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

• , thus leading to long lead times and inefficient personnel allocation. To overcome these issues, Sagmeister et al. [72] developed a dual modelling approach using a single platform that seamlessly integrates the calibration of PAT, reaction optimization, kinetic modelling, and parametrizes a process

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

• in the glycosciences. A key aspect is the modelling of protein–glycan interactions. Marcisz et al. study the power of umbrella sampling in distinguishing the interactions between different glycosaminoglycans and their receptors [14]. Nieto-Fabregat et al. provide a detailed overview on computational

Deciphering the mechanism of γ-cyclodextrin’s hydrophobic cavity hydration: an integrated experimental and theoretical study

• Stiliyana Pereva,
• Stefan Dobrev,
• Tsveta Sarafska,
• Valya Nikolova,
• Silvia Angelova,
• Tony Spassov and
• Todor Dudev

Beilstein J. Org. Chem. 2024, 20, 2635–2643, doi:10.3762/bjoc.20.221

• cavity (b) and in the center of the upper rim plane. Therefore, the narrow rim with the H-bonded primary OH groups can be considered as a major attractor (anchor, hot spot) for the incoming water molecules. The identification of this hot spot location provides very useful information for modelling the γ

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

• macroscopic irradiated volume [10]. This makes the meaningful application of SAS techniques to heterogeneous systems challenging [72]. As the topological complexity of the system increases, so too does the difficulty of modelling the data. This can result in the number of modelling parameters becoming

Hypervalent iodine-mediated cyclization of bishomoallylamides to prolinols

• Smaher E. Butt,
• Konrad Kepski,
• Jean-Marc Sotiropoulos and
• Wesley J. Moran

Beilstein J. Org. Chem. 2024, 20, 2455–2460, doi:10.3762/bjoc.20.209

• was the five-membered prolinol 7a rather than the initially assigned isomeric seven-membered tetrahydrooxazepine 6 [16]. Subsequently, we set out to understand the O- versus N-chemoselectivity by DFT modelling, and to develop an effective synthetic protocol for the preparation of prolinols 7 in high

Asymmetric organocatalytic synthesis of chiral homoallylic amines

• Nikolay S. Kondratyev and
• Andrei V. Malkov

Beilstein J. Org. Chem. 2024, 20, 2349–2377, doi:10.3762/bjoc.20.201

• (trifluoromethylphenyl) group with other fluorinated aromatics (86–90) showed a gradual decrease in ee (92% ee in 90 to 68% ee in 86 and 88) depending on the degree of fluorination. Computational modelling for the 3,5-bis(trifluoromethylphenyl) catalyst 78 revealed that π-stacking interactions of the 4-pyrene group with

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

• . Keywords: catalyst design; machine learning; modelling; organocatalysis; selectivity prediction; Introduction Since the beginning of the 21st century, organocatalysts [1] have established themselves as a third group of homogeneous catalysts, next to biocatalysts [2] (enzymes) and transition metal-based

• data is paramount for predictive modelling. Depending on the problem at hand, different sources of data are available (Figure 1). Apart from experimental data, the creation of large amounts of in silico data is possible with sufficient computational resources [31][32]. While this approach is useful in

• a major challenge in organic chemistry and restricts the applicability of literature data for statistical modelling [30]. Despite emerging high-throughput experimentation (HTE) pipelines [44][45], large datasets of high-quality are still scarce. While multiple large datasets are available for

Cell-free protein synthesis with technical additives – expanding the parameter space of in vitro gene expression

• Tabea Bartsch,
• Stephan Lütz and
• Katrin Rosenthal

Beilstein J. Org. Chem. 2024, 20, 2242–2253, doi:10.3762/bjoc.20.192

• , batch-to-batch reproducibility, and reliable kinetic modelling of the system [10][11]. Furthermore, the transferability of CFPS screening results to the cells is limited but important, as in vivo production is often required for preparative scale applications [11][12]. To date, the description of CFPS

