Dataset Information

Characterization of surfaces presenting covalently immobilized oligopeptides using near-edge X-ray absorption fine structure spectroscopy.

ABSTRACT: This study addresses the need for methods that validate the surface chemistry leading to the immobilization of biomolecules and provide information about the resulting structural configurations. We report on the use of near-edge X-ray absorption fine structure spectroscopy (NEXAFS) to characterize a widely employed immobilization chemistry that leads to the covalent attachment of a biologically relevant oligopeptide to a surface. The oligopeptide used in this study is a kinase substrate of the epidermal growth factor receptor (EGFR), a protein that is a common target for cancer therapeutics. By observing changes in the pi* and sigma* orbitals of specific nitrogen and carbon atoms (amide, imide, carbonyl), we are able to follow the sequential reactions leading to immobilization of the oligopeptide. We also show that it is possible to use NEXAFS to extend this characterization method to submonolayer densities that are relevant to biological assays. Such an element-specific chemical characterization of small peptides on surfaces fills an unmet need and establishes NEXAFS as useful technique for characterizing the immobilization of small biomolecules on surfaces.

SUBMITTER: Bai Y

PROVIDER: S-EPMC2862363 | biostudies-literature | 2010 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Characterization of surfaces presenting covalently immobilized oligopeptides using near-edge X-ray absorption fine structure spectroscopy.

Bai Yiqun Y Liu Xiaosong X Cook Peter P Abbott Nicholas L NL Himpsel F J FJ

Langmuir : the ACS journal of surfaces and colloids 20100501 9

This study addresses the need for methods that validate the surface chemistry leading to the immobilization of biomolecules and provide information about the resulting structural configurations. We report on the use of near-edge X-ray absorption fine structure spectroscopy (NEXAFS) to characterize a widely employed immobilization chemistry that leads to the covalent attachment of a biologically relevant oligopeptide to a surface. The oligopeptide used in this study is a kinase substrate of the e ...[more]

PMID: 20387822

Similar Datasets

Project description:The toxicity and bioavailability of arsenic is heavily dependent on its speciation. Therefore, robust and accurate methods are needed to determine arsenic speciation profiles for materials related to public health initiatives, such as food safety. Here, X-ray spectroscopies are attractive candidates as they provide in situ, nondestructive analyses of solid samples without perturbation to the arsenic species therein. This work provides a speciation analysis for three certified reference materials for the food chemistry community, whose assigned values may be used to assess the merit of the X-ray spectroscopy results. Furthermore, extracts of SRM 3232 Kelp Powder, which is value-assigned for arsenic species, are measured to provide further evidence of its efficacy. These analyses are performed on the results of As K-edge X-ray Absorption Near Edge Structure (XANES) measurements collected on each sample. Notably, such analyses have traditionally relied on linear combination fitting of a minimal subset of empirical standards selected by stepwise regression. This is known to be problematic for compounds with meaningfully collinear spectra and can yield overestimates of the accuracy of the analysis. Therefore, the least absolute shrinkage and selection operator (lasso) regression method is used to reduce the risk of overfitting and increase the interpretability of statistical inferences. As this is a biased statistical method, results and uncertainties are estimated using a bootstrap method accounting for the dominant sources of variability. Finally, this method does not separate model and data selection from regression analysis. Indeed, a survey of many spectral influences is presented including changes in the: state of methylation, state of protonation, oxidation state, coordination geometry, and sample phase. These compounds were all included in the model’s training set, preventing model over-simplification and enabling high-throughput and robust analyses.

Dataset Information

Characterization of surfaces presenting covalently immobilized oligopeptides using near-edge X-ray absorption fine structure spectroscopy.

Publications

Characterization of surfaces presenting covalently immobilized oligopeptides using near-edge X-ray absorption fine structure spectroscopy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets