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Pelton JM, Hochuli JE, Sadecki PW, Katoh T, Suga H, Hicks LM, Muratov EN, Tropsha A, Bowers AA. Cheminformatics-Guided Cell-Free Exploration of Peptide Natural Products. J Am Chem Soc 2024; 146:8016-8030. [PMID: 38470819 DOI: 10.1021/jacs.3c11306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/14/2024]
Abstract
There have been significant advances in the flexibility and power of in vitro cell-free translation systems. The increasing ability to incorporate noncanonical amino acids and complement translation with recombinant enzymes has enabled cell-free production of peptide-based natural products (NPs) and NP-like molecules. We anticipate that many more such compounds and analogs might be accessed in this way. To assess the peptide NP space that is directly accessible to current cell-free technologies, we developed a peptide parsing algorithm that breaks down peptide NPs into building blocks based on ribosomal translation logic. Using the resultant data set, we broadly analyze the biophysical properties of these privileged compounds and perform a retrobiosynthetic analysis to predict which peptide NPs could be directly synthesized in augmented cell-free translation reactions. We then tested these predictions by preparing a library of highly modified peptide NPs. Two macrocyclases, PatG and PCY1, were used to effect the head-to-tail macrocyclization of candidate NPs. This retrobiosynthetic analysis identified a collection of high-priority building blocks that are enriched throughout peptide NPs, yet they had not previously been tested in cell-free translation. To expand the cell-free toolbox into this space, we established, optimized, and characterized the flexizyme-enabled ribosomal incorporation of piperazic acids. Overall, these results demonstrate the feasibility of cell-free translation for peptide NP total synthesis while expanding the limits of the technology. This work provides a novel computational tool for exploration of peptide NP chemical space, that could be expanded in the future to allow design of ribosomal biosynthetic pathways for NPs and NP-like molecules.
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Affiliation(s)
- Jarrett M Pelton
- Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Joshua E Hochuli
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Patric W Sadecki
- Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Takayuki Katoh
- Department of Chemistry, Graduate School of Science, The University of Tokyo, Tokyo, 113-0033, Japan
| | - Hiroaki Suga
- Department of Chemistry, Graduate School of Science, The University of Tokyo, Tokyo, 113-0033, Japan
| | - Leslie M Hicks
- Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Eugene N Muratov
- Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Alexander Tropsha
- Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Albert A Bowers
- Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
- Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
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2
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Hellinger R, Sigurdsson A, Wu W, Romanova EV, Li L, Sweedler JV, Süssmuth RD, Gruber CW. Peptidomics. Nat Rev Methods Primers 2023; 3:25. [PMID: 37250919 PMCID: PMC7614574 DOI: 10.1038/s43586-023-00205-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/09/2023] [Indexed: 05/31/2023]
Abstract
Peptides are biopolymers, typically consisting of 2-50 amino acids. They are biologically produced by the cellular ribosomal machinery or by non-ribosomal enzymes and, sometimes, other dedicated ligases. Peptides are arranged as linear chains or cycles, and include post-translational modifications, unusual amino acids and stabilizing motifs. Their structure and molecular size render them a unique chemical space, between small molecules and larger proteins. Peptides have important physiological functions as intrinsic signalling molecules, such as neuropeptides and peptide hormones, for cellular or interspecies communication, as toxins to catch prey or as defence molecules to fend off enemies and microorganisms. Clinically, they are gaining popularity as biomarkers or innovative therapeutics; to date there are more than 60 peptide drugs approved and more than 150 in clinical development. The emerging field of peptidomics comprises the comprehensive qualitative and quantitative analysis of the suite of peptides in a biological sample (endogenously produced, or exogenously administered as drugs). Peptidomics employs techniques of genomics, modern proteomics, state-of-the-art analytical chemistry and innovative computational biology, with a specialized set of tools. The complex biological matrices and often low abundance of analytes typically examined in peptidomics experiments require optimized sample preparation and isolation, including in silico analysis. This Primer covers the combination of techniques and workflows needed for peptide discovery and characterization and provides an overview of various biological and clinical applications of peptidomics.
