Chemical structure metagenomics of microbial natural products: surveying nonribosomal peptides and beyond

• Thomas Ma and
• John Chu

Beilstein J. Org. Chem. 2024, 20, 3050–3060, doi:10.3762/bjoc.20.253

• . While microbial nonribosomal peptides have been the focus of chemical structure metagenomics efforts thus far, it is in principle applicable to other natural product families. The future outlook of this new approach will also be discussed. Keywords: bioinformatics; chemical structure metagenomics

• morphology of the host, etc. [25]. Sequence and function metagenomic approaches have been reviewed elsewhere and will not be covered herein [26][27][28]. This Perspective focuses on chemical structure metagenomics (Figure 2c), an emerging field that integrates bioinformatics, chemical synthesis, molecular

Young investigators in natural products chemistry, biosynthesis, and enzymology

• Jeffrey D. Rudolf,
• Lena Barra and
• Takayoshi Awakawa

Beilstein J. Org. Chem. 2024, 20, 2720–2721, doi:10.3762/bjoc.20.229

• present this collection of 19 Full Research Papers, three Letters, and nine Review articles from our colleagues around the world. Topics covered include natural product discovery efforts from a variety of organisms, genome and transcriptome mining and bioinformatics of natural products, biosynthetic gene

Improved deconvolution of natural products’ protein targets using diagnostic ions from chemical proteomics linkers

• Andreas Wiest and
• Pavel Kielkowski

Beilstein J. Org. Chem. 2024, 20, 2323–2341, doi:10.3762/bjoc.20.199

• via MS-based chemical proteomics [5][6]. In proteomics and its sub-field of chemical proteomics, there are two major areas of development, mass spectrometry instrumentation and bioinformatics. The MS instruments acquire the mass spectra with significantly increased throughput and sensitivity

O,S,Se-containing Biginelli products based on cyclic β-ketosulfone and their postfunctionalization

• Kateryna V. Dil and
• Vitalii A. Palchykov

Beilstein J. Org. Chem. 2024, 20, 2143–2151, doi:10.3762/bjoc.20.184

• 52: Experimental procedures and characterization data of new compounds. Acknowledgements The authors are grateful to Enamine Ltd. (Kyiv, Ukraine) for NMR/HRMS support. The authors also thank Charite University of Medicine, Germany (Institute for Physiology, Structural Bioinformatics Group), Federal

• University of Paraíba, Brazil (Laboratory of Cheminformatics), University of Lausanne, Switzerland (SIB Swiss Institute of Bioinformatics), and the University of Leeds, UK (School of Chemistry) for free online cheminformatics software. V.A.P. would like to express special thanks to the Matsumae International

Computational toolbox for the analysis of protein–glycan interactions

• Ferran Nieto-Fabregat,
• Maria Pia Lenza,
• Angela Marseglia,
• Cristina Di Carluccio,
• Antonio Molinaro,
• Alba Silipo and
• Roberta Marchetti

Beilstein J. Org. Chem. 2024, 20, 2084–2107, doi:10.3762/bjoc.20.180

• focused in the last decades on the development of new techniques and technologies for the systematic analysis of complex glycans and the study of their interactions with proteins. A multidisciplinary approach, spanning from wet laboratory experiments and biophysical techniques to bioinformatics methods is

• the field of computational chemistry and bioinformatics. It is extensively used to model and simulate the dynamic behaviour of various molecular systems, including proteins, nucleic acids, lipids, and small molecules. GROMACS provides various tools for system preparation, simulation setup, and post

Discovery of antimicrobial peptides clostrisin and cellulosin from Clostridium: insights into their structures, co-localized biosynthetic gene clusters, and antibiotic activity

• Moisés Alejandro Alejo Hernandez,
• Katia Pamela Villavicencio Sánchez,
• Rosendo Sánchez Morales,
• Karla Georgina Hernández-Magro Gil,
• David Silverio Moreno-Gutiérrez,
• Eddie Guillermo Sanchez-Rueda,
• Yanet Teresa-Cruz,
• Brian Choi,
• Armando Hernández Garcia,
• Alba Romero-Rodríguez,
• Oscar Juárez,
• Siseth Martínez-Caballero,
• Mario Figueroa and
• Corina-Diana Ceapă

Beilstein J. Org. Chem. 2024, 20, 1800–1816, doi:10.3762/bjoc.20.159

• . Furthermore, the increasing availability of genomic data has led to the development of bioinformatics tools, such as AntiSMASH [3], Bagel4 [4], and RiPPMiner [5], that have emerged to streamline the process of exploring and discovering BGCs in bacteria, known as genome mining. Genome mining has emerged as a

• bioinformatics studies have not provided any clues about the resistance mechanisms of these peptides. Therefore, we plan to conduct further research to gain insights into these functions. This could help us to understand the potential for these peptides to display antimicrobial resistance in the future. Atomic

