CO-EVOLUTION IN HIV ENZYMES

P. Boba, P. Weil, F. Hoffgaard, K. Hamacher

2010

Abstract

Proteins as molecular phenotypes need to maintain their stability, fold, and the functionality throughout their individual and collective evolution. Such important properties are maintained by a selective pressure that reveals itself in sequence data sets. Small adaptive changes are usually possible, but in general the conservation of structure and function implies the co-evolution of amino acids within the molecule. We analyze two most important enzymes in the progression of viral infection by the human immunodeficiency virus (HIV) – namely the reverse transcriptase and the protease – under an information theoretical framework to derive insight into the selective pressure acting locally and globally on the enzymes. To this end we computed mutual information inside the proteins and between the proteins for some 40,000 sequences. We discuss the results of intra- and inter-protein co-evolution of residues in these enzymes and finally annotate important structural-evolutionary correlations. In particular we focus on the reverse transcriptase and a small signal indicating a potential coevolution between the protease and the reverse transcriptase. We convinced ourselves that our sampling is sufficiently large and that no normalization schemes needs to be applied. We conclude with a short outlook into potential implications for drug resistance development.

References

  1. Altschul, S. F., Gish, W., Miller, W., Myers, E. W., and Lipman, D. J. (1990). Basic local alignment search tool. J Mol Biol, (3):403-410.
  2. Boba, P. and Hamacher, K. (2009).
  3. Chen, L. and Lee, C. (2006). 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.
  4. Chen, L., Perlina, A., and Lee, C. J. (2004). 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.
  5. Finn, R. D., Tate, J., Mistry, J., Coggill, P. C., Sammut, S. J., Hotz, H.-R., Ceric, G., Forslund, K., Eddy, S. R., Sonnhammer, E. L. L., and Bateman, A. (2008). The Pfam protein families database. Nucl. Acids Res., 36:D281-D288.
  6. Gloor, G., Martin, L., Wahl, L., and Dunn, S. (2005). Mutual information in protein multiple sequence alignments reveals two classes of coevolving positions. Biochemistry, 44(19):7156-7165.
  7. Hamacher, K. (2007). Information theoretical measures to analyze trajectories in rational molecular design. J. Comp. Chem., 28(16):2576-2580.
  8. Hamacher, K. (2008). Relating sequence evolution of HIV1-protease to its underlying molecular mechanics. Gene, 422:30-36.
  9. Hamacher, K. and McCammon, J. A. (2006). Computing the amino acid specificity of fluctuations in biomolecular systems. J. Chem. Theory Comput., 2(3):873- 878.
  10. Higgins, D. G. and Sharp, P. M. (1988). Clustal: a package for performing multiple sequence alignment on a microcomputer. Gene, 73(1):237-244.
  11. Humphrey, W., Dalke, A., and Schulten, K. (1996). VMD - Visual Molecular Dynamics. Journal of Molecular Graphics, 14:33-38.
  12. Lund, O., Nielsen, M., Lundegaard, C., and Brunak, C. K. S. (2005). Immunological Bioinformatics. MIT Press, Cambridge.
  13. Pan, C., Kim, J., Chen, L., Wang, Q., and Lee, C. (2007). The hiv positive selection mutation database. Nuc. Acids Res., 35:D371-D375(1).
  14. Perelson, A. S., Neumann, A. U., Markowitz, M., Leonard, J., and Ho, D. (1996). HIV-1 dynamics in vivo: virion clearance rate, infected cell life-span, and viral generation time. Science, 271:1582-1586.
  15. Perryman, A. L., Lin, J.-H., and McCammon, J. A. (2006). Restrained molecular dynamics simulations of hiv-1 protease: The first step in validating a new target for drug design. Biopolymers, 82(3):272-284.
  16. Prajapati, D. G., Ramajayam, R., Yadav, M. R., and Giridhar, R. (2009). The search for potent, small molecule nnrtis: A review. Bioorganic & Medicinal Chemistry, 17(16):5744-5762.
  17. Reiling, K., Endres, N., Dauber, D., Craik, C., and Stroud, R. (2002). 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.
  18. Richman, D., Margolis, D., Delaney, M., Greene, W. C., Hazuda, D., and Pomerantz, R. J. (2009). The challenge of finding a cure for HIV infection. Science, 323:1304-1307.
  19. Rong, L., Gilchrist, M. A., Feng, Z., and Perelson, A. S. (2007). 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.
  20. Sarafianos, S. G., Das, K., Hughes, S. H., and Arnold, E. (2004). Taking aim at a moving target: designing drugs to inhibit drug-resistant hiv-1 reverse transcriptases. Current Opinion in Structural Biology, 14(6):716-30.
  21. Schreck, T., Bremm, S., Held, S., and Hamacher, K. (2009). to be published.
  22. Shannon, C. E. (1951). Prediction and entropy of printed english. The Bell System Technical Journal, 30:50- 64.
  23. Stone, J. (1998). An Efficient Library for Parallel Ray Tracing and Animation. Master's thesis, Computer Science Department, University of Missouri-Rolla.
  24. Thompson, J., Higgins, D., and Gibson, T. (1994). CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res., 22:4673-4680.
  25. Trylska, J., Tozzini, V., Chang, C., and McCammon, J. A. (2007). HIV-1 protease substrate binding and product release pathways explored with coarse-grained molecular dynamics. Biophys. J., 92:4179-4187.
  26. Tsygankov, A. Y. (2009). Current developments in antiHIV/AIDS gene therapy. Curr Opin Investig Drugs, 10(2):137-149.
  27. W.H. Press et al (1995). Numerical Recipies in C. Cambridge University Press, Cambridge.
  28. Wlodawer, A. and Erickson, J. (1993). Structure-based inhibitors of HIV-1 protease. Annu. Rev. Biochem., 62(1):543-585.
  29. Yoshimura, K., Kato, R., Yusa, K., Kavlick, M. F., Maroun, V.and Nguyen, A., Mimoto, T., Ueno, T., Shintani, M., Falloon, J., Masur, H., Hayashi, H., Erickson, J., and Mitsuya, H. (1999). JE-2147: A dipeptide protease inhibitor (PI) that potently inhibits multi-PI-resistant HIV-1. Proc. Natl. Acad. Sci., 96:8675-8680.
Download


Paper Citation


in Harvard Style

Boba P., Weil P., Hoffgaard F. and Hamacher K. (2010). CO-EVOLUTION IN HIV ENZYMES . In Proceedings of the First International Conference on Bioinformatics - Volume 1: BIOINFORMATICS, (BIOSTEC 2010) ISBN 978-989-674-019-1, pages 39-47. DOI: 10.5220/0002731800390047


in Bibtex Style

@conference{bioinformatics10,
author={P. Boba and P. Weil and F. Hoffgaard and K. Hamacher},
title={CO-EVOLUTION IN HIV ENZYMES},
booktitle={Proceedings of the First International Conference on Bioinformatics - Volume 1: BIOINFORMATICS, (BIOSTEC 2010)},
year={2010},
pages={39-47},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002731800390047},
isbn={978-989-674-019-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Bioinformatics - Volume 1: BIOINFORMATICS, (BIOSTEC 2010)
TI - CO-EVOLUTION IN HIV ENZYMES
SN - 978-989-674-019-1
AU - Boba P.
AU - Weil P.
AU - Hoffgaard F.
AU - Hamacher K.
PY - 2010
SP - 39
EP - 47
DO - 10.5220/0002731800390047