Structural similarity-based predictions of protein interactions between HIV-1 and Homo sapiens
Public Deposited- Creator
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Doolittle, Janet M
- Affiliation: School of Medicine, Curriculum in Bioinformatics and Computational Biology
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Gomez, Shawn
- Affiliation: School of Medicine, Department of Pharmacology
- Abstract
- Abstract Background In the course of infection, viruses such as HIV-1 must enter a cell, travel to sites where they can hijack host machinery to transcribe their genes and translate their proteins, assemble, and then leave the cell again, all while evading the host immune system. Thus, successful infection depends on the pathogen's ability to manipulate the biological pathways and processes of the organism it infects. Interactions between HIV-encoded and human proteins provide one means by which HIV-1 can connect into cellular pathways to carry out these survival processes. Results We developed and applied a computational approach to predict interactions between HIV and human proteins based on structural similarity of 9 HIV-1 proteins to human proteins having known interactions. Using functional data from RNAi studies as a filter, we generated over 2000 interaction predictions between HIV proteins and 406 unique human proteins. Additional filtering based on Gene Ontology cellular component annotation reduced the number of predictions to 502 interactions involving 137 human proteins. We find numerous known interactions as well as novel interactions showing significant functional relevance based on supporting Gene Ontology and literature evidence. Conclusions Understanding the interplay between HIV-1 and its human host will help in understanding the viral lifecycle and the ways in which this virus is able to manipulate its host. The results shown here provide a potential set of interactions that are amenable to further experimental manipulation as well as potential targets for therapeutic intervention.
- Date of publication
- April 28, 2010
- DOI
- Identifier
- Resource type
- Article
- Rights statement
- In Copyright
- Rights holder
- Janet M Doolittle et al.; licensee BioMed Central Ltd.
- License
- Journal title
- Virology Journal
- Journal volume
- 7
- Journal issue
- 1
- Page start
- 82
- Language
- English
- Is the article or chapter peer-reviewed?
- Yes
- ISSN
- 1743-422X
- Bibliographic citation
- Virology Journal. 2010 Apr 28;7(1):82
- Publisher
- BioMed Central Ltd
- Access right
- Open Access
- Date uploaded
- August 23, 2012
Relations
- Parents:
This work has no parents.
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1743-422X-7-82.pdf | 2019-05-07 | Public | Download |
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Full Prediction Network | 2019-05-07 | Public | Download |
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1743-422X-7-82.xml | 2019-05-07 | Public | Download |
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Interaction Predictions after CC Filter | 2019-05-07 | Public | Download |
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Interaction Predictions | 2019-05-07 | Public | Download |
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Dali Similarities | 2019-05-07 | Public | Download |
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HIV-1 Protein Identifiers. The PDB codes and Uniprot accessions that correspond to each HIV-1 protein are given. This file is provided in tab-separated text format and may be viewed in a text editor or Excel. | 2019-05-07 | Public | Download |