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Affiliation(s)
- Roland Hellinger
- Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Arnar Sigurdsson
- Institut für Chemie, Technische Universität Berlin, Berlin, Germany
| | - Wenxin Wu
- School of Pharmacy and Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Elena V Romanova
- Department of Chemistry, University of Illinois, Urbana, IL, USA
| | - Lingjun Li
- School of Pharmacy and Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | | | | | - Christian W Gruber
- Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
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3
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Flissi A, Duban M, Jacques P, Leclère V, Pupin M. Norine: Bioinformatics Methods and Tools for the Characterization of Newly Discovered Nonribosomal Peptides. Methods Mol Biol 2023; 2670:303-318. [PMID: 37184712 DOI: 10.1007/978-1-0716-3214-7_16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
In this chapter, we present Norine ( https://norine.univ-lille.fr/norine ), the unique resource dedicated to nonribosomal peptides. First, the content of the knowledgebase and the related tools are described. Then, a study case shows how to query Norine by annotations or structure and how to interpret the obtained results.
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Affiliation(s)
- Areski Flissi
- Université de Lille, CNRS, Centrale Lille, UMR 9189 CRIStAL, Lille, France.
| | - Matthieu Duban
- Université de Lille, UMRt BioEcoAgro 1158-INRAe, Métabolites secondaires d'origine microbienne, Charles Viollette Institute, Lille, France
| | - Philippe Jacques
- Université de Liège, UMRt BioEcoAgro 1158-INRAe, Métabolites secondaires d'origine microbienne, TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, Gembloux, Belgium
| | - Valérie Leclère
- Université de Lille, UMRt BioEcoAgro 1158-INRAe, Métabolites secondaires d'origine microbienne, Charles Viollette Institute, Lille, France
| | - Maude Pupin
- Université de Lille, CNRS, Centrale Lille, UMR 9189 CRIStAL, Lille, France
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4
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Konanov DN, Krivonos DV, Ilina EN, Babenko VV. BioCAT: search for biosynthetic gene clusters producing nonribosomal peptides with known structure. Comput Struct Biotechnol J 2022; 20:1218-1226. [PMID: 35317229 PMCID: PMC8914306 DOI: 10.1016/j.csbj.2022.02.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 02/14/2022] [Accepted: 02/14/2022] [Indexed: 11/28/2022] Open
Affiliation(s)
- Dmitry N. Konanov
- Federal Research and Clinical Centre of Physical and Chemical Medicine, Federal Medical and Biological Agency of Russia, ul. Malaya Pirogovskaya., 1s3, Moscow 119435, Russian Federation
- Corresponding author.
| | - Danil V. Krivonos
- Federal Research and Clinical Centre of Physical and Chemical Medicine, Federal Medical and Biological Agency of Russia, ul. Malaya Pirogovskaya., 1s3, Moscow 119435, Russian Federation
| | - Elena N. Ilina
- Federal Research and Clinical Centre of Physical and Chemical Medicine, Federal Medical and Biological Agency of Russia, ul. Malaya Pirogovskaya., 1s3, Moscow 119435, Russian Federation
| | - Vladislav V. Babenko
- Federal Research and Clinical Centre of Physical and Chemical Medicine, Federal Medical and Biological Agency of Russia, ul. Malaya Pirogovskaya., 1s3, Moscow 119435, Russian Federation
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Kunyavskaya O, Tagirdzhanov AM, Caraballo-Rodríguez AM, Nothias LF, Dorrestein PC, Korobeynikov A, Mohimani H, Gurevich A. Nerpa: A Tool for Discovering Biosynthetic Gene Clusters of Bacterial Nonribosomal Peptides. Metabolites 2021; 11:693. [PMID: 34677408 DOI: 10.3390/metabo11100693] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 10/01/2021] [Accepted: 10/01/2021] [Indexed: 11/16/2022] Open
Abstract
Microbial natural products are a major source of bioactive compounds for drug discovery. Among these molecules, nonribosomal peptides (NRPs) represent a diverse class of natural products that include antibiotics, immunosuppressants, and anticancer agents. Recent breakthroughs in natural product discovery have revealed the chemical structure of several thousand NRPs. However, biosynthetic gene clusters (BGCs) encoding them are known only for a few hundred compounds. Here, we developed Nerpa, a computational method for the high-throughput discovery of novel BGCs responsible for producing known NRPs. After searching 13,399 representative bacterial genomes from the RefSeq repository against 8368 known NRPs, Nerpa linked 117 BGCs to their products. We further experimentally validated the predicted BGC of ngercheumicin from Photobacterium galatheae via mass spectrometry. Nerpa supports searching new genomes against thousands of known NRP structures, and novel molecular structures against tens of thousands of bacterial genomes. The availability of these tools can enhance our understanding of NRP synthesis and the function of their biosynthetic enzymes.
