Aalto University: Ascending Investigator Grant from Novo Nordisk Foundation awarded to Maria Sammalkorpi for computational biosynthetic materials research

The Ascending Investigator Grants are part of Novo Nordisk Foundation’s Research Leader Programme that provides proven research leaders the opportunity to pursue ambitious and innovative projects and strengthen their research groups. The five-year duration and the substantial research resources by the grant allow focusing on major research challenges that bear significant advancement potential in the field.

Sammalkorpi uses computational modelling to design self-organizing synthetic protein materials with advanced materials properties and functionalities. While living cells readily produce biological protein structural materials with fascinating and versatile properties, as evident when comparing e.g. silk fibers, reptilian scales and shells, squid beaks, or epidermal skin or leather, achieving advanced properties in biosynthetic materials remains a challenge. Even more fascinating is when synthetic materials obtain characteristics of living systems. Examples include animate materials with dynamic structural reorganization, programmable assembly, and adaptation of the material to environment.

Sammalkorpi’s project uses computational means, connected with related experimental characterization, to design proteins, map materials assembly conditions, and resolve protein-assembly condition dependencies, that lead to desired properties and response in biosynthetic materials.

“Computational modelling offers a largely untapped potential in advancing biosynthetic materials. We model the proteins and their interactions aiming at capturing e.g., the influence of chemical gradients, mass flows, and external fields on the materials formation in biosynthetic protein materials. Such non-equilibrium assembly conditions in living cells give rise to materials with advanced functionalities”, says Maria Sammalkorpi.


An illustration of biosynthetic protein materials
Biosynthetic protein materials can be modelled computationally at multiple different length scales. Examples shown for coarse-grained bead and atomistic detail modelling of the same silk-like protein forming assemblies in water solution.
Simulation visualizations in the picture above: Alberto Scacchi and Piotr Batys, Soft Materials Modelling Group, Aalto University.

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