Skip to main content

Intra- and Inter-Molecular Coevolution: The Case of HIV1 Protease and Reverse Transcriptase

  • Conference paper
Biomedical Engineering Systems and Technologies (BIOSTEC 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 127))

Abstract

The stability, fold, and the function of proteins need to be maintained throughout the evolution of these molecules – inducing a selective pressure, that can be revealed in sequence data sets. The conservation of structure and function implies coevolution of amino acids within the protein. To understand such selective pressure in the evolution of the human immunodeficiency virus (HIV), we apply information theoretical measures to the two most important enzymes for the progression of viral infection: the reverse transcriptase and the protease. We computed the mutual information to derive insight into the selective pressure acting locally and globally on the enzymes. We found intra- and inter-protein co-evolution of residues in these enzymes and annotate important structural-evolutionary correlations. We discuss a signal indicating a potential co-evolution between the protease and the reverse transcriptase.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Tsygankov, A.Y.: Current developments in anti-HIV/AIDS gene therapy. Curr. Opin. Investig Drugs 10(2), 137–149 (2009)

    MathSciNet  Google Scholar 

  2. Wlodawer, A., Erickson, J.: Structure-based inhibitors of HIV-1 protease. Annu. Rev. Biochem. 62(1), 543–585 (1993)

    Article  Google Scholar 

  3. Perelson, A.S., Neumann, A.U., Markowitz, M., Leonard, J., Ho, D.: HIV-1 dynamics in vivo: virion clearance rate, infected cell life-span, and viral generation time. Science 271, 1582–1586 (1996)

    Article  Google Scholar 

  4. Richman, D., Margolis, D., Delaney, M., Greene, W.C., Hazuda, D., Pomerantz, R.J.: The challenge of finding a cure for HIV infection. Science 323, 1304–1307 (2009)

    Article  Google Scholar 

  5. Rong, L., Gilchrist, M.A., Feng, Z., Perelson, A.S.: Modeling within-host HIV-1 dynamics and the evolution of drug resistance: Trade-offs between viral enzyme function and drug susceptibility. J. Theo. Biol. 247, 804–818 (2007)

    Article  MathSciNet  Google Scholar 

  6. Chen, L., Lee, C.: Distinguishing HIV-1 drug resistance, accessory, and viral fitness mutations using conditional selection pressure analysis of treated versus untreated patient samples. Biology Direct 1(1), 14 (2006)

    Article  Google Scholar 

  7. Trylska, J., Tozzini, V., Chang, C., McCammon, J.A.: HIV-1 protease substrate binding and product release pathways explored with coarse-grained molecular dynamics. Biophys. J. 92, 4179–4187 (2007)

    Article  Google Scholar 

  8. Hamacher, K., McCammon, J.A.: Computing the amino acid specificity of fluctuations in biomolecular systems. J. Chem. Theory Comput. 2(3), 873–878 (2006)

    Article  Google Scholar 

  9. Hamacher, K.: Relating sequence evolution of HIV1-protease to its underlying molecular mechanics. Gene 422, 30–36 (2008)

    Article  Google Scholar 

  10. Pan, C., Kim, J., Chen, L., Wang, Q., Lee, C.: The hiv positive selection mutation database. Nuc. Acids Res. 35(1), D371–D375 (2007)

    Article  Google Scholar 

  11. Chen, L., Perlina, A., Lee, C.J.: Positive Selection Detection in 40,000 Human Immunodeficiency Virus (HIV) Type 1 Sequences Automatically Identifies Drug Resistance and Positive Fitness Mutations in HIV Protease and Reverse Transcriptase. J. Virol. 78(7), 3722–3732 (2004)

    Article  Google Scholar 

  12. Shannon, C.E.: Prediction and entropy of printed english. The Bell System Technical Journal 30, 50–64 (1951)

    MATH  Google Scholar 

  13. Lund, O., Nielsen, M., Lundegaard, C., Brunak, C.K.S.: Immunological Bioinformatics. MIT Press, Cambridge (2005)

    MATH  Google Scholar 

  14. Hamacher, K.: Information theoretical measures to analyze trajectories in rational molecular design. J. Comp. Chem. 28(16), 2576–2580 (2007)