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Abstract
All organisms produce specialized organic molecules, ranging from small volatile chemicals to large gene-encoded peptides, that have evolved to provide them with diverse cellular and ecological functions. As natural products, they are broadly applied in medicine, agriculture and nutrition. The rapid accumulation of genomic information has revealed that the metabolic capacity of virtually all organisms is vastly underappreciated. Pioneered mainly in bacteria and fungi, genome mining technologies are accelerating metabolite discovery. Recent efforts are now being expanded to all life forms, including protists, plants and animals, and new integrative omics technologies are enabling the increasingly effective mining of this molecular diversity.
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Affiliation(s)
- Marnix H Medema
- Bioinformatics Group, Wageningen University, Wageningen, The Netherlands
| | - Tristan de Rond
- Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA
| | - Bradley S Moore
- Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA.
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA.
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7
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Přívratský J, Novák J. MassSpecBlocks: a web-based tool to create building blocks and sequences of nonribosomal peptides and polyketides for tandem mass spectra analysis. J Cheminform 2021; 13:51. [PMID: 34233741 PMCID: PMC8265115 DOI: 10.1186/s13321-021-00530-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 06/30/2021] [Indexed: 11/16/2022] Open
Abstract
Nonribosomal peptides and polyketides are natural products commonly synthesized by microorganisms. They are widely used in medicine, agriculture, environmental protection, and other fields. The structures of natural products are often analyzed by high-resolution tandem mass spectrometry, which becomes more popular with its increasing availability. However, the characterization of nonribosomal peptides and polyketides from tandem mass spectra is a nontrivial task because they are composed of many uncommon building blocks in addition to proteinogenic amino acids. Moreover, many of them have cyclic and branch-cyclic structures. Here, we introduce MassSpecBlocks – an open-source and web-based tool that converts the input chemical structures in SMILES format into sequences of building blocks. The structures can be searched in public databases PubChem, ChemSpider, ChEBI, NP Atlas, COCONUT, and Norine and edited in a user-friendly graphical interface. Although MassSpecBlocks can serve as a stand-alone database, our primary goal was to enable easy construction of custom sequence and building block databases, which can be used to annotate mass spectra in CycloBranch software. CycloBranch is an open-source, cross-platform, and stand-alone tool that we recently released for annotating spectra of linear, cyclic, branched, and branch-cyclic nonribosomal peptides and polyketide siderophores. The sequences and building blocks created in MassSpecBlocks can be easily exported into a plain text format used by CycloBranch. MassSpecBlocks is available online or can be installed entirely offline. It offers a REST API to cooperate with other tools. ![]()
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Affiliation(s)
- Jan Přívratský
- Faculty of Information Technology, Czech Technical University in Prague, Thákurova 9, 160 00, Prague, Czech Republic
| | - Jiří Novák
- Faculty of Information Technology, Czech Technical University in Prague, Thákurova 9, 160 00, Prague, Czech Republic. .,Institute of Microbiology, Czech Academy of Sciences, Vídeňská 1083, 142 20, Prague, Czech Republic.
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8
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Abstract
Genetically encoded small molecules (secondary metabolites) play eminent roles in ecological interactions, as pathogenicity factors and as drug leads. Yet, these chemical mediators often evade detection, and the discovery of novel entities is hampered by low production and high rediscovery rates. These limitations may be addressed by genome mining for biosynthetic gene clusters, thereby unveiling cryptic metabolic potential. The development of sophisticated data mining methods and genetic and analytical tools has enabled the discovery of an impressive array of previously overlooked natural products. This review shows the newest developments in the field, highlighting compound discovery from unconventional sources and microbiomes. Natural products are an important source of bioactive compounds and have versatile applications in different fields, but their discovery is challenging. Here, the authors review the recent developments in genome mining for discovery of natural products, focusing on compounds from unconventional microorganisms and microbiomes.
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Affiliation(s)
- Kirstin Scherlach
- Department of Biomolecular Chemistry, Leibniz Institute for Natural Product Research and Infection Biology, HKI, Jena, Germany
| | - Christian Hertweck
- Department of Biomolecular Chemistry, Leibniz Institute for Natural Product Research and Infection Biology, HKI, Jena, Germany. .,Faculty of Biological Sciences, Friedrich Schiller University Jena, Jena, Germany.
