Dirhamnolipid ester – formation of reverse wormlike micelles in a binary (primerless) system

• David Liese,
• Hans Henning Wenk,
• Xin Lu,
• Jochen Kleinen and
• Gebhard Haberhauer

Beilstein J. Org. Chem. 2020, 16, 2820–2830, doi:10.3762/bjoc.16.232

• freshly cleaned mica surface (Plano) and waiting for 12 h. The AFM data were analyzed using the Gwyddion-2.53 software. Rheological measurements The rheological data were obtained using an Anton Paar MCR 301 rheometer equipped with a cylindrical geometry (CC27 – measuring unit). The temperature was

Synthesis and investigation of quadruplex-DNA-binding, 9-O-substituted berberine derivatives

• Jonas Becher,
• Daria V. Berdnikova,
• Heiko Ihmels and
• Christopher Stremmel

Beilstein J. Org. Chem. 2020, 16, 2795–2806, doi:10.3762/bjoc.16.230

• relevant factors that affect the affinity and selectivity of such ligands. Experimental Equipment NMR data were recorded with a Varian VNMR-S600 spectrometer [600 MHz (1H), 150 MHz (13C)] at 35 °C. NMR spectra were processed with the software ACD/NMR Processor Academic Version 12.01 and are referenced to

Synthesis of purines and adenines containing the hexafluoroisopropyl group

• Viacheslav Petrov,
• Rebecca J. Dooley,
• Alexander A. Marchione,
• Elizabeth L. Diaz,
• Brittany S. Clem and
• William Marshall

Beilstein J. Org. Chem. 2020, 16, 2739–2748, doi:10.3762/bjoc.16.224

• were determined using the peak fitting utility in ACDLabs Spectrus Processor software (v. 2018.1.1). X-ray diffraction X-ray data for 7a, 2a, 3a, 4a, and 6a were collected at −100 °C using a Bruker APEX-II CCD system equipped with a sealed tube molybdenum source and a graphite monochromator. The

• structures were solved and refined using the SHELXTL software package [26], refinement by full-matrix least squares on F2, scattering factors from [25]. Crystallographic data (excluding structure factors) for the structures in this paper have been deposited with the Cambridge Crystallographic Data Center as

• supplementary publication nos. CCDC #1998565−1998569. Computational chemistry Computational optimization of 8a and 8b structures was performed with Gaussian 9 software. Density functional theory at the B3LYP level, with a 6-311g++ basis set (Co phase) was employed. Reaction of purine (2) and 1 A mixture of 1.2

Vicinal difluorination as a C=C surrogate: an analog of piperine with enhanced solubility, photostability, and acetylcholinesterase inhibitory activity

• Yuvixza Lizarme-Salas,
• Alexandra Daryl Ariawan,
• Ranjala Ratnayake,
• Hendrik Luesch,
• Angela Finch and
• Luke Hunter

Beilstein J. Org. Chem. 2020, 16, 2663–2670, doi:10.3762/bjoc.16.216

• . This was achieved by performing a DFT study in the Gaussian software, using the M06-2X level of theory with the 6-311+G(d,p) basis set, parameters similar to those employed by Linclau and co-workers for their studies of vicinal difluoro systems [22]. A set of starting structures of 2 was generated by

A consensus-based and readable extension of Linear Code for Reaction Rules (LiCoRR)

• Benjamin P. Kellman,
• Yujie Zhang,
• Emma Logomasini,
• Eric Meinhardt,
• Karla P. Godinez-Macias,
• Austin W. T. Chiang,
• James T. Sorrentino,
• Chenguang Liang,
• Bokan Bao,
• Yusen Zhou,
• Sachiko Akase,
• Isami Sogabe,
• Thukaa Kouka,
• Elizabeth A. Winzeler,
• Iain B. H. Wilson,
• Matthew P. Campbell,
• Sriram Neelamegham,
• Frederick J. Krambeck,
• Kiyoko F. Aoki-Kinoshita and
• Nathan E. Lewis

Beilstein J. Org. Chem. 2020, 16, 2645–2662, doi:10.3762/bjoc.16.215

• of reactions possible, nor open-source software available to implement the parsing of such rules. Representing reaction rules in Linear Code is not easy because of a few ambiguous cases not completely described in the initial Linear Code paper. Subsequent studies, therefore, have developed their own

