↓ Skip to main content

PLOS

Target Essentiality and Centrality Characterize Drug Side Effects

Overview of attention for article published in PLoS Computational Biology, July 2013
Altmetric Badge

Mentioned by

twitter
4 X users
facebook
1 Facebook page

Citations

dimensions_citation
46 Dimensions

Readers on

mendeley
79 Mendeley
citeulike
13 CiteULike
Title
Target Essentiality and Centrality Characterize Drug Side Effects
Published in
PLoS Computational Biology, July 2013
DOI 10.1371/journal.pcbi.1003119
Pubmed ID
Authors

Xiujuan Wang, Bram Thijssen, Haiyuan Yu

Abstract

To investigate factors contributing to drug side effects, we systematically examine relationships between 4,199 side effects associated with 996 drugs and their 647 human protein targets. We find that it is the number of essential targets, not the number of total targets, that determines the side effects of corresponding drugs. Furthermore, within the context of a three-dimensional interaction network with atomic-resolution interaction interfaces, we find that drugs causing more side effects are also characterized by high degree and betweenness of their targets and highly shared interaction interfaces on these targets. Our findings suggest that both essentiality and centrality of a drug target are key factors contributing to side effects and should be taken into consideration in rational drug design.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Hungary 1 1%
Germany 1 1%
India 1 1%
Korea, Republic of 1 1%
Spain 1 1%
Luxembourg 1 1%
Unknown 71 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 29%
Researcher 15 19%
Student > Bachelor 10 13%
Student > Master 8 10%
Student > Postgraduate 5 6%
Other 11 14%
Unknown 7 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 38%
Biochemistry, Genetics and Molecular Biology 10 13%
Computer Science 9 11%
Pharmacology, Toxicology and Pharmaceutical Science 4 5%
Engineering 4 5%
Other 11 14%
Unknown 11 14%