Understanding the orientation of proteins on material surfaces is of crucial importance for the design of material surfaces with applications in biotechnology. However, the determination of protein orientation at atomic level of detail remains a challenge. Various surface analysis techniques, like flight secondary ion mass spectrometry, sum frequency generation vibrational spectrometry and near-edge X-ray absorption fine structure, have been developed to probe the orientation of proteins adsorbed onto surfaces. However, the spectra generated by this type of experiments can be very complex and extrapolating a result can be difficult if not impossible without suitable post-processing software. In this project, software tools are developed which make use of available three-dimensional structures of proteins to predict the spectrum that would be measured given a particular orientation of the protein on a surface. Furthermore, a publicly accessible online server will be setup which, using Monte Carlo simulations, will predict the orientation of a protei uploaded by a user on a selected surface. The Monte Carlo search can be guided by including available experimental data in order to refine a model suggested by the experiments or discriminate the most likely orientation when contradicting models are suggested by different techniques. If no experimental data is present, the server will provide an estimate of the protein orientation that can be either used to generate hypotheses or as the starting conformation for more complex calculations of the protein-surface interaction.
Determining how proteins are oriented on surfaces at atomic level of detail is challenging. Software tools for the interpretation of surface analysis data and n online prediction server will be created in this project in order to improve the determination of the protein orientation on material surfaces. Improving the understanding of how proteins are oriented is crucial for the design of biotechnological applications involving protein films.
|Foster, Rami N; Harrison, Elisa T; Castner, David G (2016) ToF-SIMS and XPS Characterization of Protein Films Adsorbed onto Bare and Sodium Styrenesulfonate-Grafted Gold Substrates. Langmuir 32:3207-16|