• . Ideally, succinct, readable, and comprehensible reaction rules sets will be sufficiently standardized, like XML-type representations, so that they will be “interoperable” across multiple modeling software so that models can be “reused,” reproduced, validated, and extended across labs. Toward encouraging

Particle size effect in the mechanically assisted synthesis of β-cyclodextrin mesitylene sulfonate

• Stéphane Menuel,
• Sébastien Saitzek,
• Eric Monflier and
• Frédéric Hapiot

Beilstein J. Org. Chem. 2020, 16, 2598–2606, doi:10.3762/bjoc.16.211

• ). The spherical morphology could be deduced from the Solidicity program incorporated in the ImageJ software [22]. However, further grinding up to 297 min did not lead to further changes in either the morphology or the size of the β-CD particles (Figure 1f). From the SEM images and the inspection with

• the ImageJ software, we also calculated the granulometric composition of the β-CD particles against the grinding time (Figure 2). While a rapid decrease in size was observed over the first 10 min of grinding, a slight variation on the particle size was noticed when the grinding of β-CD was left to

• . From the SEM images and using the ImageJ software, we were able to determine the size of the β-CD particles and the calculated Feret mean diameter (mean value of the Feret diameters over all orientations, i.e., 0–180°) are collected in Table 1. BET analysis The β-CD particle size was also confirmed by

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

• software available to assist with the building up of glycosylated biomolecular systems. As opposed to manual preparation, there are glycan-specific tools and toolkits such as doGlycans [27], Glycosylator [28], and online platforms such as GLYCAM-WEB [29] and CHARMM-GUI [30]. In this work, the CHARMM-GUI

Leveraging glycomics data in glycoprotein 3D structure validation with Privateer

• Haroldas Bagdonas,
• Daniel Ungar and
• Jon Agirre

Beilstein J. Org. Chem. 2020, 16, 2523–2533, doi:10.3762/bjoc.16.204

• initiatives have stored results in publicly available databases, some of which can be accessed through API interfaces. In the present work, we will describe how the Privateer carbohydrate structure validation software has been extended to harness results from glycomics projects, and its use to greatly improve

• ], glycosidic linkage stereochemistry [14] and torsion [15][16], and most recently, ring conformation [17]. Most of these issues have now been addressed as part of ongoing efforts to provide better software tools for structure determinations of glycoproteins, although the most difficult cases remain hard to

• atomic model will be expected as the final result of the study. Modelling of carbohydrates into 3D maps can be more complex than modelling proteins [33], although recent advances in software are closing the gap [34][35][36]. However, to date it remains true that most model building software is protein

Conformational preferences of fluorine-containing agrochemicals and their implications for lipophilicity prediction

• Daniela Rodrigues Silva,
• Joyce K. Daré and
• Matheus P. Freitas

Beilstein J. Org. Chem. 2020, 16, 2469–2476, doi:10.3762/bjoc.16.200

• involving organofluorine agrochemicals, for example, towards modeling herbicidal activity, and/or for environmental risk assessment. Computational Details The conformational search of agrochemicals I–VII was performed at the ωB97X-D/6-31G(d,p) [16][17] level of theory using the Spartan’18 software [30]. The

• lowest energy minimum conformation of each compound was then reoptimized and the dipole moment determined using a higher level of theory, ωB97X-D/6-311++G(d,p) [16][18], in the Gaussian 09 software [31]. The geometries and dipole moments for compounds 1–11 were calculated at the same level, which has

Computational tools for drawing, building and displaying carbohydrates: a visual guide

• Kanhaya Lal,
• Rafael Bermeo and
• Serge Perez

Beilstein J. Org. Chem. 2020, 16, 2448–2468, doi:10.3762/bjoc.16.199

• carried out in structural glycobiology, typically using various software. In this perspective article, we outline developments in the computational tools for the sketching, visualisation and modelling of glycans. The article also provides details on the standard representation of glycans, and

