Protein farnesyltransferase: Flexible docking studies on inhibitors using computational modeling
- 108 Downloads
Using MacroModel, peptide, peptidomimetic and non-peptidomimetic inhibitors of the zinc metalloenzyme, farnesyltransferase (FTase), were docked into the enzyme binding site. Inhibitor flexibility, farnesyl pyrophosphate substrate flexibility, and partial protein flexibility were taken into account in these docking studies. In addition to CVFM and CVIM, as well as our own inhibitors FTI-276 and FTI-2148, we have docked other farnesyltransferase inhibitors (FTIs) including Zarnestra, which presently is in advanced clinical trials. The AMBER* force field was employed, augmented with parameters that were derived for zinc. A single binding site model that was derived from the crystal structure of CVFM complexed with farnesyltransferase and farnesylpyrophosphate was used for these studies. The docking results using the lowest energy structure from the simulation, or one of the lowest energy structures, were generally in excellent agreement with the X-ray structures. One of the most important findings of this study is that numerous alternative conformations for the methionine side chain can be accommodated by the enzyme suggesting that the methionine pocket can tolerate groups larger than methionine at the C-terminus of the tetrapeptide and suggesting alternative locations for the placement of side chains that may improve potency.
Keywordsdocking, drug design, flexible docking, molecular modeling, protein farnesyltransferase
Unable to display preview. Download preview PDF.
We thank the National Institutes of Health (CA67771) for financial support of this work. We also thank Dr. Corey Strickland of Schering Plough for supplying us with the coordinates of the X-ray structures of FTI-276 and FTI-2148. We thank Mr. Matt Maderios of Eckerd College for assistance with the docking studies performed on DPI-1.
- 2.Zhu K., Hamilton A.D., Sebti S.M., (2003). Curr. Opin. Investig. Drugs 4:1428Google Scholar
- 10.Long S.B., Hancock P.J., Kral A.M., Hellinga H.W., Beese L.S., (2001) Proc. Natl. Acad. Sci. U.S.A. 98:12,948Google Scholar
- 15.Ohkanda, J., Strickland, C.L., Blaskovich, M.A., Carrico, D., Lockman, J.W., Vogt, A., Bucher, C.J., Sun, J., Qian, Y., Knowles, D., Pusateri, E.E., Sebti, S.M. and Hamilton, A.D., Organic Biomol. Chem. (In press)Google Scholar
- 16.Mohamadi, F., Richards, N.G.J., Guida, W.C., Liskamp, R., Lipton, M., Caufield, C., Chang, G., Hendrickson, T. and Still, W.C., J. Comput. Chem. 11 (1990) 11, 440; MacroModel, Schrödinger L.L.C. (www.schrodinger.com), New York, NY, USAGoogle Scholar
- 18.FLO, Thistlesoft, Colebrook, CT, USAGoogle Scholar
- 20.Viewer Lite, Accelrys, Inc. (www.accelrys.com), San Diego, CA, USAGoogle Scholar
- 23.Jaguar, Schrödinger L.L.C. (www.schrodinger.com), New York, NY, USAGoogle Scholar
- 26.Lancet, J.E., Rosenblatt, J.D., Liesveld, J.L. et al., Proc. Am. Soc. Clin. Oncol. (2000) 19Google Scholar
- 27.Lobell R.B., Omer C.A., Abrahams M.T. et al. (2001). Cancer Res. :61:8758Google Scholar