Abstract

FTIR spectroscopy has become a major tool to determine protein secondary structure. One of the identified obstacle for reaching better predictions is the strong overlap of bands assigned to different secondary structures. Yet, while for instance disordered structures and α-helical structures absorb almost at the same wavenumber, the absorbance bands are differentially shifted upon deuteration, in part because exchange is much faster for disordered structures. We recorded the FTIR spectra of 85 proteins at different stages of hydrogen/deuterium exchange process using protein microarrays and infrared imaging for high throughput measurements. Several methods were used to relate spectral shape to secondary structure content. While in absolute terms, β-sheet is always better predicted than α-helix content, results consistently indicate an improvement of secondary structure predictions essentially for the α-helix and the category called “Others” (grouping random, turns, bends, etc.) after 15 min of exchange. On the contrary, the β-sheet fraction is better predicted in non-deuterated conditions. Using partial least square regression, the error of prediction for the α-helix content is reduced after 15-min deuteration. Further deuteration degrades the prediction. Error on the prediction for the “Others” structures also decreases after 15-min deuteration. Cross-validation or a single 25-protein test set result in the same overall conclusions.

Highlights

  • Proteins are widely used as therapeutics in the biopharmaceutical industry and in food industry (Dimitrov 2012)

  • root mean square error in cross validation (RMSECV) values are reported for all structures

  • When comparing the different deuteration times, best estimation by Partial least square regression (PLS) and Support vector machine (SVM) are obtained at ­t15 for α-helix (RMSECV = 5.68–6.14%, respectively) and for “Others” (RMSECV = 7.13 and 7.05%). %)

Read more

Summary

Introduction

Proteins are widely used as therapeutics in the biopharmaceutical industry and in food industry (Dimitrov 2012). Their characterisation is an essential step in the development and quality control processes (Raynal et al 2014; Rogstad et al 2019). Quality is an essential parameter for drug approval by the FDA and other similar agencies. Proteins are prone to structural modification during production, storage and transport (shaking). Protein characterization is made arduous by their complexity, size and unstable 3D structure. This highlights the importance of monitoring and quickly

Methods
Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.