Acyclic cucurbit[n]uril bearing alkyl sulfate ionic groups

• Christian Akakpo,
• Peter Y. Zavalij and
• Lyle Isaacs

Beilstein J. Org. Chem. 2025, 21, 717–726, doi:10.3762/bjoc.21.55

• Figure 6a was integrated and then plotted as ΔH versus molar ratio in Figure 7b. The ΔH versus molar ratio data was then fitted to the single-set-of-sites binding model in the PEAQ ITC data analysis software which delivered Ka = (6.49 ± 0.10) × 105 M−1 and ΔH = −7.82 ± 0.02 kcal mol−1 for the C1·CHDA

• requires that the Ka and ΔH values for the host·competitor complexes have been previously determined and used as known inputs to the competitive binding model in the PEAQ data analysis software. To maximize the heat evolved in the competitive ITC titrations, the host·competitor and host·tight guest

• ) and fitted to the competitive binding model in the PEAQ ITC data analysis software to determine Ka = (2.47 ± 0.06) × 108 M−1 and ΔH = −12.43 ± 0.02 kcal mol−1 for the C1·Me6PXDA complex. The Ka and ΔH values for the remaining C1·guest and M1·guest complexes were determined by analogous direct or

Asymmetric synthesis of fluorinated derivatives of aromatic and γ-branched amino acids via a chiral Ni(II) complex

• Maurizio Iannuzzi,
• Thomas Hohmann,
• Michael Dyrks,
• Kilian Haoues,
• Katarzyna Salamon-Krokosz and
• Beate Koksch

Beilstein J. Org. Chem. 2025, 21, 659–669, doi:10.3762/bjoc.21.52

• ) was used. MeCN/MeOH/H2O mixture with 50 mM formic acid and 25 mM diethylamine was used as eluent. A flow rate of 0.5 mL/min was applied and the detection of the respective compounds occurred at 280 nm. Data analysis was carried out with the EZChrom ELITE software (version 3.3.2 SP2, Agilent). Ni(II

Synthesis and characterizations of highly luminescent 5-isopropoxybenzo[rst]pentaphene

• Islam S. Marae,
• Jingyun Tan,
• Rengo Yoshioka,
• Zakaria Ziadi,
• Eugene Khaskin,
• Serhii Vasylevskyi,
• Ryota Kabe,
• Xiushang Xu and
• Akimitsu Narita

Beilstein J. Org. Chem. 2025, 21, 270–276, doi:10.3762/bjoc.21.19

• and support provided by the Instrumental Analysis Section and the Scientific Computing and Data Analysis Section of Research Support Division at OIST. We thank Dr. Liliia Moshniaha from Organic Optoelectronics Unit at OIST for her support in optical measurements. Funding This work was financially

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

• MassLynx ver. 4.1 and data analysis was done using Waters OpenLynx browser ver. 4.1. Solvents were commercial HPLC grade and used without further purification. The substrates 2a, 7a, and 8a were commercially available and used without further purification. The substituted β-nitrostyrenes 1a and 3a–6a were

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

• experimental workflow. In Table 1, we describe the subtle disparities for clarity and reference. Self-optimizing HTE throughput platforms require in-line and/or online characterization as well as data analysis and processing for rapid optimization of organic reactions. Chromatographic (i.e., HPLC, GC) and

• chemical reactions. In the current review, we focus on the high-throughput data processing that complements the HTE platforms for rapid optimization of organic reactions. Although multivariate data analysis has frequently been adopted in analytical chemistry for rapid data processing, the availability of

• and timely data analysis, facilitating seamless real-time monitoring of the hydrolysis of 16. The final hydrogenation step was monitored by an in-line IR probe. The spectral data was processed using a partial least squares regression model and quantified. An online UHPLC was used to analyze the final

Interaction of a pyrene derivative with cationic [60]fullerene in phospholipid membranes and its effects on photodynamic actions

• Hayato Takagi,
• Çetin Çelik,
• Ryosuke Fukuda,
• Qi Guo,
• Tomohiro Higashino,
• Hiroshi Imahori,
• Yoko Yamakoshi and
• Tatsuya Murakami

