Paper AS-MoA7
Multitechnique Characterization of Protein G B1 Orientation on Surfaces

Monday, October 19, 2015, 4:20 pm, Room 212D

The orientation of adsorbed proteins on surfaces has been shown to influence biological responses, so research and development of biotechnological applications (e.g., sandwich ELISAs) have focused on controlling the orientation of each protein layer. However, characterizing protein orientation has been a challenge. The goal of this research is to address these challenges by developing methodology to study multilayer protein systems. Specifically, we aim to determine the orientation of protein G B1, an IgG antibody-binding domain of protein G, on various surfaces and the effect of its orientation on antibody binding using a variety of surface-sensitive tools and simulations. We propose that binding selectivity will increase for well-ordered protein films due to high availability of binding domains. To achieve control over surface properties, we have utilized four types of self-assembled monolayers (SAMs) to control protein orientation: N-Hydroxysuccinimide-terminated SAMs and dodecanethiol SAMs to immobilize protein G B1 in a random orientation and maleimide-terminated SAMs and bare gold to immobilize cysteine mutants of protein G B1 in a well-ordered orientation. Developing methods using surface-sensitive, label-free tools, such as XPS, ToF-SIMS, and quartz crystal microbalance with dissipation monitoring, provide detailed information of the adsorbed proteins, such as composition, coverage, and orientation. Additionally, computational methods to predict the orientation of proteins on surfaces can help to interpret and complement experimental techniques. In this work, we describe the development of a simulator to determine protein orientation on a surface using Monte Carlo (MC) simulations. We chose two proteins to test the MC simulator: LKα14 peptide and protein G B1. We chose LKα14, a 14-mer consisting of only leucine and lysine amino acid residues, as a benchmark because of its predictable structure and orientation on hydrophobic surfaces. To test the MC simulator on a more complex system, we used protein G B1. Preliminary MC simulations show that protein G B1 is likely to interact with a graphene surface through residues Met1, Val21, Ala48, and the hydrophobic part of Lys10 on terminal ends of the protein. We will extend the MC algorithm to predict the orientation of additional protein/surface combinations and validate using experimental results. While the systems explored thus far are model systems that are far less complex compared to biological systems of the real world, we aim to develop methodology using state-of-the-art tools that can be continuously improved to help expand our knowledge of, and possibly control, biomolecules on surfaces.