Document Type
Article
Publication Date
2008
Digital Object Identifier (DOI)
https://doi.org/10.1186/1743-422X-5-126
Abstract
Background: A previous study (Goh G.K.-M., Dunker A.K., Uversky V.N. (2008) Protein intrinsic disorder toolbox for comparative analysis of viral proteins. BMC Genomics. 9 (Suppl. 2), S4) revealed that HIV matrix protein p17 possesses especially high levels of predicted intrinsic disorder (PID). In this study, we analyzed the PID patterns in matrix proteins of viruses related and unrelated to HIV-1.
Results: Both SIVmac and HIV-1 p17 proteins were predicted by PONDR VLXT to be highly disordered with subtle differences containing 50% and 60% disordered residues, respectively. SIVmac is very closely related to HIV-2. A specific region that is predicted to be disordered in HIV-1 is missing in SIVmac. The distributions of PID patterns seem to differ in SIVmac and HIV-1 p17 proteins. A high level of PID for the matrix does not seem to be mandatory for retroviruses, since Equine Infectious Anemia Virus (EIAV), an HIV cousin, has been predicted to have low PID level for the matrix; i.e. its matrix protein p15 contains only 21% PID residues. Surprisingly, the PID percentage and the pattern of predicted disorder distribution for p15 resemble those of the influenza matrix protein M1 (25%).
Conclusioin: Our data might have important implications in the search for HIV vaccines since disorder in the matrix protein might provide a mechanism for immune evasion.
Was this content written or created while at USF?
No
Citation / Publisher Attribution
Virology Journal, v. 5, art. 128
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Scholar Commons Citation
Kian-Meng Goh, Gerard; Dunker, A. Keith; and Uversky, Vladimir N., "A Comparative Analysis of Viral Matrix Proteins Using Disorder Predictors" (2008). Molecular Medicine Faculty Publications. 817.
https://digitalcommons.usf.edu/mme_facpub/817