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

• simulations and analyse the corresponding results. The presented computational toolbox represents a valuable resource for researchers studying protein–glycan interactions and incorporates advanced computational methods for building, visualising and predicting protein/glycan structures, modelling protein

• tools, designed to guide the structural and conformational elucidation process, and on the application of molecular dynamic simulations to the study of proteins and glycans in free and bound states. Detailed protocols and methods for protein and glycan modelling are extensively described and links to

• files of the minimised resulting structures but also files for input to an AMBER simulation (https://glycam.org/). Notably, among the currently available interfaces for modelling oligosaccharide conformations on glycam website, one is dedicated to GAG modelling [51] (https://glycam.org/gag/). 3. CHARMM

2-Heteroarylethylamines in medicinal chemistry: a review of 2-phenethylamine satellite chemical space

• Carlos Nieto,
• Alejandro Manchado,
• Ángel García-González,
• David Díez and
• Narciso M. Garrido

Beilstein J. Org. Chem. 2024, 20, 1880–1893, doi:10.3762/bjoc.20.163

• against the H1 receptor by Straßer et al. [62]. From the set of compounds, biological assays revealed pKi values of 4.5–7.5 in human, rat, bovine, and guinea pig H1 receptor activities. Additional modelling studies via CoMFA (comparative molecular field analysis) and posterior comparison with experimental

• these SAR expansions is creating new chemical matter with appealing potency and selectivity profiles. The impact of the scaffold hopping exercise in these target biomarkers depends on the nature of the targets themselves. It is noteworthy, that the use of molecular modelling tools, especially molecular

The Groebke–Blackburn–Bienaymé reaction in its maturity: innovation and improvements since its 21st birthday (2019–2023)

• Cristina Martini,
• Muhammad Idham Darussalam Mardjan and
• Andrea Basso

Beilstein J. Org. Chem. 2024, 20, 1839–1879, doi:10.3762/bjoc.20.162

Methyltransferases from RiPP pathways: shaping the landscape of natural product chemistry

• Maria-Paula Schröder,
• Isabel P.-M. Pfeiffer and
• Silja Mordhorst

Beilstein J. Org. Chem. 2024, 20, 1652–1670, doi:10.3762/bjoc.20.147

• dimethylated [81][123]. Polytheonamides are originally derived from the marine sponge Theonella swinhoei, which is colonised by various symbiotic bacteria. The polytheonamide encoding BGC poy includes two B12-dependent rSAM C-MTs, namely PoyB and PoyC. In silico modelling and alignment of the structures of

Monitoring carbohydrate 3D structure quality with the Privateer database

• Jordan S. Dialpuri,
• Haroldas Bagdonas,
• Lucy C. Schofield,
• Phuong Thao Pham,
• Lou Holland and
• Jon Agirre

Beilstein J. Org. Chem. 2024, 20, 931–939, doi:10.3762/bjoc.20.83

• complement the growing glycan content of the PDB. Keywords: carbohydrates; database; N-glycans; N-glycosylation; polysaccharides; validation; website; Introduction Carbohydrate modelling is an important but often cumbersome stage in the macromolecular X-ray structure solution workflow. The accurate

• modelling of glycoproteins and protein–carbohydrate complexes is pivotal in understanding the complex biochemical interactions that affect the physiological function of cells [1]. Any mechanistic analysis done with finely grained approaches such as QM/MM [2] relies heavily on the correctness of the starting

• coordinates. Despite this, carbohydrate models often contain modelling inconsistencies that cannot easily be attributed to known biochemical principles [3]. These inconsistencies cannot solely be attributed to model-building inexperience, as carbohydrate model building is an inherently difficult task, which

Spatial arrangements of cyclodextrin host–guest complexes in solution studied by ¹³C NMR and molecular modelling

• Konstantin Lebedinskiy,
• Ivan Barvík,
• Zdeněk Tošner,
• Ivana Císařová,
• Jindřich Jindřich and
• Radim Hrdina