Polymer degrading marine Microbulbifer bacteria: an un(der)utilized source of chemical and biocatalytic novelty

• Weimao Zhong and
• Vinayak Agarwal

Beilstein J. Org. Chem. 2024, 20, 1635–1651, doi:10.3762/bjoc.20.146

• thus so far is not comparable to the expected metabolites envisioned from bioinformatics analyses of the Microbulbifer genomes. Contemporary and in-development tools and technologies for data mining, synthetic biology, and strain manipulation will have a transformative effect on future natural product

Mining raw plant transcriptomic data for new cyclopeptide alkaloids

• Draco Kriger,
• Michael A. Pasquale,
• Brigitte G. Ampolini and
• Jonathan R. Chekan

Beilstein J. Org. Chem. 2024, 20, 1548–1559, doi:10.3762/bjoc.20.138

• and post-translationally modified peptide (RiPP) natural products offer a valuable opportunity for bioinformatics-guided discovery in plants due to their short biosynthetic pathways and gene encoded substrates. Using a high-throughput approach to assemble and analyze 700 publicly available raw

Bioinformatic prediction of the stereoselectivity of modular polyketide synthase: an update of the sequence motifs in ketoreductase domain

• Changjun Xiang,
• Shunyu Yao,
• Ruoyu Wang and
• Lihan Zhang

Beilstein J. Org. Chem. 2024, 20, 1476–1485, doi:10.3762/bjoc.20.131

• : bioinformatics; conserved motifs; ketoreductase; polyketide synthase; stereocontrol; Introduction Type I modular polyketide synthases (PKSs) are large enzyme complexes that play a crucial role in the biosynthesis of bacterial polyketides, including many important clinical drugs such as erythromycin (antibiotic

• binding motif can be used to predict C2-type KRs [9]. These conserved motifs have been widely used to predict the stereochemical outcome of modular cis-AT PKSs and have facilitated bioinformatics-guided structural determination of complex polyketides [12][13][14][15][16][17]. However, despite being widely

• bioinformatics perspective, and will facilitate accurate stereochemical prediction and genome mining of complex polyketides. Experimental Sequence collection and screening All cis-AT PKS and PKS-NRPS amino acid sequences recorded in MIBiG, as well as the PKS sequences reported in literatures we have curated were

A Diels–Alder probe for discovery of natural products containing furan moieties

• Alyssa S. Eggly,
• Namuunzul Otgontseren,
• Carson B. Roberts,
• Amir Y. Alwali,
• Haylie E. Hennigan and
• Elizabeth I. Parkinson

Beilstein J. Org. Chem. 2024, 20, 1001–1010, doi:10.3762/bjoc.20.88

• times) to observe the molecules in their native producers. While this is not ideal, it is still significantly better than the concentration needed without probe (≈260,000 times). Conclusion MMFs are important signaling hormones that induce the production of methylenomycin A. Bioinformatics data suggests

Discovery and biosynthesis of bacterial drimane-type sesquiterpenoids from Streptomyces clavuligerus

• Dongxu Zhang,
• Wenyu Du,
• Xingming Pan,
• Xiaoxu Lin,
• Fang-Ru Li,
• Qingling Wang,
• Qian Yang,
• Hui-Min Xu and
• Liao-Bin Dong

Beilstein J. Org. Chem. 2024, 20, 815–822, doi:10.3762/bjoc.20.73

• subfamilies within the sesquiterpenoids. Our discovery significantly broadens the scope for future exploration of bacterial DMTs. Discovery and identification of a DMS in the cav BGC in S. clavuligerus To explore the BGC responsible for DMTs production in S. clavuligerus, we performed bioinformatics research

Chemoenzymatic synthesis of macrocyclic peptides and polyketides via thioesterase-catalyzed macrocyclization

• Senze Qiao,
• Zhongyu Cheng and
• Fuzhuo Li

Beilstein J. Org. Chem. 2024, 20, 721–733, doi:10.3762/bjoc.20.66

• -acetylcysteamine. Via bioinformatics analysis, Parkinson and co-workers most recently reported the characterization of Ulm16, the PBP-TE predicted to cyclize ulleungymycin. Compared with previously studied PBP-TEs, Ulm16 showed much higher efficiency and broader substrate scope, producing a variety of ullemgymycin

• stability, etc. Emerging research methods on bioinformatics, computational modeling, deep learning, protein engineering, and high-throughput screening will accelerate the pace of enzyme discovery to provide a broader platform of tools for employing chemoenzymatic strategies [64][87][88][89]. More