• . Consequently, unless the interface is rather straightforward and the building dynamic is well-designed, the software would be too difficult to use effectively. The ideal carbohydrate builder pick would also allow liberty for the user in terms of levels of precision since it has to fit every level of complexity

• list of pre-built core N- and O-linked carbohydrate moieties, which are usually present in glycoproteins structures, can be used as a template for further modification. A shortlist of glycan epitopes is also included providing templates for drawing more complex molecules. The software uses the Symbol

Styryl-based new organic chromophores bearing free amino and azomethine groups: synthesis, photophysical, NLO, and thermal properties

• Anka Utama Putra,
• Deniz Çakmaz,
• Nurgül Seferoğlu,
• Alberto Barsella and
• Zeynel Seferoğlu

Beilstein J. Org. Chem. 2020, 16, 2282–2296, doi:10.3762/bjoc.16.189

• Shimadzu 1800 UV–vis spectrophotometer in Britton–Robinson buffer solutions [63] with pH values ranging from 5.5 to 11 at room temperature (25 °C). The pKa values were obtained using the Origin software by recording the curve data. Computational methods The geometries of the dyes in their ground states

Tools for generating and analyzing glycan microarray data

• Akul Y. Mehta,
• Jamie Heimburg-Molinaro and
• Richard D. Cummings

Beilstein J. Org. Chem. 2020, 16, 2260–2271, doi:10.3762/bjoc.16.187

• alignments are usually done by hand with assistance from the scanner software, which usually offers partial alignment algorithms based on background intensities. The spot diameters are also adjusted as some glycans just form smaller spots in comparison to others. Spots where information is not reliable due

• to extraneous factors such as poor printing due to a flaw in the surface, spot overlap/fusion with adjacent spot or presence of dust particles are flagged with a “bad” (or some numeric value) flag, so as to be disregarded in the data processing. The software then provides a results file as an output

• . CarbArrayART: Status: Development (available for testing upon request). Description: CarbArrayART is a software in development for the storage, processing and presentation of microarray data [38][39]. It is based on the GRITS Toolbox (classically used for mass spectrometry data) [40]. Features of CarbArrayART

Naphthalene diimide bis-guanidinio-carbonyl-pyrrole as a pH-switchable threading DNA intercalator

• Poulami Jana,
• Filip Šupljika,
• Carsten Schmuck and
• Ivo Piantanida

Beilstein J. Org. Chem. 2020, 16, 2201–2211, doi:10.3762/bjoc.16.185

• ). Origin 7.0 software, supplied by the manufacturer, was used for data analysis. During the titration of ct-DNA, d: poly(rA)–poly(rU), poly(dAdT)–poly(dAdT), and poly(dGdC)–poly(dGdC) with the compound 4, one aliquot of 2 μL and 27 aliquots of 10 μL of 4 (c = 1.0 × 10−4 M) were injected from rotating

• silicon cantilevers (AC-160TS, Olympus) a NanoDrive controller with an Innova scanning probe microscope (Veeco, Germany, Mannheim) was used. The analysis of the AFM images was carried out by use of the Gwyddion (version 2.19) software. DLS experimental All measurements were carried out using a

• compound 4 (5–100 μM) were prepared and filtered prior to measurement through 0.20 μm nylon filters. The autocorrelation functions of the backscattered light fluctuations were analysed with the DTS 6.20 software from Malvern providing the hydrodynamic diameter (Z-average), polydispersity, and size

GlypNirO: An automated workflow for quantitative N- and O-linked glycoproteomic data analysis

• Toan K. Phung,
• Cassandra L. Pegg and
• Benjamin L. Schulz

Beilstein J. Org. Chem. 2020, 16, 2127–2135, doi:10.3762/bjoc.16.180

• automated software pipeline which integrates the complementary outputs of Byonic and Proteome Discoverer to allow high-throughput automated quantitative glycoproteomic data analysis. The output of GlypNirO is clearly structured, allowing manual interrogation, and is also appropriate for input into diverse

• acquisition methods [10]. Progress in MS technology in particular has enabled deep and sensitive measurement of highly complex glycoproteomes, generating large amounts of high quality data [11]. With that comes the need for robust and automated workflows for extracting meaningful results. Numerous software

