(74i) Toward a Computational Protocol for the Design of Functional Amyloid Peptide Self-Assembling Materials

Tamamis, P., Texas A&M University
Jonnalagadda, S. V. R., Texas A&M University
Orr, A. A., Texas A&M University
Jakubowski, J. M., Texas A&M University
Henderson, K. J., Texas A&M University
Choi, C. H., Texas A&M University
Kokotidou, C., University of Crete
Mitraki, A., University of Crete
Jeong, H. K., Texas A & M University
Amyloid materials resulting from peptide self-assembly constitute the basis for the design of novel functional materials, with tremendous biomedical, technological and environmental applications. In previous studies we used computational tools to uncover the self-assembling structures of short peptides1,2,3,4 and in tandem with experiments, we designed novel functional materials5,6. Also, computational insights from our studies were used for the experimental design of novel amyloid materials7. Yet, until now, despite the successful experimental design of functional amyloid materials, experiments primarily rely on scientists’ intuition to transform amyloid scaffolds into functional amyloid materials. Thus, if the desired properties are hard to achieve, several peptide mutants need to be generated and tested experimentally, often with low success, making the procedure inefficient or nearly impossible, especially if multifunctional properties are desired. Here, we present - the first to our knowledge - computational protocol for the design of functional amyloid materials, which combines MD simulations, an innovative computational optimization-based design model, big data analysis and free energy calculations. We applied this protocol for the design of amyloid materials capturing cesium from water. According to experiments performed at Dr. Mitraki’s lab and Dr. Jeong’s lab, the newly designed amyloid materials have cesium deposition properties, can capture cesium in water and possess the capacity to capture cesium in acidic water conditions. The aforementioned protocol can be advanced into a generalized computational protocol for the design of novel amyloid materials binding other types of ions or compounds, leading to innovative functional materials of the future with a series of applications in biomedicine, energy and environment.


  1. Tamamis P, Adler-Abramovich L, Reches M, Marshall K, Sikorski P, Serpell L, Gazit E, Archontis G. Self-assembly of phenylalanine oligopeptides: insights from experiments and simulations. Biophys J. 2009, 96, 5020-9.
  2. Tamamis P, Kasotakis E, Mitraki A, Archontis G. Amyloid-like self-assembly of peptide sequences from the adenovirus fiber shaft: insights from molecular dynamics simulations. J Phys Chem B. 2009, 113, 15639-47.
  3. Tamamis P, Terzaki K, Kassinopoulos M, Mastrogiannis L, Mossou E, Forsyth VT, Mitchell EP, Mitraki A, Archontis G. Self-assembly of an aspartate-rich sequence from the adenovirus fiber shaft: insights from molecular dynamics simulations and experiments. J Phys Chem B. 2014, 118, 1765-74.
  4. Tamamis P, Kasotakis E, Archontis G, Mitraki A. Combination of theoretical and experimental approaches for the design and study of fibril-forming peptides. Methods Mol Biol. 2014, 1216, 53-70.
  5. Deidda G, Jonnalagadda SVR, Spies JW, Ranella A, Mossou E, Forsyth VT, Mitchell EP, Bowler MW, Tamamis P, Mitraki A. Self-assembled amyloid peptides with Arg-Gly-Asp (RGD) motifs as scaffolds for tissue engineering. ACS Biomater Sci Eng. 2017, 3, 1404–1416.
  6. Jonnalagadda SVR, Ornithopoulou E, Orr AA, Mossou E, Forsyth VT, Mitchell EP, Bowler MW, Mitraki A, Tamamis P. Computational design of amyloid self-assembling peptides bearing aromatic residues and the cell adhesive motif Arg-Gly-Asp. Syst. Des. Eng., 2017, 2, 321-335.
  7. Terzaki, K et al. Mineralized self-assembled peptides on 3D laser-made scaffolds: a new route toward 'scaffold on scaffold' hard tissue engineering. 2013, 5, 045002.