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9
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Abstract
Covering: 2020 Bioinformatic approaches to document and analyse chemical structures, biosynthetic gene clusters and analytical data play an important role in the study of natural products. Every year, such a large number of new algorithms, tools and databases are released, that it is difficult to keep track of all the latest developments. The aim of this short article is to provide a concise overview of and reference to the major tools, methods and databases that have been released in the past year.
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Affiliation(s)
- Marnix H Medema
- Bioinformatics Group, Wageningen University, Wageningen, The Netherlands.
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Affiliation(s)
- Emma Ricart
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, CMU, Rue Michel-Servet 1, Geneva 1211, Switzerland
- Computer Science Department, University of Geneva, Geneva 1227, Switzerland
| | - Maude Pupin
- University Lille, CNRS, Centrale Lille, UMR 9189−CRIStAL−Centre de Recherche en Informatique Signal et Automatique de Lille, Lille F-59000, France
| | - Markus Müller
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, CMU, Rue Michel-Servet 1, Geneva 1211, Switzerland
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, Amphipole Building, Quartier Sorge, Lausanne 1015, Switzerland
| | - Frédérique Lisacek
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, CMU, Rue Michel-Servet 1, Geneva 1211, Switzerland
- Computer Science Department, University of Geneva, Geneva 1227, Switzerland
- Section of Biology, University of Geneva, Geneva 1227, Switzerland
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11
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Flissi A, Ricart E, Campart C, Chevalier M, Dufresne Y, Michalik J, Jacques P, Flahaut C, Lisacek F, Leclère V, Pupin M. Norine: update of the nonribosomal peptide resource. Nucleic Acids Res 2020; 48:D465-D469. [PMID: 31691799 PMCID: PMC7145658 DOI: 10.1093/nar/gkz1000] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2019] [Revised: 10/15/2019] [Accepted: 10/22/2019] [Indexed: 12/21/2022] Open
Abstract
Norine, the unique resource dedicated to nonribosomal peptides (NRPs), is now updated with a new pipeline to automate massive sourcing and enhance annotation. External databases are mined to extract NRPs that are not yet in Norine. To maintain a high data quality, successive filters are applied to automatically validate the NRP annotations and only validated data is inserted in the database. External databases were also used to complete annotations of NRPs already in Norine. Besides, annotation consistency inside Norine and between Norine and external sources have reported annotation errors. Some can be corrected automatically, while others need manual curation. This new approach led to the insertion of 539 new NRPs and the addition or correction of annotations of nearly all Norine entries. Two new tools to analyse the chemical structures of NRPs (rBAN) and to infer a molecular formula from the mass-to-charge ratio of an NRP (Kendrick Formula Predictor) were also integrated. Norine is freely accessible from the following URL: https://bioinfo.cristal.univ-lille.fr/norine/
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Affiliation(s)
- Areski Flissi
- Univ. Lille, CNRS, Centrale Lille, UMR 9189 - CRIStAL - Centre de Recherche en Informatique Signal et Automatique de Lille, F-59000 Lille, France
| | - Emma Ricart
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, CMU, Rue Michel-Servet 1, 1211 Geneva, Switzerland.,Computer Science Department, University of Geneva, CUI, 7 route de Drize, 1227 Carouge, Switzerland
| | - Clémentine Campart
- Univ. Lille, CNRS, Centrale Lille, UMR 9189 - CRIStAL - Centre de Recherche en Informatique Signal et Automatique de Lille, F-59000 Lille, France
| | - Mickael Chevalier
- Univ. Lille, INRA, ISA, Univ. Artois, Univ. Littoral Côte d'Opale, EA 7394-ICV- Institut Charles Viollette, F-59000 Lille, France
| | - Yoann Dufresne
- Univ. Lille, CNRS, Centrale Lille, UMR 9189 - CRIStAL - Centre de Recherche en Informatique Signal et Automatique de Lille, F-59000 Lille, France
| | - Juraj Michalik
- Univ. Lille, CNRS, Centrale Lille, UMR 9189 - CRIStAL - Centre de Recherche en Informatique Signal et Automatique de Lille, F-59000 Lille, France.,bilille, CNRS, cité scientifique, F-59650 Villeneuve d'Ascq, France
| | - Philippe Jacques
- TERRA Teaching and Research Centre, Microbial Processes and Interactions, Gembloux Agro-Bio Tech, University of Liège, Avenue de la Faculté d'Agronomie, B5030 Gembloux, Belgium
