(735c) Investigating the Role of Phosphorylation and pH in Peptide Binding to Silica

Biosilicification – the process by which diatoms and sponges grow ornate silica exoskeletons – is thought to occur through the self-assembly of peptides into a matrix, followed by the condensation of silicic acid to form silica nanostructures. Thus, many stages of this process are likely governed by complex interfacial interactions, which, in addition to the conditions permitting biosilicification to take place, have been generally poorly understood until now. This talk will highlight recently published work [1] that employed the advanced sampling simulation technique PTMetaD-WTE [2] to uncover dominant driving forces behind the precipitation of silica and the formation of nanostructures in the biosilicification process. The effects of peptide sequence phosphorylation and pH – both thought to play large roles in multiple stages of the process – on peptide/silica binding are discussed in detail. Our results show the peptide/silica interaction strength decreases with decreasing pH and an increasing degree of phosphorylation. These differences can be attributed to alterations in intramolecular hydrogen-bonding and in peptide/surface electrostatic interactions at the different pH conditions studied, providing a new hypothesis as to why silica is precipitated at a different pH in a lab versus natural setting. Our predictions also shed light on other important features such as the role of the C-terminal motif, the interaction of phosphorylated residues with the peptide/silica environment, and the facilitation of peptide−surface binding through surface-bound ions. Ultimately, this work has implications for future design of novel silica-based biomaterials/biotechnologies with highly tailorable properties/morphologies for a variety of applications.

References

[1] Sprenger, K.G.; Prakash, A.; Drobny, G.; Pfaendtner, J. Investigating the Role of Phosphorylation in the Binding of Silaffin Peptide R5 to Silica with Molecular Dynamics Simulations. Langmuir 2018, 34, 1199-1207.

[2] Deighan, M.; Bonomi, M.; Pfaendtner, J. Efficient Simulation of Explicitly Solvated Proteins in the Well-Tempered Ensemble. JCTC 2012, 8, 2189-2192.