Orthogonal photoswitching of heterobivalent azobenzene glycoclusters: the effect of glycoligand orientation in bacterial adhesion

• Leon M. Friedrich and
• Thisbe K. Lindhorst

Beilstein J. Org. Chem. 2025, 21, 736–748, doi:10.3762/bjoc.21.57

• modeling illustrates the different FimH binding modes of the various isomers of 1 and 2 (Figure 4C and D). Inspection of these ligand–protein complexes reveals that in all isomers, a terminal α-ᴅ-mannoside ligand is complexed within the FimH carbohydrate binding pocket where it forms the classical network

Photochemically assisted synthesis of phenacenes fluorinated at the terminal benzene rings and their electronic spectra

• Yuuki Ishii,
• Minoru Yamaji,
• Fumito Tani,
• Kenta Goto,
• Yoshihiro Kubozono and
• Hideki Okamoto

Beilstein J. Org. Chem. 2025, 21, 670–679, doi:10.3762/bjoc.21.53

• Suzuki (Okayama University) for solid-state absorption spectral measurements. Funding The present study was supported by Grants-in-Aid for Scientific Research, KAKENHI, from JSPS, Japan (JP18H02043, JP20K05648, JP23K04877), and by the Cooperative Research Program of the ‘Network Joint Research Centre for

Unprecedented visible light-initiated topochemical [2 + 2] cycloaddition in a functionalized bimane dye

• Metodej Dvoracek,
• Brendan Twamley,
• Mathias O. Senge and
• Mikhail A. Filatov

Beilstein J. Org. Chem. 2025, 21, 500–509, doi:10.3762/bjoc.21.37

• reported bimane, syn-(H,Cl)bimane (BIYGUL), reveals a ribbon-like packing pattern, which arises from a hydrogen-bonding network [23], which also features a coplanar and parallel arrangement of the potentially reactive double bonds. Due to these characteristics, the reaction site can be represented by a

Heteroannulations of cyanoacetamide-based MCR scaffolds utilizing formamide

• Marios Zingiridis,
• Danae Papachristodoulou,
• Despoina Menegaki,
• Konstantinos G. Froudas and
• Constantinos G. Neochoritis

Beilstein J. Org. Chem. 2025, 21, 217–225, doi:10.3762/bjoc.21.13

• was observed at an average wavelength of 384 nm for 5a–e, 439 nm for 6a–e and 430 nm for 7a–e (see Supporting Information File 1 for detailed information). In support of the proposed scaffold 7b, we were able to solve its crystal structure (Figure 3). An intermolecular bifurcated hydrogen bond network

Quantifying the ability of the CF₂H group as a hydrogen bond donor

• Matthew E. Paolella,
• Daniel S. Honeycutt,
• Bradley M. Lipka,
• Jacob M. Goldberg and
• Fang Wang

Beilstein J. Org. Chem. 2025, 21, 189–199, doi:10.3762/bjoc.21.11

• Island Institutional Development Award (IDeA) Network of Biomedical Research Excellence from the National Institute of General Medical Sciences of the National Institutes of Health under Grant No. P20GM103430 through the Centralized Research Core facility. M.E.P. was a Moissan Summer Undergraduate

Facile one-pot reduction of β-nitrostyrenes to phenethylamines using sodium borohydride and copper(II) chloride

• Laura D’Andrea and
• Simon Jademyr

Beilstein J. Org. Chem. 2025, 21, 39–46, doi:10.3762/bjoc.21.4

• optimization table, and ESI-MS spectra for the synthesis of 4b. Acknowledgements The authors acknowledge the Ph.D. thesis of L.D'A., titled "Design and Synthesis of beta-Arrestin-Biased 5HT2AR Agonists". Funding L.D’A. acknowledges the EU Horizon 2020, Innovative Training Network SAFER (765657). Conflict of

Emerging trends in the optimization of organic synthesis through high-throughput tools and machine learning

• Pablo Quijano Velasco,
• Kedar Hippalgaonkar and
• Balamurugan Ramalingam

Beilstein J. Org. Chem. 2025, 21, 10–38, doi:10.3762/bjoc.21.3

• reflectance probe was employed for real-time monitoring of hydrolysis by in-line UV–vis spectroscopy. The raw data was processed using a sophisticated neural network algorithm, yielding rapid quantification with an impressive processing time of 1.4 ms per spectrum. This streamlined approach ensured efficient