Beilstein J. Org. Chem. 2024, 20, 331–335, doi:10.3762/bjoc.20.33

• modelling and solid-state X-ray analysis, provides a detailed description of the spatial arrangement of cyclodextrin host–guest complexes in solution. The chiral cavity of the cyclodextrin molecule creates an anisotropic environment for the guest molecule resulting in a splitting of its prochiral carbon

• . The 3D densities show the spatial distribution of prochiral atoms within MD simulations. Studied host–guest complexes and splitting of guests’ prochiral carbons in their 13C NMR spectra. Molecular modelling of the host–guest complexes of compound 4 with α-CD, β-CD and γ-CD. X-ray analysis of the α-CD

Using the phospha-Michael reaction for making phosphonium phenolate zwitterions

• Matthias R. Steiner,
• Max Schmallegger,
• Larissa Donner,
• Johann A. Hlina,
• Christoph Marschner,
• Judith Baumgartner and
• Christian Slugovc

Beilstein J. Org. Chem. 2024, 20, 41–51, doi:10.3762/bjoc.20.6

• constants, we performed kinetic modelling (Supporting Information File 1, Figures S76–S81), fitting the experimental time traces by considering the second-order reaction shown in Scheme 1. The strong Michael acceptor methyl acrylate quite readily yields the corresponding zwitterion 2d in chloroform (kCHCl3

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

• explanation and prediction of GAG specificity [35]. Computational methodologies like molecular docking and molecular dynamics (MD) have proven to be successful in modelling protein–GAG interactions, particularly examining the fundamental questions related to these interactions such as their specificity, the

Application of N-heterocyclic carbene–Cu(I) complexes as catalysts in organic synthesis: a review

• Nosheen Beig,
• Varsha Goyal and
• Raj K. Bansal

Beilstein J. Org. Chem. 2023, 19, 1408–1442, doi:10.3762/bjoc.19.102

CO₂ complexation with cyclodextrins

• Cecilie Høgfeldt Jessen,
• Jesper Bendix,
• Theis Brock Nannestad,
• Heloisa Bordallo,
• Martin Jæger Pedersen,
• Christian Marcus Pedersen and
• Mikael Bols

Beilstein J. Org. Chem. 2023, 19, 1021–1027, doi:10.3762/bjoc.19.78

• and 6 containing 3,6-anhydrides in the α-cyclodextrin structure were chosen because they have a smaller cavity according to modelling. In models the diameter of 5 was measured and it was 5.0 Å and that of 6 was 4.6 Å with an α-CD height of 7.9 Å to give the cavity volumes given in Table 2. These

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

• Biochemistry, Faculty of Food Technology and Biotechnology, University of Zagreb, Croatia Laboratory for Protein Biochemistry and Molecular Modelling, Division of Organic Chemistry and Biochemistry, Ruđer Bošković Institute, Bijenička cesta 54, 10000 Zagreb, Croatia Laboratory for Molecular Plant Biology and

• modelling combined with spectrophotometric experiments revealed that in neutral and acidic buffered water solutions conjugates predominantly exist in intramolecularly stacked conformations because of the π–π stacking interaction between pyrene and phenanthridine moieties. The investigated systems exhibited

Synthesis, α-mannosidase inhibition studies and molecular modeling of 1,4-imino-ᴅ-lyxitols and their C-5-altered N-arylalkyl derivatives

• Martin Kalník,
• Sergej Šesták,
• Juraj Kóňa,
• Maroš Bella and
• Monika Poláková

Beilstein J. Org. Chem. 2023, 19, 282–293, doi:10.3762/bjoc.19.24

• the structural moiety at C-5 (ΔElinker-E)] are also compiled. Supporting Information Supporting Information File 30: Experimental (synthesis, enzyme assay, molecular modelling). Supporting Information File 31: Copies of NMR spectra. Supporting Information File 32: Optimized QM/MM complexes