New variochelins from soil-isolated Variovorax sp. H002

• Jabal Rahmat Haedar,
• Aya Yoshimura and
• Toshiyuki Wakimoto

Beilstein J. Org. Chem. 2024, 20, 692–700, doi:10.3762/bjoc.20.63

• )-ʟ-alaninamide) derivatives [5]. In addition, a combination of NOESY and bioinformatics analyses proposed all three stereocenters of 4-amino-7-guanidino-3-hydroxy-2-methylheptanoic acid as S configured [5]. The stereochemistry of these moieties in 3–5 are discussed in the next section, regarding the

Chemical and biosynthetic potential of Penicillium shentong XL-F41

• Ran Zou,
• Xin Li,
• Xiaochen Chen,
• Yue-Wei Guo and
• Baofu Xu

Beilstein J. Org. Chem. 2024, 20, 597–606, doi:10.3762/bjoc.20.52

• applications. Despite the extensive catalog of secondary metabolites discovered, the pace of new findings has decelerated. However, the advent of bioinformatics analysis tools has reinvigorated the search for fungal secondary metabolites. The estimated number of non-redundant clusters in Penicillium is around

Recent developments in the engineered biosynthesis of fungal meroterpenoids

• Zhiyang Quan and
• Takayoshi Awakawa

Beilstein J. Org. Chem. 2024, 20, 578–588, doi:10.3762/bjoc.20.50

• cross-coupling between two aromatic rings [43]. In the future, further developments in bioinformatics, structural biology, and AI techniques will enable the design of biosynthetic enzymes and pathways to produce desired bioactive compounds, although understanding the chemistry catalyzed by individual

Discovery of unguisin J, a new cyclic peptide from Aspergillus heteromorphus CBS 117.55, and phylogeny-based bioinformatic analysis of UngA NRPS domains

• Sharmila Neupane,
• Marcelo Rodrigues de Amorim and
• Elizabeth Skellam

Beilstein J. Org. Chem. 2024, 20, 321–330, doi:10.3762/bjoc.20.32

• , MeOH); UV (photodiode array, MeCN/H2O) λmax = 219 and 279 nm; HRESIMS m/z: [M + H]+ calcd for C41H57N8O7+, 773.4345; found, 773.4338, [M + Na]+ calcd for C41H56N8O7Na+, 795.4164; found, 795.4162. For the 1H and 13C NMR spectroscopic data, see Table 1. Bioinformatics The A. heteromorphus CBS 117.55

Characterization of a new fusicoccane-type diterpene synthase and an associated P450 enzyme

• Jia-Hua Huang,
• Jian-Ming Lv,
• Liang-Yan Xiao,
• Qian Xu,
• Fu-Long Lin,
• Gao-Qian Wang,
• Guo-Dong Chen,
• Sheng-Ying Qin,
• Dan Hu and
• Hao Gao

Beilstein J. Org. Chem. 2022, 18, 1396–1402, doi:10.3762/bjoc.18.144

• corresponding products. Bioinformatics analysis of the tad cluster. A) Phylogenetic tree of TadA and representative fungal DTSs. B) Putative functions of the tad cluster. HPLC–MS analysis of mycelial extracts from A. oryzae NSAR1 transformants. A) The HPLC profiles monitored at 208 nm. B) The HPLC profiles

Computational model predicts protein binding sites of a luminescent ligand equipped with guanidiniocarbonyl-pyrrole groups

• Neda Rafieiolhosseini,
• Matthias Killa,
• Thorben Neumann,
• Niklas Tötsch,
• Jean-Noël Grad,
• Alexander Höing,
• Thies Dirksmeyer,
• Jochen Niemeyer,
• Christian Ottmann,
• Shirley K. Knauer,
• Michael Giese,
• Jens Voskuhl and
• Daniel Hoffmann

Beilstein J. Org. Chem. 2022, 18, 1322–1331, doi:10.3762/bjoc.18.137

• Neda Rafieiolhosseini Matthias Killa Thorben Neumann Niklas Totsch Jean-Noel Grad Alexander Hoing Thies Dirksmeyer Jochen Niemeyer Christian Ottmann Shirley K. Knauer Michael Giese Jens Voskuhl Daniel Hoffmann Bioinformatics and Computational Biophysics, Center for Medical Biotechnology (ZMB

Isolation and biosynthesis of daturamycins from Streptomyces sp. KIB-H1544

• Yin Chen,
• Jinqiu Ren,
• Ruimin Yang,
• Jie Li,
• Sheng-Xiong Huang and
• Yijun Yan

Beilstein J. Org. Chem. 2022, 18, 1009–1016, doi:10.3762/bjoc.18.101

• daturamycin C, were isolated and identified. The new diarylcyclopentenones possess a rare class of a tricyclic 6/5/6 system. Based on the bioinformatics analysis, the daturamycins biosynthetic gene cluster has been identified and confirmed by the inactivation of the structural gene datA. The following

