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Computer applications for prediction of protein–protein interactions and rational drug design

Overview of attention for article published in Advances and Applications in Bioinformatics and Chemistry : AABC, November 2009
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Title
Computer applications for prediction of protein–protein interactions and rational drug design
Published in
Advances and Applications in Bioinformatics and Chemistry : AABC, November 2009
DOI 10.2147/aabc.s6272
Pubmed ID
Authors

Solène Grosdidier, Max Totrov, Juan Fernández-Recio

Abstract

In recent years, protein-protein interactions are becoming the object of increasing attention in many different fields, such as structural biology, molecular biology, systems biology, and drug discovery. From a structural biology perspective, it would be desirable to integrate current efforts into the structural proteomics programs. Given that experimental determination of many protein-protein complex structures is highly challenging, and in the context of current high-performance computational capabilities, different computer tools are being developed to help in this task. Among them, computational docking aims to predict the structure of a protein-protein complex starting from the atomic coordinates of its individual components, and in recent years, a growing number of docking approaches are being reported with increased predictive capabilities. The improvement of speed and accuracy of these docking methods, together with the modeling of the interaction networks that regulate the most critical processes in a living organism, will be essential for computational proteomics. The ultimate goal is the rational design of drugs capable of specifically inhibiting or modifying protein-protein interactions of therapeutic significance. While rational design of protein-protein interaction inhibitors is at its very early stage, the first results are promising.

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X Demographics

The data shown below were collected from the profile of 1 X user 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 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Australia 1 2%
United Kingdom 1 2%
Belgium 1 2%
Japan 1 2%
Unknown 45 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 34%
Researcher 14 28%
Student > Bachelor 5 10%
Student > Master 4 8%
Professor > Associate Professor 3 6%
Other 4 8%
Unknown 3 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 44%
Biochemistry, Genetics and Molecular Biology 6 12%
Chemistry 5 10%
Computer Science 4 8%
Pharmacology, Toxicology and Pharmaceutical Science 3 6%
Other 7 14%
Unknown 3 6%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 30 November 2020.
All research outputs
#17,285,668
of 25,373,627 outputs
Outputs from Advances and Applications in Bioinformatics and Chemistry : AABC
#26
of 55 outputs
Outputs of similar age
#91,689
of 108,540 outputs
Outputs of similar age from Advances and Applications in Bioinformatics and Chemistry : AABC
#1
of 1 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 55 research outputs from this source. They receive a mean Attention Score of 2.5. This one is in the 41st percentile – i.e., 41% 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 108,540 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them