| | - Christophe Flahaut
- Univ. Lille, INRA, ISA, Univ. Artois, Univ. Littoral Côte d'Opale, EA 7394-ICV- Institut Charles Viollette, F-59000 Lille, France
| | - Frédérique Lisacek
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, CMU, Rue Michel-Servet 1, 1211 Geneva, Switzerland.,Computer Science Department, University of Geneva, CUI, 7 route de Drize, 1227 Carouge, Switzerland.,Section of Biology, University of Geneva, Sciences III, 30 quai Ernest-Ansermet, 1211 Geneva, Switzerland
| | - Valérie Leclère
- Univ. Lille, INRA, ISA, Univ. Artois, Univ. Littoral Côte d'Opale, EA 7394-ICV- Institut Charles Viollette, F-59000 Lille, France
| | - Maude Pupin
- Univ. Lille, CNRS, Centrale Lille, UMR 9189 - CRIStAL - Centre de Recherche en Informatique Signal et Automatique de Lille, F-59000 Lille, France
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Abstract
Declining rates of novel natural product discovery and exponential rates of rediscovery heralded the end of the 1940s to 1960s "golden era" of antibiotic discovery. Fifty years later, the implementation of molecular screening methodologies revealed that standard culture-based screening approaches had failed to capture the vast majority of environmental bacteria and that even for the cultivable isolates only a small fraction of the biosynthetic potential had been tapped. A diversity of metagenomic screening and synthetic biology approaches have been developed to address these issues. The nonribosomal peptides have received particular focus, owing to their high levels of bioactivity and the predictability of the biosynthetic logic of the genetically encoded assembly lines that produce them. By uniting advances in next-generation sequencing and bioinformatic analysis with a diversity of traditional disciplines, several pioneering teams have proven that this previously inaccessible resource is no longer out of reach.
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Affiliation(s)
- Luke J. Stevenson
- School of Biological Sciences, Victoria University of Wellington, Wellington 6012, New Zealand
- Centre for Biodiscovery, Victoria University of Wellington, Wellington 6012, New Zealand
- Maurice Wilkins Centre for Molecular Biodiscovery, Auckland, New Zealand
| | - Jeremy G. Owen
- School of Biological Sciences, Victoria University of Wellington, Wellington 6012, New Zealand
- Centre for Biodiscovery, Victoria University of Wellington, Wellington 6012, New Zealand
- Maurice Wilkins Centre for Molecular Biodiscovery, Auckland, New Zealand
| | - David F. Ackerley
- School of Biological Sciences, Victoria University of Wellington, Wellington 6012, New Zealand
- Centre for Biodiscovery, Victoria University of Wellington, Wellington 6012, New Zealand
- Maurice Wilkins Centre for Molecular Biodiscovery, Auckland, New Zealand
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Alanjary M, Cano-Prieto C, Gross H, Medema MH. Computer-aided re-engineering of nonribosomal peptide and polyketide biosynthetic assembly lines. Nat Prod Rep 2019; 36:1249-1261. [PMID: 31259995 DOI: 10.1039/c9np00021f] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Covering: 2014 to 2019Nonribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs) have been the subject of engineering efforts for multiple decades. Their modular assembly line architecture potentially allows unlocking vast chemical space for biosynthesis. However, attempts thus far are often met with mixed success, due to limited molecular compatibility of the parts used for engineering. Now, new engineering strategies, increases in genomic data, and improved computational tools provide more opportunities for major progress. In this review we highlight some of the challenges and progressive strategies for the re-design of NRPSs & type I PKSs and survey useful computational tools and approaches to attain the ultimate goal of semi-automated and design-based engineering of novel peptide and polyketide products.
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Affiliation(s)
- Mohammad Alanjary
- Bioinformatics Group, Wageningen University, Wageningen, The Netherlands.
| | - Carolina Cano-Prieto
- Department of Pharmaceutical Biology, Pharmaceutical Institute, Eberhard Karls Universität Tübingen, Tübingen, Germany.
| | - Harald Gross
- Department of Pharmaceutical Biology, Pharmaceutical Institute, Eberhard Karls Universität Tübingen, Tübingen, Germany.
| | - Marnix H Medema
- Bioinformatics Group, Wageningen University, Wageningen, The Netherlands.
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