Anti-inflammatory aromadendrane- and cadinane-type sesquiterpenoids from the South China Sea sponge Acanthella cavernosa

• Shou-Mao Shen,
• Qing Yang,
• Yi Zang,
• Jia Li,
• Xueting Liu and
• Yue-Wei Guo

Beilstein J. Org. Chem. 2022, 18, 916–925, doi:10.3762/bjoc.18.91

• yet been discovered. Phenolic sesquiterpenoids, for instance, illudacetalic acid and illudinine from Omphalotus olearius, were also discovered. Based on bioinformatics analysis, their aromatic rings were proposed to be constructed by putative P450 enzymes or oxidoreductase [33]. The Huang group

GlycoBioinformatics

• Kiyoko F. Aoki-Kinoshita,
• Frédérique Lisacek,
• Niclas Karlsson,
• Daniel Kolarich and
• Nicolle H. Packer

Beilstein J. Org. Chem. 2021, 17, 2726–2728, doi:10.3762/bjoc.17.184

• Kiyoko F. Aoki-Kinoshita Frederique Lisacek Niclas Karlsson Daniel Kolarich Nicolle H. Packer Faculty of Science and Engineering, Soka University, 1-236 Tangi-machi, Hachioji-shi, Tokyo, Japan University of Geneva and Swiss Institute of Bioinformatics, CUI - 7, route de Drize, 1211 Geneva

• , Queensland 4222, Australia Department of Molecular Sciences, Macquarie University, Sydney, New South Wales, Australia 10.3762/bjoc.17.184 Keywords: bioinformatics; glycobioinformatics; glycoinformatics; In order to introduce this thematic issue “GlycoBioinformatics” [1] in the Beilstein Journal of Organic

• Chemistry, it would be appropriate to define what we actually mean by this term. This is important not only for newcomers to the field but also in order for researchers that have used or developed “glycobioinformatics” to place their work into a wider context of this diverse field. The term “bioinformatics

A systems-based framework to computationally describe putative transcription factors and signaling pathways regulating glycan biosynthesis

• Theodore Groth,
• Rudiyanto Gunawan and
• Sriram Neelamegham

Beilstein J. Org. Chem. 2021, 17, 1712–1724, doi:10.3762/bjoc.17.119

• , but enhancers present several kilobases away from the transcription state site (TSS) are neglected; and iii) most of these reported TF–glycogene relationships only have partial support in established bioinformatics databases (DBs, see Supporting Information File 1). Thus, these are limited hypothesis

Volatile emission and biosynthesis in endophytic fungi colonizing black poplar leaves

• Christin Walther,
• Pamela Baumann,
• Katrin Luck,
• Beate Rothe,
• Peter H. W. Biedermann,
• Jonathan Gershenzon,
• Tobias G. Köllner and
• Sybille B. Unsicker

Beilstein J. Org. Chem. 2021, 17, 1698–1711, doi:10.3762/bjoc.17.118

• Genomics Workbench (Qiagen Bioinformatics) using default parameters or parameters specified as follows: bubble size, 100; automatic word size; minimum contig length, 600. A BUSCO analysis (Supporting Information File 1, Figure S3) was performed to validate the completeness of the transcriptome

Semiautomated glycoproteomics data analysis workflow for maximized glycopeptide identification and reliable quantification

• Steffen Lippold,
• Arnoud H. de Ru,
• Jan Nouta,
• Peter A. van Veelen,
• Magnus Palmblad,
• Manfred Wuhrer and
• Noortje de Haan

Beilstein J. Org. Chem. 2020, 16, 3038–3051, doi:10.3762/bjoc.16.253

• quantification. Keywords: bioinformatics; cysteine oxidation; glycoproteomics; immunoglobulins; mass spectrometry; Introduction Protein glycosylation mainly occurs in the form of N- and O-glycosylation. N-Glycans are attached to Asn within an amino acid consensus sequence (Asn-Xxx-Ser/Thr, Xxx ≠ Pro) and O

Comparative ligand structural analytics illustrated on variably glycosylated MUC1 antigen–antibody binding

• Christopher B. Barnett,
• Tharindu Senapathi and
• Kevin J. Naidoo

Beilstein J. Org. Chem. 2020, 16, 2540–2550, doi:10.3762/bjoc.16.206

• ]. Originally built to support bioinformatics, Galaxy now supports a much more expansive community including proteomics [2], metabolomics [3], cheminformatics [4], glycoinformatics [5], and chemistry [6]. Of value to these communities are the broad range of tools and ways to connect tools (workflows) in Galaxy

• of the analyses was carried out using Galaxy, the popular open web-based platform for bioinformatics and computational data analysis, which enables the creation of repeatable analysis pipelines (workflows). There are several well-known molecular dynamics analysis packages (MDAnalysis [37], Bio3D [38