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Identification of a better Homo sapiens Class II HDAC inhibitor through binding energy calculations and descriptor analysis

Overview of attention for article published in BMC Bioinformatics, October 2010
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

news
1 news outlet
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
60 Mendeley
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Title
Identification of a better Homo sapiens Class II HDAC inhibitor through binding energy calculations and descriptor analysis
Published in
BMC Bioinformatics, October 2010
DOI 10.1186/1471-2105-11-s7-s16
Pubmed ID
Authors

Usman Sumo Friend Tambunan, Evi Kristin Wulandari

Abstract

Human papillomaviruses (HPVs) are the most common on sexually transmitted viruses in the world. HPVs are responsible for a large spectrum of deseases, both benign and malignant. The certain types of HPV are involved in the development of cervical cancer. In attemps to find additional drugs in the treatment of cervical cancer, inhibitors of the histone deacetylases (HDAC) have received much attention due to their low cytotoxic profiles and the E6/E7 oncogene function of human papilomavirus can be completely by passed by HDAC inhibition. The histone deacetylase inhibitors can induce growth arrest, differentiation and apoptosis of cancer cells. HDAC class I and class II are considered the main targets for cancer. Therefore, the six HDACs class II was modeled and about two inhibitors (SAHA and TSA) were docked using AutoDock4.2, to each of the inhibitor in order to identify the pharmacological properties. Based on the results of docking, SAHA and TSA were able to bind with zinc ion in HDACs models as a drug target. SAHA was satisfied almost all the properties i.e., binding affinity, the Drug-Likeness value and Drug Score with 70% oral bioavailability and the carbonyl group of these compound fits well into the active site of the target where the zinc is present. Hence, SAHA could be developed as potential inhibitors of class II HDACs and valuable cervical cancer drug candidate.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Indonesia 4 7%
United States 1 2%
India 1 2%
Unknown 54 90%

Demographic breakdown

Readers by professional status Count As %
Student > Master 13 22%
Student > Ph. D. Student 10 17%
Student > Bachelor 9 15%
Researcher 6 10%
Student > Doctoral Student 5 8%
Other 14 23%
Unknown 3 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 23%
Chemistry 14 23%
Medicine and Dentistry 12 20%
Biochemistry, Genetics and Molecular Biology 8 13%
Pharmacology, Toxicology and Pharmaceutical Science 5 8%
Other 3 5%
Unknown 4 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 05 May 2023.
All research outputs
#2,813,826
of 23,515,383 outputs
Outputs from BMC Bioinformatics
#917
of 7,404 outputs
Outputs of similar age
#11,390
of 100,552 outputs
Outputs of similar age from BMC Bioinformatics
#3
of 55 outputs
Altmetric has tracked 23,515,383 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,404 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 87% of its peers.
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 100,552 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.