Preferential Binding of Cytochrome c to Anionic Ligand-Coated Gold Nanoparticles: A Complementary Computational and Experimental Approach

• Published in: ACS nano 2019-06, Vol.13 (6), p.6856-6866
• Main Authors: Tollefson, Emily J, Allen, Caley R, Chong, Gene, Zhang, Xi, Rozanov, Nikita D, Bautista, Anthony, Cerda, Jennifer J, Pedersen, Joel A, Murphy, Catherine J, Carlson, Erin E, Hernandez, Rigoberto
• Format: Article
• Language: English
• ISSN: 1936-0851; 1936-086X
• DOI: 10.1021/acsnano.9b01622

Membrane-bound proteins can play a role in the binding of anionic gold nanoparticles (AuNPs) to model bilayers; however, the mechanism for this binding remains unresolved. In this work, we determine the relative orientation of the peripheral membrane protein cytochrome c in binding to a mercaptopropionic acid-functionalized AuNP (MPA-AuNP). As this is nonrigid binding, traditional methods involving crystallographic or rigid molecular docking techniques are ineffective at resolving the question. Instead, we have implemented a computational assay technique using a cross-correlation of a small ensemble of 200 ns long molecular dynamics trajectories to identify a preferred nonrigid binding orientation or pose of cytochrome c on MPA-AuNPs. We have also employed a mass spectrometry-based footprinting method that enables the characterization of the stable protein corona that forms at long time-scales in solution but remains in a dynamic state. Through the combination of these computational and experimental primary results, we have established a consensus result establishing the identity of the exposed regions of cytochrome c in proximity to MPA-AuNPs and its complementary pose(s) with amino-acid specificity. Moreover, the tandem use of the two methods can be applied broadly to determine the accessibility of membrane-binding sites for peripheral membrane proteins upon adsorption to AuNPs or to determine the exposed amino-acid residues of the hard corona that drive the acquisition of dynamic soft coronas. We anticipate that the combined use of simulation and experimental methods to characterize biomolecule–nanoparticle interactions, as demonstrated here, will become increasingly necessary as the complexity of such target systems grows.