(323b) Data-Driven Design of Functional Amyloid Biomaterials

Authors: 
Tamamis, P., Texas A&M University
Jonnalagadda, S. V. R., Texas A&M University
He, S., Texas A&M University
Jakubowski, J. M., Texas A&M University
Orr, A. A., Texas A&M University
Lim, X. L., Texas A&M University
Mitraki, A., University of Crete
Gkikas, M., Massachusetts Institute of Technology
Kokotidou, C., University of Crete
The design of novel amyloid biomaterials with diverse structuresand functions is an upcoming field with future tremendous applications in biomedicine and biotechnology. However, the design of functional amyloid biomaterials with the capacity to bind to ions and compounds, or amyloid biomaterials with cell-attachment properties has been significantly limited until currently experiments primarily on researchers’ intuition on which mutations should be added to amyloids to transform them into functional biomaterials. During the last years, we have been developing the first computational protocol with the ability to transform amyloid peptide scaffolds into functional amyloid biomaterials. According to the protocol, suitable amyloid short peptide structures with non-β-sheet residue positions at the termini (referred to as amyloid designable scaffolds [1]) are transformed into functional amyloid biomaterials, by computationally designing these positions to bear a specific functionality. Specifically, the protocol searches in an optimization-based approach for combinations of modifications, which according to data analysis, can yield a desired functionality and which can produce energetically favorable solutions.

The talk will focus on the design of functional amyloid biomaterials binding to cesium ions, at which the designed amino acids were introduced to the amyloid designable scaffold to mimic how amino acids bind to cesium ions according to data analysis on experimentally resolved structures binding cesium ions [2]. As part of the protocol the optimum designs were computationally validated using a series of simulations and structural analysis to select the top designed peptides which were experimentally validated [2]. The talk will also present recent applications of the computational protocol in additional studies, emphasizing on how data-driven analysis can lead to the formation of functional amyloid biomaterials.

[1] Kokotidou, C.; Jonnalagadda, S. V. R.; Orr, A. A.; Seoane-Blanco, M.; Apostolidou, C. P.; van Raaij, M. J.; Kotzabasaki, M.; Chatzoudis, A.; Jakubowski, J. M.; Mossou, E.; Forsyth, V. T.; Mitchell, E. P.; Bowler, M. W.; Llamas-Saiz, A. L.; Tamamis, P.; Mitraki, A., A novel amyloid designable scaffold and potential inhibitor inspired by GAIIG of amyloid beta and the HIV-1 V3 loop. FEBS Letters 2018, 592 (11), 1777-1788.

[2] Jonnalagadda, S. V. R.; Kokotidou, C.; Orr, A. A.; Fotopoulou, E.; Henderson, K. J.; Choi, C.-H.; Lim, W. T.; Choi, S. J.; Jeong, H.-K.; Mitraki, A.; Tamamis, P., Computational Design of Functional Amyloid Materials with Cesium Binding, Deposition, and Capture Properties. The Journal of Physical Chemistry B 2018, 122 (30), 7555-7568.