Genetically engineered gold-binding polypeptides: structure prediction and molecular dynamics
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Updated: Sep 29, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
Published on: January 26, 2024
Rosemary Braun1, Mehmet Sarikaya, Klaus Schulten
1Beckman Institute and Department of Physics, University of Illinois, Urbana 61801, USA.
Abstract:
The biological control of inorganic crystal formation, morphology, and assembly is of interest to biologists and biotechnologists studying hard tissue growth and regeneration, as well as to materials scientists using biomimetic approaches for the control of inorganic material fabrication and assembly. Biomimetics requires an accurate understanding of natural mechanisms at the molecular level. Such understanding can be derived from the use of metal surfaces to study surface recognition by proteins together with combinatorial genetics techniques for the selection of suitable peptides. Polymerization of these peptides produces engineered polypeptides large enough to encode their own folding information with low structural complexity, while enhancing binding affinity to surfaces. The low complexity of such polypeptides can aid in analyses, leading to modeling and eventual manipulation of the structure of the folded polypeptide. This paper presents structure predictions for gold-binding protein sequences, originally selected by combinatorial techniques. Molecular dynamics simulations lasting 5 ns were carried out using solvated polypeptides at the gold surface to assess the dynamics of the binding process and the effects of surface topography on the specificity of protein binding.
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