Pinto Corujo, Marco, Olamoyesan, Adewale, Tukova, Anastasiia, Ang, Dale, Goormaghtigh, Erik, Peterson, Jason, Sharov, Victor, Chmel, Nikola Paul and Rodger, Alison (2022) SOMSpec as a general purpose validated self-organising map tool for rapid protein secondary structure prediction from infrared absorbance data. Frontiers in Chemistry, 9 . 784625. doi:10.3389/fchem.2021.784625

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Abstract

A protein’s structure is the key to its function. As protein structure can vary with environment, it is important to be able to determine it over a wide range of concentrations, temperatures, formulation vehicles, and states. Robust reproducible validated methods are required for applications including batch-batch comparisons of biopharmaceutical products. Circular dichroism is widely used for this purpose, but an alternative is required for concentrations above 10 mg/mL or for solutions with chiral buffer components that absorb far UV light. Infrared (IR) protein absorbance spectra of the Amide I region (1,600–1700 cm−1) contain information about secondary structure and require higher concentrations than circular dichroism often with complementary spectral windows. In this paper, we consider a number of approaches to extract structural information from a protein infrared spectrum and determine their reliability for regulatory and research purpose. In particular, we compare direct and second derivative band-fitting with a self-organising map (SOM) approach applied to a number of different reference sets. The self-organising map (SOM) approach proved significantly more accurate than the band-fitting approaches for solution spectra. As there is no validated benchmark method available for infrared structure fitting, SOMSpec was implemented in a leave-one-out validation (LOOV) approach for solid-state transmission and thin-film attenuated total reflectance (ATR) reference sets. We then tested SOMSpec and the thin-film ATR reference set against 68 solution spectra and found the average prediction error for helix (α + 310) and β-sheet was less than 6% for proteins with less than 40% helix. This is quantitatively better than other available approaches. The visual output format of SOMSpec aids identification of poor predictions. We also demonstrated how to convert aqueous ATR spectra to and from transmission spectra for structure fitting. Fourier self-deconvolution did not improve the average structure predictions.

Item Type:	Journal Article
Subjects:	Q Science > QC Physics Q Science > QD Chemistry
Divisions:	Faculty of Science, Engineering and Medicine > Science > Chemistry
SWORD Depositor:	Library Publications Router
Library of Congress Subject Headings (LCSH):	Proteins -- Structure -- Research, Absorption spectra, Infrared spectra, Self-organizing maps
Journal or Publication Title:	Frontiers in Chemistry
Publisher:	Frontiers Research Foundation
ISSN:	2296-2646
Official Date:	27 January 2022
Dates:	Date Event 27 January 2022 Published 6 December 2021 Accepted
Volume:	9
Article Number:	784625
DOI:	10.3389/fchem.2021.784625
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access
RIOXX Funder/Project Grant:	Project/Grant ID RIOXX Funder Name Funder ID EP/L015307/1 [EPSRC] Engineering and Physical Sciences Research Council http://dx.doi.org/10.13039/501100000266 European Marie Curie Initial Training Network scheme European Commission http://dx.doi.org/10.13039/501100000780 Research Excellence Scholarship Macquarie University http://dx.doi.org/10.13039/501100001230

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