Nanoparticles have become increasingly useful in the fields of drug delivery and biosensing. In these applications, nanoparticles are frequently exposed to biological fluids, where proteins will spontaneously adsorb to the nanoparticle surface when exposed to a mixture of proteins. This project aims to present a predictive host-guest system for quantifying each residue’s contribution to nanoparticle binding. Initial studies revealed that lysine at position 13 plays a crucial role in the adsorption of GB3 to 15 nm citrate-coated spherical gold nanoparticles (AuNPs). Therefore, we have constructed a library of K13X GB3 variants, and our initial findings confirm that basic residues (Arg) interact more favorably with AuNPs than other polar (Asn) and acidic side (Glu) chains, and a rank-ordering of side-chain affinity for AuNP surfaces could be inferred in further studies. A simple mechanism can be used to interpret these rankings with respect to thermodynamic vs. kinetic control in future studies.