    Article  MathSciNet  Google Scholar 

  15. Hamacher, K.: Protein domain phylogenies - information theory and evolutionary dynamics. In: Fred, A., Filipe, J., Gamboa, H. (eds.) BIOINFORMATICS 2010, pp. 114–122 (2010)

    Google Scholar 

  16. Pape, S., Hoffgaard, F., Hamacher, K.: Distance-dependent classification of amino acids by information theory. Proteins: Structure, Function, and Bioinformatics 78, 2322–2328 (2010)

    Article  Google Scholar 

  17. Boba, P., Weil, P., Hoffgaard, F., Hamacher, K.: Co-evolution in HIV enzymes. In: Fred, A., Filipe, J., Gamboa, H. (eds.) BIOINFORMATICS 2010, pp. 39–47 (2010)

    Google Scholar 

  18. Weil, P., Hoffgaard, F., Hamacher, K.: Estimating sufficient statistics in co-evolutionary analysis by mutual information. Computational Biology and Chemistry 33(6), 440–444 (2009)

    Article  MathSciNet  Google Scholar 

  19. Boba, P., Hamacher, K. (2009), http://bioserver.bio.tu-darmstadt.de/HIV

  20. Press, W.H., et al.: Numerical Recipies in C. Cambridge University Press, Cambridge (1995)

    Google Scholar 

  21. Sarafianos, S.G., Das, K., Hughes, S.H., Arnold, E.: Taking aim at a moving target: designing drugs to inhibit drug-resistant hiv-1 reverse transcriptases. Current Opinion in Structural Biology 14(6), 716–730 (2004)

    Article  Google Scholar 

  22. Prajapati, D.G., Ramajayam, R., Yadav, M.R., Giridhar, R.: The search for potent, small molecule nnrtis: A review. Bioorganic & Medicinal Chemistry 17(16), 5744–5762 (2009)

    Article  Google Scholar 

  23. Yoshimura, K., Kato, R., Yusa, K., Kavlick, M.F., Maroun, V., Nguyen, A., Mimoto, T., Ueno, T., Shintani, M., Falloon, J., Masur, H., Hayashi, H., Erickson, J., Mitsuya, H.: JE-2147: A dipeptide protease inhibitor (PI) that potently inhibits multi-PI-resistant HIV-1. Proc. Natl. Acad. Sci. 96, 8675–8680 (1999)

    Article  Google Scholar 

  24. Reiling, K., Endres, N., Dauber, D., Craik, C., Stroud, R.: Anisotropic dynamics of the JE-2147-HIV protease complex: Drug resistance and thermodynamic binding mode examined in a 1.09 a structure. Biochemistry 41, 4582 (2002)

    Article  Google Scholar 

  25. Perryman, A.L., Lin, J.H., McCammon, J.A.: Restrained molecular dynamics simulations of hiv-1 protease: The first step in validating a new target for drug design. Biopolymers 82(3), 272–284 (2006)

    Article  Google Scholar 

  26. Stone, J.: An Efficient Library for Parallel Ray Tracing and Animation. Master’s thesis, Computer Science Department, University of Missouri-Rolla (April 1998)

    Google Scholar 

  27. Humphrey, W., Dalke, A., Schulten, K.: VMD – Visual Molecular Dynamics. Journal of Molecular Graphics 14, 33–38 (1996)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Boba, P., Weil, P., Hoffgaard, F., Hamacher, K. (2011). Intra- and Inter-Molecular Coevolution: The Case of HIV1 Protease and Reverse Transcriptase. In: Fred, A., Filipe, J., Gamboa, H. (eds) Biomedical Engineering Systems and Technologies. BIOSTEC 2010. Communications in Computer and Information Science, vol 127. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18472-7_28

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-18472-7_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-18471-0

  • Online ISBN: 978-3-642-18472-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics