(131b) Rational Design of Peptide-Calcite Biomineralization Systems

Many organisms produce complex, hierarchically structured, inorganic materials via protein-influenced crystal growth?a process known as biomineralization. Understanding this process would shed light on hard tissue development and guide efforts to develop biomaterials. We created and tested a computational method to design protein-biomineralization systems. The algorithm folds a protein from a fully extended structure and simultaneously optimizes the fold, orientation, and sequence of the protein adsorbed to a crystal surface. We used the algorithm to design peptides (16 residues) to modify calcite (CaC03) crystallization. We chemically synthesized six peptides that were predicted to bind different states of the 001 growth plane of calcite. All six peptides dramatically affected calcite crystal growth (as observed by scanning electron microscopy), and the effects were dependent on the targeted state of the 001 growth plane. Additionally, we synthesized and assayed scrambled variants of all six designer peptides to distinguish cases where sequence composition determines the interactions versus cases where sequence order (and presumably structure) plays a role. Finally, to investigate energetic and structural aspects of these systems, we used a structure prediction algorithm to generate ensembles of all 12 peptides adsorbed to calcite. The adsorbed peptide structures give insight into the sequence specificity and molecular mechanisms by which the designed peptides control crystal growth.