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Defining Structure in Synthetic Proteins
Predicted 3-dimensional structures, an N-aryl trimer and N-alkyl trimer (top) and a larger cyclic nonamer (bottom) later confirmed by X-ray crystallography results.
Blind conformational predictions were performed for 3 new peptoids using Replica Exchange Molecular Dynamics simulation and Quantum Mechanical refinement. Subsequent comparison with the 3D structure determined by X-ray crystallography showed these predictions to be accurate to within 1 Å, demonstrating that reliable de novo structural prediction for peptoids is possible.
The ability to correctly predict the 3-dimensional structure of peptoids, validates the effectiveness of current theoretical modeling techniques and demonstrates that de novo predictions of small peptoid structures is possible. This accomplishment helps pave the way for rational design of 3-dimensional structure, necessary to synthesize functional peptoid molecules.
- Using a blind prediction method, theoretical modelers predict the structures of three synthesized peptoids.
- Actual structure determined via X-ray crystallography was shown to match the predicted conformations with very high accuracy.
- This study led to characterization of the largest confirmed peptoid structure to date.
Glenn L. Butterfoss, Barney Yoo, Jonathan N. Jaworski, Ilya Chorny, Ken A. Dill, Ronald N. Zuckermann, Richard Bonneau, Kent Kirshenbaum, Vincent A. Voelz PNAS. In Press (2012).
Portions of this work were performed at the Molecular Foundry, Lawrence Berkeley National Laboratory, which is supported by the Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02—05CH11231. Portions of this work were funded by the Defense Threat Reduction Agency under IACRO B1144571. This work was supported by the NSF through award CHE-1152317 to KK. GB and RB were funded by NIH PN2 EY016586- 06, NIH U54CA143907-01 and NSF IOS-1126971. This research was supported in part by the National Science Foundation through major research instrumentation grant number CNS-09-58854.