Insight into oral amphiphilic cyclodextrin nanoparticles for colorectal cancer: comprehensive mathematical model of drug release kinetic studies and antitumoral efficacy in 3D spheroid colon tumors

• Sedat Ünal,
• Gamze Varan,
• Juan M. Benito,
• Yeşim Aktaş and
• Erem Bilensoy

Beilstein J. Org. Chem. 2023, 19, 139–157, doi:10.3762/bjoc.19.14

Inclusion complexes of the steroid hormones 17β-estradiol and progesterone with β- and γ-cyclodextrin hosts: syntheses, X-ray structures, thermal analyses and API solubility enhancements

• Alexios I. Vicatos,
• Zakiena Hoossen and
• Mino R. Caira

Beilstein J. Org. Chem. 2022, 18, 1749–1762, doi:10.3762/bjoc.18.184

• the hormones BES and PRO, while the complex γ-CD·BES was readily shown to be isostructural with γ-CD·PRO by PXRD. Severe disorder of the encapsulated steroid molecules in the respective channels of the CD molecular assemblies was evident, however, preventing their modelling, but combination of the

Make or break: the thermodynamic equilibrium of polyphosphate kinase-catalysed reactions

• Michael Keppler,
• Sandra Moser,
• Henning J. Jessen,
• Christoph Held and
• Jennifer N. Andexer

Beilstein J. Org. Chem. 2022, 18, 1278–1288, doi:10.3762/bjoc.18.134

• modelling polyP with high chain length is currently not possible with ePC-SAFT, we assumed that only nucleotides were present in water. The consequence of this assumption is that interactions among nucleotides and polyP were considered to be equal to interactions among nucleotides and polyPn−1, and we

• yet possible to characterise polyP by thermodynamic modelling due to lack of experimental data and knowledge of the precise distribution of chain lengths, in a second step the influence of orthophosphate as a representative for polyP was investigated on the qualitative behaviour of the results in

• experimental issues (measurement uncertainty, occurrence of side reactions not considered in the modelling) or by theory issues, since, as described before, the influence of polyP was neglected in modelling with ePC-SAFT. Further, it should be noted again ePC-SAFT was used in a predictive mode, which was not

Experimental and theoretical studies on the synthesis of 1,4,5-trisubstituted pyrrolidine-2,3-diones

• Nguyen Tran Nguyen,
• Vo Viet Dai,
• Nguyen Ngoc Tri,
• Luc Van Meervelt,
• Nguyen Tien Trung and
• Wim Dehaen

Beilstein J. Org. Chem. 2022, 18, 1140–1153, doi:10.3762/bjoc.18.118

• Nguyen Tran Nguyen Vo Viet Dai Nguyen Ngoc Tri Luc Van Meervelt Nguyen Tien Trung Wim Dehaen Department of Chemistry, University of Science and Education, the University of Da Nang, Ton Duc Thang 459, 550000 Da Nang, Viet Nam Laboratory of Computational Chemistry and Modelling, Faculty of Natural

Identification of the new prenyltransferase Ubi-297 from marine bacteria and elucidation of its substrate specificity

• Jamshid Amiri Moghaddam,
• Huijuan Guo,
• Karsten Willing,
• Thomas Wichard and
• Christine Beemelmanns

Beilstein J. Org. Chem. 2022, 18, 722–731, doi:10.3762/bjoc.18.72

• -297, we performed sequence alignments and structure homology modelling using Swiss-Model (Figure 4) [32], which revealed the transmembrane domain consisting of ten α-helices and loops connecting the transmembrane helices (Figure S2 in Supporting Information File 1), similar to archaeal UbiA

• sequence alignments using MAFFT (7.450) [36]. Structure modelling of UbiA-297 was done using the SWISS-MODEL server [32] and visualized using Pymol (2.3.3). Regional alignment of homologous Ptase genes was done using MultiGeneBlast [37]. Nucleotide sequence accession numbers: The ubiA-297 and menA-1335