(575f) Computational Design of Novel Self-Assembling Peptide Biomaterials Based on an Amyloid Forming Motif from the Adenovirus Fiber Shaft

The properties of self-assembling peptides can be tuned through changes at their sequence level, and thus amyloid-forming peptides are increasingly gaining interest as potential biomaterials for a series of applications (1-5). Naturally occurring sequences from amyloid proteins or β-sheet rich proteins, for example sequence NSGAITIG from the adenovirus fiber shaft, self-assemble into amyloid fibril peptide nanostructures. Previous computational studies have suggested that the GAITIG motif is the key amyloidogenic region of the peptide with sequence NSGAITIGC (6), and experiments exploited these for the fabrication of biomaterials with several biomedical and technological applications. Here, we introduced a combination of computational and experimental studies, and investigated the addition of the cell-adhesive motif as well as single residues at the two termini of GAITIG motif, aiming at discovering novel bifunctional self-assembling amyloid peptide biomaterials with advanced biomedical applications.

In the first part of the study, we used replica exchange MD simulations and free energy calculations, as in ref. (7,8) in CHARMM (9) to design a self-assembling amyloid peptide biomaterial with sequence RGDSGAITIGC (1). According to analysis of the simulations, the GAITIG motif is at the core of the fibril and is the motif leading to self-assembly (1,6,7,10), the cell-adhesive motif RGD at the N-terminal end is flexible and adequately solvent exposed to promote cell-adhesion, and the cysteine residue at the C-terminal domain is not part of the amyloid peptide’s amyloid zipper region, thus providing the biomaterial with metal binding properties. Experiments confirmed the bifunctional properties of the designed self-assembling amyloid peptide biomaterial which can be exploited for tissue engineering applications.

In the second part of the study, we introduced a novel in-house computational design protocol, which innovatively combines biophysical and optimization principles, and aimed at further stabilizing and potentially functionalizing the aforementioned self-assembling biomaterial by computationally and experimentally investigating additional mutations at the C-terminal end of the peptide. The mutations suggested by the computational protocol were investigated using replica exchange MD simulations and free energy calculations, and preliminary results from simulations and experiments confirm that the introduction of a specific amino acid substitution leads to a cell-adhesive self-assembling amyloid peptide biomaterial with promising advanced mechanical properties which can be further exploited in future tissue engineering applications.

1. Deidda G, Jonnalagadda SVR, Spies JW, Ranella A, Mossou E, Forsyth VT, Mitchell EP, Mitraki A, Tamamis P (2016) Self-Assembled Amyloid Peptides with Arg-Gly-Asp (RGD) Motifs As Scaffolds for Tissue Engineering. ACS. Biomater. Sci. Eng. Article ASAP. DOI: 10.1021/acsbiomaterials.6b00570

2. Loo Y, Goktas M, Tekinay AB, Guler MO, Hauser CA, Mitraki A (2015) Self-Assembled Proteins and Peptides as Scaffolds for Tissue Regeneration. Adv. Healthc. Mater. 4(16):2557-86.

3. Terzaki K, Kalloudi E, Mossou E, Mitchell EP, Forsyth VT, Rosseeva E, Simon P, Vamvakaki M, Chatzinikolaidou M, Mitraki A, Farsari M (2013) Mineralized self-assembled peptides on 3D laser-made scaffolds: a new route toward 'scaffold on scaffold' hard tissue engineering. Biofabrication 5(4):045002.

4. Kasotakis E, Mossou E, Adler-Abramovich L, Mitchell EP, Forsyth VT, Gazit E, Mitraki A (2009) Design of metal-binding sites onto self-assembled peptide fibrils. Biopolymers 92(3):164-72.

5. Kasotakis E, Mitraki A (2012) Silica biotemplating by self-assembling peptides via serine residues activated by the peptide amino terminal group. Biopolymers 98(6):501−509.

6. Tamamis P, Kasotakis E, Mitraki A, 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.

7. 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.

8. Tamamis P, Terzaki K, Kassinopoulos M, Mastrogiannis L, Mossou E, Forsyth VT, Mitchell EP, 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.

9. Brooks BR, Brooks CL 3rd, Mackerell AD Jr, Nilsson L, Petrella RJ, Roux B, Won Y, Archontis G, Bartels C, Boresch S, Caflisch A, Caves L, Cui Q, Dinner AR, Feig M, Fischer S, Gao J, Hodoscek M, Im W, Kuczera K, Lazaridis T, Ma J, Ovchinnikov V, Paci E, Pastor RW, Post CB, Pu JZ, Schaefer M, Tidor B, Venable RM, Woodcock HL, Wu X, Yang W, York DM, Karplus M. (2009) CHARMM: the biomolecular simulation program. J Comput Chem 30(10):1545-614.

10. 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.