↓ Skip to main content

A novel small molecule inhibitor of p32 mitochondrial protein overexpressed in glioma

Overview of attention for article published in Journal of Translational Medicine, October 2017
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users

Citations

dimensions_citation
23 Dimensions

Readers on

mendeley
34 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A novel small molecule inhibitor of p32 mitochondrial protein overexpressed in glioma
Published in
Journal of Translational Medicine, October 2017
DOI 10.1186/s12967-017-1312-7
Pubmed ID
Authors

Venkata Yenugonda, Natsuko Nomura, Valentina Kouznetsova, Igor Tsigelny, Valentina Fogal, Elmar Nurmemmedov, Santosh Kesari, Ivan Babic

Abstract

The mitochondrial protein p32 is a validated therapeutic target of cancer overexpressed in glioma. Therapeutic targeting of p32 with monoclonal antibody or p32-binding LyP-1 tumor-homing peptide can limit tumor growth. However, these agents do not specifically target mitochondrial-localized p32 and would not readily cross the blood-brain barrier to target p32-overexpressing gliomas. Identifying small molecule inhibitors of p32 overexpressed in cancer is a more rational therapeutic strategy. Thus, in this study we employed a pharmacophore modeling strategy to identify small molecules that could bind and inhibit mitochondrial p32. A pharmacophore model of C1q and LyP-1 peptide association with p32 was used to screen a virtual compound library. A primary screening assay for inhibitors of p32 was developed to identify compounds that could rescue p32-dependent glutamine-addicted glioma cells from glutamine withdrawal. Inhibitors from this screen were analyzed for direct binding to p32 by fluorescence polarization assay and protein thermal shift. Affect of the p32 inhibitor on glioma cell proliferation was assessed by Alamar Blue assay, and affect on metabolism was examined by measuring lactate secretion. Identification of a hit compound (M36) validates the pharmacophore model. M36 binds directly to p32 and inhibits LyP-1 tumor homing peptide association with p32 in vitro. M36 effectively inhibits the growth of p32 overexpressing glioma cells, and sensitizes the cells to glucose depletion. This study demonstrates a novel screening strategy to identify potential inhibitors of mitochondrial p32 protein overexpressed in glioma. High throughput screening employing this strategy has potential to identify highly selective, potent, brain-penetrant small molecules amenable for further drug development.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 18%
Student > Ph. D. Student 6 18%
Professor 5 15%
Student > Master 4 12%
Student > Doctoral Student 3 9%
Other 5 15%
Unknown 5 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 21%
Chemistry 6 18%
Medicine and Dentistry 4 12%
Agricultural and Biological Sciences 3 9%
Pharmacology, Toxicology and Pharmaceutical Science 2 6%
Other 3 9%
Unknown 9 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 October 2017.
All research outputs
#14,956,881
of 23,006,268 outputs
Outputs from Journal of Translational Medicine
#1,994
of 4,022 outputs
Outputs of similar age
#193,587
of 327,016 outputs
Outputs of similar age from Journal of Translational Medicine
#20
of 57 outputs
Altmetric has tracked 23,006,268 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,022 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 327,016 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 57 others from the same source and published within six weeks on either side of this one. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.