464675 Self-Assembled Peptides with RGD Motifs As Scaffolds for Tissue Engineering

Thursday, November 17, 2016: 9:00 AM
Yosemite C (Hilton San Francisco Union Square)
Graziano Deidda1, Sai Vamshi R Jonnalagadda2, Jacob W Spies2, Anthi Ranella1, Estelle Mossou3, V. Trevor Forsyth3, Edward P Mitchell4, Anna Mitraki1 and Phanourios Tamamis5, (1)Department of Materials Science and Technology, University of Crete, Heraklion, Greece, (2)Artie McFerrin Department of Chemical Engineering, Texas A&M University, College station, TX, (3)EPSAM/ISTM, Keele University, Staffordshire, United Kingdom, (4)European Synchrotron Radiation Facility, Grenoble, France, (5)Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX

Self-assembled peptides gain increasing interest as biocompatible and biodegradable scaffolds for tissue engineering (1). Rationally designed self-assembling building blocks that carry cell attachment motifs such as RGD are especially attractive. We have been using a combination of theoretical and experimental approaches towards such rational designs (2-5). We have been especially focusing on modular designs that consist of a central ultrashort amphiphilic motif derived from the adenovirus fiber shaft (2-4). This central motif is combined with the RGD motif and cysteine residues that allow further functionalization possibilities, such as conjugation of growth factors or attachment to surfaces. We employed replica exchange MD simulations and free energy calculations using CHARMM (6) to computationally investigate the self-assembly properties of possible designed peptide sequences. Our simulations provide insights into the amyloidogenic β-sheet rich self-assembling conformations of the peptides. We performed a detailed analysis on the highly-ordered and well- aligned β-sheet containing conformations and provided insights into the structural arrangement of the peptides’ functional groups. The designer peptides experimentally self-assemble into fibers that are structurally characterized with Transmission Electron Microscopy, Scanning Electron Microscopy and X-ray fiber diffraction. Furthermore, they support cell attachment and proliferation of model cell lines. Such short self-assembling peptides that are amenable to computational design offer open-ended possibilities towards multifunctional tissue engineering scaffolds of the future.

References

1. Loo Y, Goktas M, Tekinay AB, Guler MO, Hauser CAE, Mitraki A. (2015) Self-assembled proteins and peptides as scaffolds for tissue regeneration. Advanced Healthcare Materials 16: 2557-86.

2. Tamamis, P., Kasotakis, E., Mitraki, A., and Archontis, G. (2009) Amyloid-like self-assembly of peptide sequences from the adenovirus fiber shaft: insights from molecular dynamics simulations. J. Phys. Chem. B. 113: 15639-15647.

3. Tamamis, P., Kasotakis, E., Archontis, G., Mitraki, A. (2014) Combination of Theoretical and Experimental Approaches for the Design and Study of Fibril-forming Peptides. In Protein Design: Methods and Applications. Methods Mol. Biol. 1216: 53-70.

4. Tamamis, P., Archontis, G. (2011) Amyloid-like Self-Assembly of a Dodecapeptide Sequence from the Adenovirus Fiber Shaft: Perspectives from Molecular Dynamics Simulations. Journal of Non-Crystalline Solids, 357 (2): 717-722.

5. Tamamis, P., Terzaki, K., Kassinopoulos, M., Mastrogiannis, L., Mossou, E., Forsyth, V. T., Mitchell, E. P., Mitraki, A., Archontis, G. (2014) Self-Assembly of an Aspartate-Rich Sequence from the Adenovirus Fiber Shaft: Insights from Molecular Dynamics Simulations and Experiments. Journal of Physical Chemistry B, 118 (7): 1765-1774.

6. B.R. Brooks, C.L. Brooks, III, A.D. MacKerell, Jr., L. Nilsson, R.J. Petrella, B. Roux, Y. Won, G. Archontis, C. Bartels, S. Boresch, A. Caflisch, L. Caves, Q. Cui, A.R. Dinner, M. Feig, S. Fischer, J. Gao, M. Hodoscek, W. Im, K. Kuczera, T. Lazaridis, J. Ma, V. Ovchinnikov, E. Paci, R.W. Pastor, C.B. Post, J.Z. Pu, M. Schaefer, B. Tidor, R. M. Venable, H. L. Woodcock, X. Wu, W. Yang, D.M. York, and M. Karplus. (2009) CHARMM: The Biomolecular Simulation Program J Comput Chem. 30(10): 1545–1614.


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