Chemical glycobiology

• Elisa Fadda,
• Rachel Hevey,
• Benjamin Schumann and
• Ulrika Westerlind

Beilstein J. Org. Chem. 2025, 21, 8–9, doi:10.3762/bjoc.21.2

• experimental and computational efforts, developing a neural-network-based approach for the interpretation of glycan structures from their vibrational fingerprints [17]. We anticipate that this diverse collection of reports across the entire spectrum of the chemical sciences cements the readers’ understanding

Synthesis, structure and π-expansion of tris(4,5-dehydro-2,3:6,7-dibenzotropone)

• Yongming Xiong,
• Xue Lin Ma,
• Shilong Su and
• Qian Miao

Beilstein J. Org. Chem. 2025, 21, 1–7, doi:10.3762/bjoc.21.1

• recently showed that polymerizing negatively curved polycyclic arenes produced an amorphous covalent network. This network was able to mimic the structure and function of carbon schwarzites, serving as an anode material in lithium-ion batteries with high capacity [21]. Further exploration of bottom-up

Cyclodextrin-based rotaxanes for polymer materials: challenge on simultaneous realization of inexpensive production and defined structures

• Yosuke Akae

Beilstein J. Org. Chem. 2024, 20, 3026–3049, doi:10.3762/bjoc.20.252

• consists of the rotaxane crosslinking structure, as a tough material or ultra-stretchable/swelling polymer [79][80]. A typical slide ring gel has a network structure of polyrotaxane, which consists of a linear polymer chain like PEG and many α-CD rings on it, meaning that the crosslinking points are made

• ) on it, besides it has a thick ring structure. The electrochemical properties of the modified CD-based conjugative polymers have been intensively studied by Terao and co-workers [83]. Apart from a typical CD-based polyrotaxane network, which contains CDs and linear polymer chain-based polyrotaxane as

• -responsive nature became much faster than the system without VSC. This fast responsiveness was induced by the dynamic rotaxane crosslinking structure. This method can be applied in various vinyl polymer systems, and induces the rotaxane crosslinking nature to the resulting network polymer, suggesting its

Applications of microscopy and small angle scattering techniques for the characterisation of supramolecular gels

• Connor R. M. MacDonald and
• Emily R. Draper

Beilstein J. Org. Chem. 2024, 20, 2608–2634, doi:10.3762/bjoc.20.220

• utilise the self-assembly of small molecules into a network of long anisotropic structures which can entangle or cross-link. This network can immobilise the solvent, resulting in a material with both solid-like and liquid-like characteristics. The versatility of these compounds arises from their self

• techniques Imaging is the most widely used and accessible technique for characterising these gel materials. Researchers are looking for the presence of fibrous structures, coils, entanglements, spherulites and other such features that can give them some insight into how the gel is formed in the network via

• the assembly of interlocking nanostructures and microstructures. Imaging is often inexpensive and accessible both in terms of access and interpretation of the data given. These images are attractive and give an instant visual summary of the network. Depending on the type of imaging used, multiple

Machine learning-guided strategies for reaction conditions design and optimization

• Lung-Yi Chen and
• Yi-Pei Li

Beilstein J. Org. Chem. 2024, 20, 2476–2492, doi:10.3762/bjoc.20.212

• architectures that can learn latent patterns from the reactants and products, but they require sufficient data to train both the feature extractor and the neural network. These methods also reduce the need for manual feature selection by chemists. Descriptor-based representation Descriptor-based methods are

• nodes and edges through recursive message passing and a readout function, resulting in a molecular representation. There are many variants of GNN models [140][141][142][143], most of which are based on the message passing neural network (MPNN) framework proposed by Gilmer et al. [144]. Encoding

Phenylseleno trifluoromethoxylation of alkenes

• Clément Delobel,
• Armen Panossian,
• Gilles Hanquet,
• Frédéric R. Leroux,
• Fabien Toulgoat and
• Thierry Billard

Beilstein J. Org. Chem. 2024, 20, 2434–2441, doi:10.3762/bjoc.20.207

• and Research and CPE Lyon are thanked for funding. The French Fluorine Network (GIS-FLUOR) is also acknowledged for its support.