Beilstein J. Org. Chem. 2024, 20, 2732–2738, doi:10.3762/bjoc.20.231

• free PyBA. Data analysis, including calculation of the phase transition temperature, was performed using the MicroCal PEAQ-DSC Software. UV–vis absorption measurement UV–vis spectra of DMPC liposomes (1 mM DMPC) with or without catC60 or C60 were measured in PBS(–) using a UV-3600 Plus absorption

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

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

• , the authors developed a separate model to gain a sufficiently interpretable model, finding that some parameters remain important throughout the different subsets. This example demonstrates both the strength of careful data analysis and the intricacies of dealing with chemical reactivity data. The

• optimization algorithm allowed them to discover multiple trade-off optima, enabling a scientist to select the ideal catalyst based on the specific requirements of catalytic activity and selectivity, while still accounting for catalyst generality through design of the objectives. Noticeably, data analysis

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

Hetero-polycyclic aromatic systems: A data-driven investigation of structure–property relationships

• Sabyasachi Chakraborty,
• Eduardo Mayo Yanes and
• Renana Gershoni-Poranne

Beilstein J. Org. Chem. 2024, 20, 1817–1830, doi:10.3762/bjoc.20.160

• relationships require more advanced data-analysis tools, and we are currently leveraging different machine learning and deep learning techniques to tap the full potential of the COMPAS-2 dataset. A) The building blocks used in the COMPAS-2 datasets. B) Possible annulation types formed when combining the

Ligand effects, solvent cooperation, and large kinetic solvent deuterium isotope effects in gold(I)-catalyzed intramolecular alkene hydroamination

• Ruichen Lan,
• Brock Yager,
• Yoonsun Jee,
• Cynthia S. Day and
• Amanda C. Jones

Beilstein J. Org. Chem. 2024, 20, 479–496, doi:10.3762/bjoc.20.43

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

• ]+ at m/z 773.4338, calculated for C41H57N8O7+, m/z 773.4345, Δ 0.9 ppm; [M + Na]+ at m/z 795.4162, calculated for C41H56N8O7Na+, m/z 795.4164, Δ 0.3 ppm) and NMR data analysis, corresponding to eighteen indices of hydrogen deficiency. Its UV spectrum exhibited absorption maxima at λmax 219 and 279 nm

Studying specificity in protein–glycosaminoglycan recognition with umbrella sampling

• Mateusz Marcisz,
• Sebastian Anila,
• Margrethe Gaardløs,
• Martin Zacharias and
• Sergey A. Samsonov

Beilstein J. Org. Chem. 2023, 19, 1933–1946, doi:10.3762/bjoc.19.144

• would be significantly smaller. Data analysis and its graphical representation were done with the R-package [49] and VMD [50]. Results In total, 14 US simulations were performed to investigate the specificity of GAG–protein interactions, capabilities of US simulations to dissociate and reassociate

GlAIcomics: a deep neural network classifier for spectroscopy-augmented mass spectrometric glycans data

• Thomas Barillot,
• Baptiste Schindler,
• Baptiste Moge,
• Elisa Fadda,
• Franck Lépine and
• Isabelle Compagnon

Beilstein J. Org. Chem. 2023, 19, 1825–1831, doi:10.3762/bjoc.19.134

• appealing candidates to address this challenge. They have been used for mass spectrometry data analysis since the 2000’s [6] and the idea of using them on vibrational spectra goes back to the early 90’s [7]. Support vector machines (SVM) and decision tree ensemble methods were benchmarked on infrared

• single spectrum is arbitrarily chosen by the operator and serves as reference for all future analyses. The latest MS–IR developments brought the data collection down to few seconds [5]. This is a considerable step towards high throughput carbohydrate analysis, which must be accompanied by fast data

• analysis, thus excluding manual interpretation. Besides, in the prospective of deploying the technology beyond the molecular spectroscopy community, it is essential to develop an automated, reliable, and robust strategy for the analysis of the spectroscopic data. Machine learning methods appear to be

Benzoimidazolium-derived dimeric and hydride n-dopants for organic electron-transport materials: impact of substitution on structures, electrochemistry, and reactivity

