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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. [ABSTRACT FROM AUTHOR]

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 (atb.uq.edu.au) with all submitted ncAAs stored in a dedicated database. The described procedure also includes a general method for linking of sidechains 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 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]

α‐Helical membrane‐active antimicrobial peptides (AMPs) are known to act via a range of mechanisms, including the formation of barrel‐stave and toroidal pores and the micellisation of the membrane (carpet mechanism). Different mechanisms imply that the peptides adopt different 3D structures when bound at the water–membrane interface, a highly amphipathic environment. Here, an evolutionary algorithm is used to predict the 3D structure of a range of α‐helical membrane‐active AMPs at the water–membrane interface by optimising amphipathicity. This amphipathic structure prediction (ASP) is capable of distinguishing between curved and linear peptides solved experimentally, potentially allowing the activity and mechanism of action of different membrane‐active AMPs to be predicted. The ASP algorithm is accessible via a web interface at http://atb.uq.edu.au/asp/. [ABSTRACT FROM AUTHOR]

α-Helical membrane-active antimicrobial peptides (AMPs) are known to act via a range of mechanisms, including the formation of barrel-stave and toroidal pores and the micellisation of the membrane (carpet mechanism). Different mechanisms imply that the peptides adopt different 3D structures when bound at the water-membrane interface, a highly amphipathic environment. Here, an evolutionary algorithm is used to predict the 3D structure of a range of α-helical membrane-active AMPs at the water-membrane interface by optimising amphipathicity. This amphipathic structure prediction (ASP) is capable of distinguishing between curved and linear peptides solved experimentally, potentially allowing the activity and mechanism of action of different membrane-active AMPs to be predicted. The ASP algorithm is accessible via a web interface at http://atb.uq.edu.au/asp/., (© 2019 Federation of European Biochemical Societies.)