Catalysing (organo-)catalysis: Trends in the application of machine learning to enantioselective organocatalysis

• Stefan P. Schmid,
• Leon Schlosser,
• Frank Glorius and
• Kjell Jorner

Beilstein J. Org. Chem. 2024, 20, 2280–2304, doi:10.3762/bjoc.20.196

• enantioselectivities (Figure 9B). In their model, molecules were represented as graphs, where local steric and electronic information was added to each node (atom). Additionally, the used graph neural network contains a molecular interaction module that allows the model to learn synergistic effects between molecules

• , crucial for reactivity prediction tasks. While reaching state-of-the art performance in predicting ∆∆G‡ on the data set from Denmark and co-workers, the designed neural network also enables to interpret the effects leading to the observed enantioselectivity by eliminating the atom features and observing

Synthesis and reactivity of the di(9-anthryl)methyl radical

• Tomohiko Nishiuchi,
• Kazuma Takahashi,
• Yuta Makihara and
• Takashi Kubo

Beilstein J. Org. Chem. 2024, 20, 2254–2260, doi:10.3762/bjoc.20.193

• ), Osaka University, Osaka, Japan Spintronics Research Network Division, Institute for Open and Transdisciplinary Research Initiatives (SRN-OTRI), Osaka University, Osaka, Japan 10.3762/bjoc.20.193 Abstract The di(9-anthryl)methyl (DAntM) radical was synthesized and investigated to elucidate its optical

Finding the most potent compounds using active learning on molecular pairs

• Zachary Fralish and
• Daniel Reker

Beilstein J. Org. Chem. 2024, 20, 2152–2162, doi:10.3762/bjoc.20.185

• were not used during active learning but were used only in the test set evaluation of all algorithms. Model architecture and implementation To evaluate ActiveDelta with a deep machine learning model, we used the previously established, two-molecule version of the directed Message Passing Neural Network

• pairing to identify the most potent inhibitors in adaptive learning campaigns. When comparing the performance of the tree-based and the deep neural network-based ActiveDelta approaches, we observed that AD-CP and AD-XGB showed no statistically significant difference at 100 iterations (p = 0.2, Figure 2A,B

From perfluoroalkyl aryl sulfoxides to ortho thioethers

• Yang Li,
• Guillaume Dagousset,
• Emmanuel Magnier and
• Bruce Pégot

Beilstein J. Org. Chem. 2024, 20, 2108–2113, doi:10.3762/bjoc.20.181

• novel compounds. Acknowledgements We thank Matthias George for preparing some of the initial material during his master's degree. Funding Y.L. thanks the CNRS for Ph.D. grant. French Fluorine Network (GIS Fluor) is acknowledged for financial support.

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

• modelling, and some of the most popular include: 1. AlphaFold2 [88]: It is an open-access protein structure prediction system based on artificial intelligence and machine learning. It is based on a neural network that can predict the 3D protein structure at a high accuracy level. The AlphaFold solution is

• composed of two steps. First, given a protein sequence, it generates multiple alignments with sequences from all the species, including evolutionary profiles from different sources. In the second step, a model refinement is generated based on structural refinement (where the network optimises the torsion

• ://github.com/BojarLab/LectinOracle). 4. CAPSIF [109]: CArbohydrate-Protein Site IdentiFier is a convolutional neural network able to predict protein–carbohydrate binding interface from a protein structure. In contrast to other DN algorithms, as GlyNet and LectinOracle, which predict lectin-carbohydrate binding

Cage-like microstructures via sequential Ugi reactions in aqueous emulsions

• Rita S. Alqubelat,
• Yaroslava A. Menzorova and
• Maxim A. Mironov

Beilstein J. Org. Chem. 2024, 20, 2078–2083, doi:10.3762/bjoc.20.179

• principle, two possible mechanisms were considered: (1) Soft CMC/chitosan gel particles interacted with the surface and flattened to form discs. (2) When particles were deposited on the surface, they did not completely cover it, forming a network. In this work, we tested these hypotheses and found arguments

• removing the solvent, the resulting structure could be easily identified using optical microscopy. They were cage-like microspheres with an average diameter corresponding to the diameter of droplets in the Pickering emulsion (Figure 2). The surface of the droplets was covered with a network of individual

• network. The repeated Ugi reaction resulted in the formation of a strong cage-like structure that was not destroyed upon removal of the solvent. We noticed a connection between the structure of the colloidal particles and their behavior at the interface. The developed surface of the particles, consisting

A new platform for the synthesis of diketopyrrolopyrrole derivatives via nucleophilic aromatic substitution reactions

• Vitor A. S. Almodovar and
• Augusto C. Tomé

Beilstein J. Org. Chem. 2024, 20, 1933–1939, doi:10.3762/bjoc.20.169

• /2020, UIDP/50006/2020 doi:10.54499/UIDP/50006/2020 and UIDB/50006/2020 doi:54499/UIDB/50006/2020, through PT national funds within the PT2020 Partnership Agreement, and to the Portuguese NMR Network. Vítor A. S. Almodovar thanks FCT/MCTES for his doctoral grant (SFRH/BD/135598/2018).

