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      Efficient rational modification of non-ribosomal peptides by adenylation domain substitution

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          Abstract

          Non-ribosomal peptide synthetase (NRPS) enzymes form modular assembly-lines, wherein each module governs the incorporation of a specific monomer into a short peptide product. Modules are comprised of one or more key domains, including adenylation (A) domains, which recognise and activate the monomer substrate; condensation (C) domains, which catalyse amide bond formation; and thiolation (T) domains, which shuttle reaction intermediates between catalytic domains. This arrangement offers prospects for rational peptide modification via substitution of substrate-specifying domains. For over 20 years, it has been considered that C domains play key roles in proof-reading the substrate; a presumption that has greatly complicated rational NRPS redesign. Here we present evidence from both directed and natural evolution studies that any substrate-specifying role for C domains is likely to be the exception rather than the rule, and that novel non-ribosomal peptides can be generated by substitution of A domains alone. We identify permissive A domain recombination boundaries and show that these allow us to efficiently generate modified pyoverdine peptides at high yields. We further demonstrate the transferability of our approach in the PheATE-ProCAT model system originally used to infer C domain substrate specificity, generating modified dipeptide products at yields that are inconsistent with the prevailing dogma.

          Abstract

          Non-ribosomal peptide synthases are multimodular enzymes comprised of adenylation (A), condensation (C) and thiolation domains. Here, the authors show that non-ribosomal peptides can be generated solely by A domain substitutions, providing evidence that the postulated substrate specifying role of C-domains may be rare in nature.

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          Most cited references59

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          QMEAN: A comprehensive scoring function for model quality assessment.

          In protein structure prediction, a considerable number of alternative models are usually produced from which subsequently the final model has to be selected. Thus, a scoring function for the identification of the best model within an ensemble of alternative models is a key component of most protein structure prediction pipelines. QMEAN, which stands for Qualitative Model Energy ANalysis, is a composite scoring function describing the major geometrical aspects of protein structures. Five different structural descriptors are used. The local geometry is analyzed by a new kind of torsion angle potential over three consecutive amino acids. A secondary structure-specific distance-dependent pairwise residue-level potential is used to assess long-range interactions. A solvation potential describes the burial status of the residues. Two simple terms describing the agreement of predicted and calculated secondary structure and solvent accessibility, respectively, are also included. A variety of different implementations are investigated and several approaches to combine and optimize them are discussed. QMEAN was tested on several standard decoy sets including a molecular dynamics simulation decoy set as well as on a comprehensive data set of totally 22,420 models from server predictions for the 95 targets of CASP7. In a comparison to five well-established model quality assessment programs, QMEAN shows a statistically significant improvement over nearly all quality measures describing the ability of the scoring function to identify the native structure and to discriminate good from bad models. The three-residue torsion angle potential turned out to be very effective in recognizing the native fold. (c) 2007 Wiley-Liss, Inc.
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            FUGUE: sequence-structure homology recognition using environment-specific substitution tables and structure-dependent gap penalties.

            FUGUE, a program for recognizing distant homologues by sequence-structure comparison (http://www-cryst.bioc.cam.ac.uk/fugue/), has three key features. (1) Improved environment-specific substitution tables. Substitutions of an amino acid in a protein structure are constrained by its local structural environment, which can be defined in terms of secondary structure, solvent accessibility, and hydrogen bonding status. The environment-specific substitution tables have been derived from structural alignments in the HOMSTRAD database (http://www-cryst.bioc. cam.ac.uk/homstrad/). (2) Automatic selection of alignment algorithm with detailed structure-dependent gap penalties. FUGUE uses the global-local algorithm to align a sequence-structure pair when they greatly differ in length and uses the global algorithm in other cases. The gap penalty at each position of the structure is determined according to its solvent accessibility, its position relative to the secondary structure elements (SSEs) and the conservation of the SSEs. (3) Combined information from both multiple sequences and multiple structures. FUGUE is designed to align multiple sequences against multiple structures to enrich the conservation/variation information. We demonstrate that the combination of these three key features implemented in FUGUE improves both homology recognition performance and alignment accuracy. Copyright 2001 Academic Press.
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              Nonribosomal Peptide Synthesis-Principles and Prospects

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                Author and article information

                Contributors
                david.ackerley@vuw.ac.nz
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                11 September 2020
                11 September 2020
                2020
                : 11
                : 4554
                Affiliations
                [1 ]GRID grid.267827.e, ISNI 0000 0001 2292 3111, School of Biological Sciences, , Victoria University of Wellington, ; Wellington, New Zealand
                [2 ]GRID grid.267827.e, ISNI 0000 0001 2292 3111, Centre for Biodiscovery and Maurice Wilkins Centre for Molecular Biodiscovery, , Victoria University of Wellington, ; Wellington, New Zealand
                Author information
                http://orcid.org/0000-0002-7736-8095
                http://orcid.org/0000-0002-6188-9902
                Article
                18365
                10.1038/s41467-020-18365-0
                7486941
                32917865
                379690f3-8043-4fd8-bd0b-21a859261b0d
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 5 June 2020
                : 19 August 2020
                Funding
                Funded by: Royal Society of New Zealand Marsden Fund (grant 18-VUW-082)
                Funded by: FundRef https://doi.org/10.13039/501100001505, Manatu Hauora | Health Research Council of New Zealand (HRC);
                Award ID: 16/172
                Award ID: 16/172
                Award Recipient :
                Funded by: Royal Society of New Zealand Marsden Fund (grant 09-VUW-01)
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                multienzyme complexes,synthetic biology
                Uncategorized
                multienzyme complexes, synthetic biology

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