• Swagat K. Mohapatra,
• Khaled Al Kurdi,
• Samik Jhulki,
• Georgii Bogdanov,
• John Bacsa,
• Maxwell Conte,
• Tatiana V. Timofeeva,
• Seth R. Marder and
• Stephen Barlow

Beilstein J. Org. Chem. 2023, 19, 1651–1663, doi:10.3762/bjoc.19.121

• (DOE) under Contract No. DE-AC36-08GO28308; specifically, some of the data analysis was carried out as part of a Laboratory Directed Research and Development (LDRD) Program at NREL. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S

Unravelling a trichloroacetic acid-catalyzed cascade access to benzo[f]chromeno[2,3-h]quinoxalinoporphyrins

• Chandra Sekhar Tekuri,
• Pargat Singh and
• Mahendra Nath

Beilstein J. Org. Chem. 2023, 19, 1216–1224, doi:10.3762/bjoc.19.89

• . After workup and chromatographic purification, the isolated product was characterized based on spectral data analysis as copper(II) benzo[f]quinoxalinoporphyrin intermediate 17. Further, porphyrin 17 reacted with benzaldehyde and dimedone in chloroform containing 20 mol% trichloroacetic acid at 65 °C to

• copper(II) porphyrins 3–8. Finally, the structures of all newly synthesized benzo[f]chromeno[2,3-h]quinoxalinoporphyrins 3–16 and benzo[f]quinoxalinoporphyrin 17 were assigned on the basis of IR, 1H and 13C NMR, and HRMS data analysis. Photophysical characteristics The UV–vis spectra of the newly

Phenanthridine–pyrene conjugates as fluorescent probes for DNA/RNA and an inactive mutant of dipeptidyl peptidase enzyme

• Josipa Matić,
• Tana Tandarić,
• Marijana Radić Stojković,
• Filip Šupljika,
• Zrinka Karačić,
• Ana Tomašić Paić,
• Lucija Horvat,
• Robert Vianello and
• Lidija-Marija Tumir

Beilstein J. Org. Chem. 2023, 19, 550–565, doi:10.3762/bjoc.19.40

• calorimetry (ITC) titrations were performed on a Malvern PEAQ-ITC microcalorimeter (MicroCal, Inc.,Northampton, MA, USA). MicroCal PEAQ-ITC analysis software, supplied by the manufacturer, was used for data analysis. Polynucleotides were purchased as noted: calf thymus (ct)-DNA, poly dAdT–poly dAdT, poly dGdC

Synthesis and characterisation of new antimalarial fluorinated triazolopyrazine compounds

• Kah Yean Lum,
• Jonathan M. White,
• Daniel J. G. Johnson,
• Vicky M. Avery and
• Rohan A. Davis

Beilstein J. Org. Chem. 2023, 19, 107–114, doi:10.3762/bjoc.19.11

• ) triazolopyrazine scaffold (Series 4). The structures of all analogues were fully characterised by NMR, UV and MS data analysis; three triazolopyrazines were confirmed by X-ray crystal structure analysis. The inhibitory activity of all compounds against the growth of the malaria parasite Plasmodium falciparum (3D7

Using UHPLC–MS profiling for the discovery of new sponge-derived metabolites and anthelmintic screening of the NatureBank bromotyrosine library

• Sasha Hayes,
• Aya C. Taki,
• Kah Yean Lum,
• Joseph J. Byrne,
• Merrick G. Ekins,
• Robin B. Gasser and
• Rohan A. Davis

Beilstein J. Org. Chem. 2022, 18, 1544–1552, doi:10.3762/bjoc.18.164

• marine natural product, ianthesine E (2). The chemical structure of the new compound was determined following detailed spectroscopic and spectrometric data analysis. These two compounds (1 and 2) along with seven previously reported marine bromotyrosine alkaloids from the NatureBank open access library

• -scale extraction and isolation work. Small-scale (300 mg) extraction of the abundant 39 sponge samples followed by UHPLC–MS and data analysis led to the prioritisation of several extracts for follow-up large-scale chemical investigations (see Figure S1 in Supporting Information File 1 for all UHPLC–MS

Enantioselective total synthesis of putative dihydrorosefuran, a monoterpene with an unique 2,5-dihydrofuran structure

