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modPDZpep: a web resource for structure based analysis of human PDZ-mediated interaction networks

Overview of attention for article published in Biology Direct, September 2016
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Title
modPDZpep: a web resource for structure based analysis of human PDZ-mediated interaction networks
Published in
Biology Direct, September 2016
DOI 10.1186/s13062-016-0151-4
Pubmed ID
Authors

Neetu Sain, Debasisa Mohanty

Abstract

PDZ domains recognize short sequence stretches usually present in C-terminal of their interaction partners. Because of the involvement of PDZ domains in many important biological processes, several attempts have been made for developing bioinformatics tools for genome-wide identification of PDZ interaction networks. Currently available tools for prediction of interaction partners of PDZ domains utilize machine learning approach. Since, they have been trained using experimental substrate specificity data for specific PDZ families, their applicability is limited to PDZ families closely related to the training set. These tools also do not allow analysis of PDZ-peptide interaction interfaces. We have used a structure based approach to develop modPDZpep, a program to predict the interaction partners of human PDZ domains and analyze structural details of PDZ interaction interfaces. modPDZpep predicts interaction partners by using structural models of PDZ-peptide complexes and evaluating binding energy scores using residue based statistical pair potentials. Since, it does not require training using experimental data on peptide binding affinity, it can predict substrates for diverse PDZ families. Because of the use of simple scoring function for binding energy, it is also fast enough for genome scale structure based analysis of PDZ interaction networks. Benchmarking using artificial as well as real negative datasets indicates good predictive power with ROC-AUC values in the range of 0.7 to 0.9 for a large number of human PDZ domains. Another novel feature of modPDZpep is its ability to map novel PDZ mediated interactions in human protein-protein interaction networks, either by utilizing available experimental phage display data or by structure based predictions. In summary, we have developed modPDZpep, a web-server for structure based analysis of human PDZ domains. It is freely available at http://www.nii.ac.in/modPDZpep.html or http://202.54.226.235/modPDZpep.html . This article was reviewed by Michael Gromiha and Zoltán Gáspári.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 3 18%
Student > Bachelor 2 12%
Student > Master 2 12%
Professor > Associate Professor 2 12%
Student > Ph. D. Student 2 12%
Other 4 24%
Unknown 2 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 29%
Biochemistry, Genetics and Molecular Biology 4 24%
Computer Science 2 12%
Engineering 2 12%
Chemistry 1 6%
Other 0 0%
Unknown 3 18%
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 23 September 2016.
All research outputs
#20,342,896
of 22,889,074 outputs
Outputs from Biology Direct
#450
of 487 outputs
Outputs of similar age
#278,296
of 320,659 outputs
Outputs of similar age from Biology Direct
#15
of 18 outputs
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