Discovering or designing biofunctionalized materials with improved quality highly depends on the ability to manipulate and control the peptide-inorganic interaction. Various peptides can be used as assemblers, synthesizers, and linkers in the material syntheses. In another context, specific and selective material-binding peptides can be used as recognition blocks in mining applications. In this study, we propose a new in silico method to select short 4-mer peptides with high affinity and selectivity for a given target material. This method is illustrated with the calcite (104) surface as an example, which has been experimentally validated. A calcite binding peptide can play an important role in our understanding of biomineralization. A practical aspect of calcite is a need for it to be selectively depressed in mining sites.
Keywords: computational modeling; organic-inorganic interaction; peptides; virtual library.
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