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

• cluster of C. cellulovorans 743, clostrisin and cellulosin were compared with known lanthipeptides, generating a similarity network made using the percent identity between the precursor peptides from all experimentally characterized lanthipeptides to date (Figure 3A). We found it noteworthy to examine the

• Supporting Information File 1). For the similarity network, a database was created containing 145 precursor peptides of lanthipeptides reported in the MIBiG [38], RiPPMiner [5], and UniProt [57] databases. This input was utilized in the EFI-EST [51] web platform, employing the "FASTA" analysis option with

• the following parameters: E-value: 0.001; Fragments: disabled. Upon completion of the initial calculation, in the SNN Finishing section, an alignment score threshold of 40% was chosen, with default values for sequence length constraint, and neighborhood connectivity disabled. Network similarity was

pKalculator: A pK_a predictor for C–H bonds

• Rasmus M. Borup,
• Nicolai Ree and
• Jan H. Jensen

Beilstein J. Org. Chem. 2024, 20, 1614–1622, doi:10.3762/bjoc.20.144

• (DMSO) using a graph convolutional neural network (GCNN) [3]. Using a mix of experimental and computed pKa data, they achieved a mean absolute error (MAE) of 2.1 pKa units. Lee and co-workers also addressed this problem by creating a general machine learning (ML) model using either a neural network or

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

• . ameranicus using UHPLC-HRMS/MS. Finally, we generated a global natural product social (GNPS) network to show the correlation between metabolites from these different plant species (Figure 5) [29]. Cyclopeptides in Ceanothus americanus The GNPS network showed the presence of multiple features from C

• , Figures S16–S26, Table S1). Indeed, our results support the proposed structure of ceanothine B while also assigning absolute stereochemistry consistent with all ʟ-amino acids (Figure 5). We next explored the GNPS network for new cyclopeptide alkaloids from C. americanus. We previously noted the presence

• analysis, which confirmed the presence of all ʟ-Phe in the structure (Supporting Information File 1, Figure S27). Beyond this, multiple other features in the GNPS network appeared to represent new molecules for C. americanus (Supporting Information File 1, Figures S4–S11). Xylopyrine-C was previously

Predicting bond dissociation energies of cyclic hypervalent halogen reagents using DFT calculations and graph attention network model

• Yingbo Shao,
• Zhiyuan Ren,
• Zhihui Han,
• Li Chen,
• Yao Li and
• Xiao-Song Xue

Beilstein J. Org. Chem. 2024, 20, 1444–1452, doi:10.3762/bjoc.20.127

• results of this study could aid in estimating the chemical stability and functional group transfer capabilities of hypervalent bromine(III) and chlorine(III) reagents, thereby facilitating their development. Keywords: BDE; cyclic hypervalent halogen reagents; DFT calculation; graph attention network

• DFT calculations for predicting key properties of organic molecules such as BDE, nucleophilicity, and electrophilicity [48][49][50][51][52][53][54][55][56][57][58][59][60]. Recently, applications of the Elastic Net model with Avalon fingerprints [55] and the deployment of artificial neural network

• reagents, we can obtain a rough estimation of the BDEs for others with different halogen centers. With these homolytic and heterolytic BDEs in hand, we next attempted to develop a predictive model for BDEs of hypervalent halogen compounds using machine learning algorithms. Graph attention network (GAT) [85

Synthesis and physical properties of tunable aryl alkyl ionic liquids based on 1-aryl-4,5-dimethylimidazolium cations

• Stefan Fritsch and
• Thomas Strassner

Beilstein J. Org. Chem. 2024, 20, 1278–1285, doi:10.3762/bjoc.20.110

• blocked at the C2 position [33]. The use of a substituent at the C2 position was found to have a strong influence on the properties of these ionic liquids due to changes in the hydrogen-bonding network. Here, we investigate the properties of TAAILs based on the 1-aryl-4,5-dimethylimidazolium cation. It is