• Irene Torres-García,
• Josefa L. López-Martínez,
• Rocío López-Domene,
• Manuel Muñoz-Dorado,
• Ignacio Rodríguez-García and
• Miriam Álvarez-Corral

Beilstein J. Org. Chem. 2022, 18, 1264–1269, doi:10.3762/bjoc.18.132

• cyclization is a simple and efficient strategy for the preparation of the 2,5-dihydrofuran moiety present in many natural products. In fact, we have achieved the total synthesis of the 2,5-dihydrofuran structure 1. After systematic data analysis of our prepared compound and those in the literature, it can be

Terpenoids from Glechoma hederacea var. longituba and their biological activities

• Dong Hyun Kim,
• Song Lim Ham,
• Zahra Khan,
• Sun Yeou Kim,
• Sang Un Choi,
• Chung Sub Kim and
• Kang Ro Lee

Beilstein J. Org. Chem. 2022, 18, 555–566, doi:10.3762/bjoc.18.58

• reported literature and NOESY data analysis. Comparison with 1H NMR of 1β,10α;4α,5β-diepoxy-8α-isobutoxy-glechomanolide (8α-DIG) and 1β,10α;4α,5β-diepoxy-8β-isobutoxy-glechomanolide (8β-DIG) of reference [8], the two epimers similar to 1 showed a significant difference in the chemical shift of H-5 (8α, δH

Regioselective synthesis of methyl 5-(N-Boc-cycloaminyl)-1,2-oxazole-4-carboxylates as new amino acid-like building blocks

• Jolita Bruzgulienė,
• Greta Račkauskienė,
• Aurimas Bieliauskas,
• Vaida Milišiūnaitė,
• Miglė Dagilienė,
• Gita Matulevičiūtė,
• Vytas Martynaitis,
• Sonata Krikštolaitytė,
• Frank A. Sløk and
• Algirdas Šačkus

Beilstein J. Org. Chem. 2022, 18, 102–109, doi:10.3762/bjoc.18.11

• structural assignment of regiospecific compound 4a was readily deduced via detailed spectral data analysis. The IR spectrum of 4a contained characteristic absorption bands such as 1723 (C=O, ester), and 1687 (C=O, Boc) cm−1. The 1H NMR spectrum of compound 4a revealed a characteristic resonance for the Boc

Chemical and chemoenzymatic routes to bridged homoarabinofuranosylpyrimidines: Bicyclic AZT analogues

• Sandeep Kumar,
• Jyotirmoy Maity,
• Banty Kumar,
• Sumit Kumar and
• Ashok K. Prasad

Beilstein J. Org. Chem. 2022, 18, 95–101, doi:10.3762/bjoc.18.10

• established on the basis of 1H,1H-COSY and NOESY NMR spectral data analysis of nucleoside 9a (Figure 2). Herein, cross peaks were observed in the NOESY spectrum of compound 9a due to the spatial interaction of the C6′ methylene protons resonating at δ 3.41 with the C3′ proton resonating at δ 4.73 and the C5

• , 13C NMR, 1H,1H-COSY NMR, 1H,13C-HETCOR NMR, NOESY NMR and HRMS) data analysis. The structures of known compounds 11 and 17 were further confirmed by comparison of their physical and spectral data with those reported in literature [28]. Conclusion The efficiency of Lipozyme® TL IM was discovered for

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

• MS data analysis tools for glycoproteomic characterization and quantification. The article by Walsh et al. [11], on the other hand, addresses the problems of an irreproducible retention time and peak integration in antibody glycomic analysis using CE, thus allowing small quantitative differences to

In-depth characterization of self-healing polymers based on π–π interactions

• Josefine Meurer,
• Julian Hniopek,
• Johannes Ahner,
• Michael Schmitt,
• Jürgen Popp,
• Stefan Zechel,
• Kalina Peneva and
• Martin D. Hager

Beilstein J. Org. Chem. 2021, 17, 2496–2504, doi:10.3762/bjoc.17.166

• controlled program was developed, which mainly uses the well-established data analysis library pandas as well as the SciPy and NumPy libraries for linear algebra, integration and interpolation. Polymer synthesis The polymer synthesis was adapted from literature [23] and is reported briefly in the following