• are few efficient, robust, and automated workflows for glycopeptide quantification. There are several freely available software programs for quantitative label-free glycoproteomics using MS1 or data-dependent acquisition. These include LaCyTools [17], MassyTools [18], and GlycoSpectrumScan [19], which

Muyocopronones A and B: azaphilones from the endophytic fungus Muyocopron laterale

• Ken-ichi Nakashima,
• Junko Tomida,
• Tomoe Tsuboi,
• Yoshiaki Kawamura and
• Makoto Inoue

Beilstein J. Org. Chem. 2020, 16, 2100–2107, doi:10.3762/bjoc.16.177

• –7.62 (m, 10H, phenyl groups of MTPAs). Computational methods Calculation of the ECD spectra were performed using CONFLEX 8, Gaussian 16, and SpecDis software as described previously [13][14]. Geometry optimizations were performed using DFT at the CAM-B3LYP/6-311+G(d,p) level of theory, while TDDFT

Clustering and curation of electropherograms: an efficient method for analyzing large cohorts of capillary electrophoresis glycomic profiles for bioprocessing operations

• Ian Walsh,
• Matthew S. F. Choo,
• Sim Lyn Chiin,
• Amelia Mak,
• Shi Jie Tay,
• Pauline M. Rudd,
• Yang Yuansheng,
• Andre Choo,
• Ho Ying Swan and
• Terry Nguyen-Khuong

Beilstein J. Org. Chem. 2020, 16, 2087–2099, doi:10.3762/bjoc.16.176

• similar groups, making it easier to define peaks manually. Open-source software is then used to determine peak areas of the manually defined peaks. We successfully applied this semi-automated method to a dataset (containing 391 glycoprofiles) of monoclonal antibody biosimilars from a bioreactor

• databases and software (among others) are discussed in a recent review [15]. A long standing problem associated with the analysis of large sets of electrophoretic data generated during bioprocessing is inevitably the drift of the peak migration time and area under the curve pertaining to glycan structures

• small peaks and peaks that can lose their “Gaussian-ness” when multiple peaks migrate close together. This is especially true for large sets of diverse CE electropherograms collected over days or months under varied conditions. Consequently, they are often processed with automated software using

How and why plants and human N-glycans are different: Insight from molecular dynamics into the “glycoblocks” architecture of complex carbohydrates

• Carl A. Fogarty,
• Aoife M. Harbison,
• Amy R. Dugdale and
• Elisa Fadda

Beilstein J. Org. Chem. 2020, 16, 2046–2056, doi:10.3762/bjoc.16.171

• , namely the three gg, gt and tg conformations for each 1-6 torsion. The topology file for each structure was obtained using tleap [31], with parameters from the GLYCAM06-j1 [32] for the carbohydrate atoms and with TIP3P for water molecules [33]. All calculations were run with the AMBER18 software package

• cpptraj [31] and visually analysed with the Visual Molecular Dynamics (VMD) software package [34]. Root mean square deviation (RMSD) and torsion angles values were measured using VMD. A density-based clustering method was used to calculate the populations of occupied conformations for each torsion angle

Automated high-content imaging for cellular uptake, from the Schmuck cation to the latest cyclic oligochalcogenides

• Rémi Martinent,
• Javier López-Andarias,
• Dimitri Moreau,
• Yangyang Cheng,
• Naomi Sakai and
• Stefan Matile

Beilstein J. Org. Chem. 2020, 16, 2007–2016, doi:10.3762/bjoc.16.167

• data produced per day. The high number of images generated by the automated microscope cannot be analysed manually, and therefore need to go through a completely automated analysis pipeline. For this purpose, dedicated software is used to first create specific masks that detect the objects of interest

Models of necessity

• Timothy Clark and
• Martin G. Hicks

Beilstein J. Org. Chem. 2020, 16, 1649–1661, doi:10.3762/bjoc.16.137

• Applied to Synthetic Analysis) [52], or implement an automatic ML approach that encodes the reactions based on a training set, as pioneered by Gelernter [53][54]. Latterly, hard- and software improvements have made advances possible (see, for example [55][56][57]), as has an unprecedented effort in the

