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Facilitating the structural characterisation of non-canonical amino acids in biomolecular NMR.
- Source :
- Magnetic Resonance; 2023, Vol. 4 Issue 1, p57-72, 16p
- Publication Year :
- 2023
-
Abstract
- 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 26990016
- Volume :
- 4
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Magnetic Resonance
- Publication Type :
- Academic Journal
- Accession number :
- 170404787
- Full Text :
- https://doi.org/10.5194/mr-4-57-2023