Applications of Analytical Ultracentrifugation in Structure-Based Drug Design
As a technique analytical ultracentrifugation encompasses a family of related hydrodynamic methods which are employed to monitor either transport (sedimentation velocity) or equilibrium (sedimentation equilibrium) processes. Recent development of the Beckman Optima XLA analytical ultracentrifuge, to eventually replace the Model E, makes it possible to routinely apply these methods to biophysical problems associated with the development of effective, targeted, pharmacophores. In order to evaluate the contributions that ultracentrifugation can make to the process of structure-based drug design it is essential to first define the drug design cycle (Fig. 1). The characterizations of structure and function provided by Protein Biochemistry in this process precede and fuel all subsequent three-dimensional structure determinations. The role of computationally-based and structure-based 3D information in the design cycle has recently been elaborated (Propst and Perun, 1989, and references cited therein). Typically, the cycle begins with the identification of a tissue source of the “activity” of interest: i.e. the protein or the DNA encoding the protein of interest. Whether the desired protein is from a natural or recombinant source it is first purified and characterized. Some recent examples from our laboratories include the purification and characterization of two classes of natural and recombinant, highly-expressed, peptidyl-prolyl isomerases, cyclophilin (Holzman et al., 1991, and references cited therein) and FKBP (Edalji et al., 1992).
KeywordsMolecular Weight Distribution Drug Design Radial Position Sedimentation Velocity Fractional Contribution
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- Fujita,H. (1962) in “Mathematical Theory of Sedimentation Analysis” Academic Press, NY., pp 64–122.Google Scholar
- Giebeler, R. (1992) in Analytical Ultracentrifugation in Biochemistry and Polymer Science, (S.E. Harding, A.J. Rowe, J.C. Horton, Eds.) Roy. Soc. Chem., London, pp 16–25.Google Scholar
- Giordano, T., Pan, J.B., Monteggia, L.M., Holzman, T.F., Snyder, S.W., Krafft, G. Ghanbari, H., and Kowal, N. W. (1994) Exptl. Neurol. 125, in press.Google Scholar
- Holzman, T.F., Egan, D.A., Chung, C.C., Rittenhouse, J., and Turon, M. (1990) Biophys. J. 57, 378.Google Scholar
- Holzman, T.F., Fesik, S.W., Park, C., and Kofron, J.A. (1991) in Applications of Enzyme Biotechnology (Kelly, J.A. and Baldwin, T.O., Eds.) Plenum, pp. 109–128.Google Scholar
- Holzman, T.F., Egan, D.A., and Edalji, R. (1992a) Biophys. J. 61, 171.Google Scholar
- Holzman, T.F., Gampe, R.T., and Fesik, S.W. (1992b) Biophys. J. 61, 475.Google Scholar
- Holzman, T.F., Gampe, R.T., and Fesik, S.W. (1992c) Biophys. J. 61, 478.Google Scholar
- Propst, C.L., and Perun, T.J. (1989) in Computer-Aided Drug Design: Methods and Applications, (C.L. Propst and T.J Perun, Eds.) Marcel Dekker, New York, pp. 1–16.Google Scholar
- Snyder, S.W., Ladror, U.S., Wang, G.T., Krafiìt, G.A., and Holzman, T.F. (1993a) Biophys. J. 64, 378.Google Scholar
- Snyder, S.W., Ladror, U.S., Wang, G.T., Krafft, G.A., and Holzman, T.F. (1993b) Biophys. J. 64, 378.Google Scholar