• ], developing a ML-suitable model for intermolecular interactions is feasible. As noted above, old models such as Gasteiger–Marsili [38][39] charges or Hammett constants [59] have been used in recent applications. This development ignores the immense improvements in hard- and software of the last four decades

Rearrangement of o-(pivaloylaminomethyl)benzaldehydes: an experimental and computational study

• Csilla Hargitai,
• Györgyi Koványi-Lax,
• Tamás Nagy,
• Péter Ábrányi-Balogh,
• András Dancsó,
• Gábor Tóth,
• Judit Halász,
• Angéla Pandur,
• Gyula Simig and
• Balázs Volk

Beilstein J. Org. Chem. 2020, 16, 1636–1648, doi:10.3762/bjoc.16.136

• ) spectrometer equipped with a Prodigy cryo-probehead. The pulse programs were taken from the Bruker software library (TopSpin 3.5) and full 1H and 13C assignments were achieved with widely accepted strategies [34][35]. 1H NMR assignments were accomplished using general knowledge of chemical shift dispersion

Five-component, one-pot synthesis of an electroactive rotaxane comprising a bisferrocene macrocycle

• Natalie Lagesse,
• Luca Pisciottani,
• Maxime Douarre,
• Pascale Godard,
• Brice Kauffmann,
• Vicente Martí-Centelles and
• Nathan D. McClenaghan

Beilstein J. Org. Chem. 2020, 16, 1564–1571, doi:10.3762/bjoc.16.128

• = 0.0450, Rsigma = 0.0402) which were used in all calculations. The final R1 was 0.0454 (I > 2σ(I)) and wR2 was 0.1180 (all data). CCDC Deposition Number 1968472. Molecular modelling Monte Carlo conformational searches with the MMFF force field were carried out with the Spartan ‘18 software [30]. For each

Heterogeneous photocatalysis in flow chemical reactors

• Christopher G. Thomson,
• Ai-Lan Lee and
• Filipe Vilela

Beilstein J. Org. Chem. 2020, 16, 1495–1549, doi:10.3762/bjoc.16.125

In silico rationalisation of selectivity and reactivity in Pd-catalysed C–H activation reactions

• Liwei Cao,
• Mikhail Kabeshov,
• Steven V. Ley and
• Alexei A. Lapkin

Beilstein J. Org. Chem. 2020, 16, 1465–1475, doi:10.3762/bjoc.16.122

• computational data, a threshold to distinguish between two possible reaction mechanisms was established. Computational Methods The NWChem, an open source software package, was used for the DFT calculations. It is easily scalable and designed to solve large scientific computational problems efficiently employing

One-step route to tricyclic fused 1,2,3,4-tetrahydroisoquinoline systems via the Castagnoli–Cushman protocol

• Aleksandar Pashev,
• Nikola Burdzhiev and
• Elena Stanoeva

Beilstein J. Org. Chem. 2020, 16, 1456–1464, doi:10.3762/bjoc.16.121

• . The APEX 2 v.2014.11.0 software was used for all data processing [53]. The structure was solved and refined with SHELX [54] programs, ShelXT and ShelXL by using OLEX 2 software [55]. Hydrogen atoms were placed at idealized positions and refined. Crystallographic data (excluding structure factors) for

[3 + 2] Cycloaddition with photogenerated azomethine ylides in β-cyclodextrin

• Margareta Sohora,
• Leo Mandić and
• Nikola Basarić

Beilstein J. Org. Chem. 2020, 16, 1296–1304, doi:10.3762/bjoc.16.110

• analysis using WinEQNMR software [51]. The titration was performed at 25 °C. NMR titrations with AN A solution of 2@β-CD (prepared by mixing 2 in the concentration of 2.71 mM with β-CD in the concentration of 8.20 mM), or 3@β-CD (prepared by mixing 3 in the concentration of 1.54 mM with β-CD in the

• concentration of 20.5 mM) in CD3CN/D2O (3:7 v/v, 1.0 mL) was titrated with acrylonitrile (AN). After each addition of AN, an 1H NMR spectrum was recorded. The changes of chemical shifts depending on the AN concentration were processed by nonlinear regression analysis using WinEQNMR software [51]. The titration