Facilitating the structural characterisation of non-canonical amino acids in biomolecular NMR

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Peptides and proteins containing non-canonical amino acids (ncAAs) are a large and important class of biopolymers. They include non-ribosomally synthesised peptides, post-translationally modified proteins, expressed or synthesised proteins containing unnatural amino acids, and peptides and proteins that are chemically modified. Here, we describe a general procedure for generating atomic descriptions required to incorporate ncAAs within popular NMR structure determination software such as CYANA, CNS, Xplor-NIH and ARIA. This procedure is made publicly available via the existing Automated Topology Builder (ATB) server (https://atb.uq.edu.au, last access: 17 February 2023) with all submitted ncAAs stored in a dedicated database. The described procedure also includes a general method for linking of side chains of amino acids from CYANA templates. To ensure compatibility with other systems, atom names comply with IUPAC guidelines. In addition to describing the workflow, 3D models of complex natural products generated by CYANA are presented, including vancomycin. In order to demonstrate the manner in which the templates for ncAAs generated by the ATB can be used in practice, we use a combination of CYANA and CNS to solve the structure of a synthetic peptide designed to disrupt Alzheimer-related protein-protein interactions. Automating the generation of structural templates for ncAAs will extend the utility of NMR spectroscopy to studies of more complex biomolecules, with applications in the rapidly growing fields of synthetic biology and chemical biology. The procedures we outline can also be used to standardise the creation of structural templates for any amino acid and thus have the potential to impact structural biology more generally.

Original languageEnglish
JournalMagnetic Resonance
Volume4
Issue number1
Pages (from-to)57-72
ISSN2699-0059
DOIs
Publication statusPublished - 2023

Bibliographical note

Funding Information:
This research has been supported by the Australian Research Council (grant nos. DP190101177, DP220103028, and DP220100896), the Australian National Health and Medical Research Council (grant no. APP1162597 to Mehdi Mobli), and the Austrian Science Fund (FWF) (grant no. P36101-B to Anne Claire Conibear).

Funding Information:
This project was supported by The University of Queensland (Postgraduate Research Scholarship to Sarah Kuschert, Research Stimulus fellowship to Yanni Ka-Yan Chin and Development Fellowship to Mehdi Mobli).

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