi'an, Shaanxi, China.
Xinyu WangDepartment of Orthopaedic Trauma, Center of Orthopaedics and Traumatology, The First Hospital of Jilin University Street Xinmin 71, Changchun, Jilin, China.
Taotao RenLower Extremity Division, Orthopedic Trauma Department, Honghui Hospital, Xi'an Jiaotong University Youyi East Road No. 555, Beilin District, Xi'an, Shaanxi, China.
Zhong LiLower Extremity Division, Orthopedic Trauma Department, Honghui Hospital, Xi'an Jiaotong University Youyi East Road No. 555, Beilin District, Xi'an, Shaanxi, China.
Bo WuLower Extremity Division, Orthopedic Trauma Department, Honghui Hospital, Xi'an Jiaotong University Youyi East Road No. 555, Beilin District, Xi'an, Shaanxi, China.
Ming LiLower Extremity Division, Orthopedic Trauma Department, Honghui Hospital, Xi'an Jiaotong University Youyi East Road No. 555, Beilin District, Xi'an, Shaanxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe stromal cell protein metalloproteinase 9 (MMP9), associated with extracellular matrix degradation and remodeling, promotes tumor invasion and metastasis and regulates cell adhesion molecule and cytokine activity. This study evaluated MMP9 in pan-cancer and screened for compounds and drug candidates that can inhibit it.

methodsMMP9 expression in pan-cancer tissues was evaluated in a pan-cancer dataset from the University of California Santa Cruz database, along with the correlation between MMP9 and the tumor microenvironment (TME), RNA modification genes, and tumor mutation burden. MMP9 crystal structures were downloaded, and a ligand-based pharmacophore model was constructed. A machine learning model was constructed for further screening. The identified compounds were pooled into Discovery Studio 4.5 for absorption, distribution, metabolism, and excretion (ADME) and toxicity prediction. Molecular docking was used to demonstrate the binding affinity and mechanism between the compounds and MMP9, and the stability of the ligand-receptor complex was assessed.

resultsThe expression levels of MMP9 differed between tumor tissues. Prognostic analysis showed that high MMP9 expression indicates poor survival and tumor progression in glioma (GMBLGG), pan-kidney (KIPAN; KICH+KIRC+KIRP), uveal melanoma (UVM), low-grade glioma (LGG), adrenocortical carcinoma (ACC), and liver hepatocellular carcinoma (LIHC). MMP9 expression in GMBLGG, KIPAN, UVM, LGG, ACC, and LIHC was positively correlated with the TME. The ligand-based pharmacophore model and the machine learning model identified 49 small molecules. ADME and toxicity prediction identified CEMBL82047 and CEMBL381163 as potential MMP9 inhibitors, showing robust binding affinity with MMP9. The resulting complexes are stable in the natural environment.

conclusionCHEMBL82047 and CHEMBL381163 are ideal compounds for inhibiting MMP9. The findings of this study will contribute to the design and improvement of MMP9-targeting drugs.

Indexed as

ligand-based pharmacophore modelmachine learning modelMMP9molecular dynamics simulationpan-cancervirtual screening

Identifiers

PMID39678601
PMCPMC11645558

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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.