Theory and simulations of designable modular bionic proteins

Self-assembling is the process by which a substance spontaneously reaches a specific long-lived configuration with a well-defined structure. Such structures may be highly inhomogeneous but still strongly differ from random amorphous materials, which are typically dynamically arrested. In fact by having an easily accessible ground state, self-assembling materials have the property of forming structures characterized by few defects, and they often have the capacity to adapt to changes in the environment. The large number of potential applications makes self- assembling a most researched feature in material science. Both theoretically and experimentally, creating a material that spontaneously assembles into an arbitrary target structure is a challenging task, as most chemical substances have the propensity to form either highly ordered structures (crystals) or disordered and arrested structures. This research project aims at defining a novel theoretical framework within which we will be able to design new experimentally realizable materials with tunable self-assembling properties. Final aims of this project are the identification of an optimal set of modular sub-units, and the definition of a design procedure necessary to choose a string of the units that once bonded into a chain will spontaneously collapse to a specific target structure. Subsequently, the collapsed chains will themselves self-assemble into complex super structures, again controlled by the same sequence selection criterion. In order to produce realistic and experimentally realizable sub-units particles, we have already established a collaboration with the group of Prof. Erik Reimhult at the BOKU University in Vienna, who is an expert in the synthesis and manipulation of nano-particles. The main objective of the project is to transfer what we learned for proteins, with our recently developed caterpillar protein model, to the system of artificial chains made of selected particles. During a second phase we will extend the focus of our study to the dynamical properties of the self-assembling process. This project will represent a considerable step forward in the synthesis of novel materials, because it will be based on a limited alphabet of particles that can be reused and assembled, practically, in an infinite number of combinations. Artificial modular self-assembling systems are not available at the moment and the one we propose will be the first of this kind. Direct comparison with experiments will evolve towards a very high impact research, as it will represent an important step towards possible applications of designed artificial materials such as smart materials, that active respond to the environment, catalysis, optronics (photo-voltaic materials), or even three-dimensional electronics that exploits three-dimensional connectivity extending the possibilities of modern electronics based on surface lithography.

Self-assembling is the process by which a substance spontaneously reaches a specific long- lived configuration with a well-defined structure. Such structures may be highly inhomogeneous but still strongly differ from random amorphous materials, which are typically dynamically arrested. In fact by having an easily accessible ground state, self-assembling materials have the property of forming structures characterized by few defects, and they often have the capacity to adapt to changes in the environment. The large number of potential applications makes self-assembling a most researched feature in material science. Both theoretically and experimentally, creating a material that spontaneously assembles into an arbitrary target structure is a challenging task, as most chemical substances have the propensity to form either highly ordered structures (crystals) or disordered and arrested structures. Using computer simulations, we reverse engineered proteins by focusing on the key elements that give them the ability to execute the program written in the genetic code. As a result of our research we have unlocked the key for general heteropolymer design. We have successfully defined the first completely artificial protein heteropolymer that we defined as Bionic Proteins. The folding precision of Bionic Proteins is so high that our artificial bio- mimetic model system are capable of spontaneously self-knotting into a complex topologies. Finally, we have connected our research to bio-polymer demonstrating that our results are universal for both artificial and natural systems. Our results represent a considerable step forward in the synthesis of novel materials, because it will be based on a limited alphabet of particles that can be reused and assembled, practically, in an infinite number of combinations. Artificial modular self-assembling systems are not available at the moment and the one we propose will be the first of this kind. Direct comparison with experiments will evolve towards a very high impact research, as it will represent an important step towards possible applications of designed artificial materials such as smart materials, that active respond to the environment, catalysis, optronics (photo-voltaic materials), or even three- dimensional electronics that exploits three-dimensional connectivity extending the possibilities of modern electronics based on surface lithography.