Structure and thermal stability of phosphorus-iodonium ylids

• Andrew Greener,
• Stephen P. Argent,
• Coby J. Clarke and
• Miriam L. O’Duill

Beilstein J. Org. Chem. 2024, 20, 2931–2939, doi:10.3762/bjoc.20.245

• in this decomposition, which will be elucidated with future computational studies. It was, however, found that the torsion angle φ (or ‘hypervalent twist’) between the plane of the arene substituent and the hypervalent 3-centre-4-electron bond was instrumental: When the arene ring was locked in the

The charge transport properties of dicyanomethylene-functionalised violanthrone derivatives

• Sondos A. J. Almahmoud,
• Joseph Cameron,
• Dylan Wilkinson,
• Michele Cariello,
• Claire Wilson,
• Alan A. Wiles,
• Peter J. Skabara and
• Graeme Cooke

Beilstein J. Org. Chem. 2024, 20, 2921–2930, doi:10.3762/bjoc.20.244

• hindered charge transport. Experimental Computational Density functional theory (DFT) calculations were performed using Gaussian 09 software. Molecular geometries were initially optimised semi-empirically (AM1) and then reoptimised by DFT using the B3LYP method with the 6-311G(d,p) basis set unless stated

Recent advances in transition-metal-free arylation reactions involving hypervalent iodine salts

• Ritu Mamgain,
• Kokila Sakthivel and
• Fateh V. Singh

Beilstein J. Org. Chem. 2024, 20, 2891–2920, doi:10.3762/bjoc.20.243

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

• clusters, and enzymes, development of chemical probes, biocatalysis and chemoenzymatic total synthesis, enzymatic mechanisms, and computational investigations of chemical structures and reactions. All of the major classes of natural products are represented here: nonribosomal peptides, ribosomally

Computational design for enantioselective CO₂ capture: asymmetric frustrated Lewis pairs in epoxide transformations

• Maxime Ferrer,
• Iñigo Iribarren,
• Tim Renningholtz,
• Ibon Alkorta and
• Cristina Trujillo

Beilstein J. Org. Chem. 2024, 20, 2668–2681, doi:10.3762/bjoc.20.224

• an asymmetric FLP and consequently an asymmetric catalyst. The subsequent study explores the asymmetric insertion of CO2 into chiral PO catalysed by the proposed in silico designed catalyst. Computational Details During the benchmark to choose the best catalyst, the reported geometries were optimised

• -D3(BJ)/def2-SVP computational level. Single point energy calculations on the optimised structures were run at the B3LYP-D3(BJ)/def2-TZVP level to obtain more accurate electronic energies. The reported free energies in this section correspond to the sum of the triple-zeta electronic energy and the

• minimise the computational costs associated with the study, the asymmetric catalyst was obtained by removing a phenyl group and exchanging the t-Bu group with a methyl group in the catalyst of Gao [28]. It appears that the capture of CO2 by the catalyst is barrierless and results in the formation of an

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

• complex is formed [11]. This suggests that hydration of CDs remains an important factor, especially given a recent study that showed how hydration history contributes to the hydration ability of α-CD [12]. Numerous experimental and computational studies have investigated the hydration of natural and

• upon heating. Conclusion Using experimental and computational methods as well as available literature data, the present study reliably estimates the number of water molecules present in γ-CD, their preferable binding position, and thermal stability. Comparison with the other cyclodextrins revealed that

• atmosphere of pure nitrogen. To ensure accuracy and reproducibility of the results the measurements were repeated multiple times, and no difference was observed between individual trials. Computational details A computational protocol similar to that used in our previous work on α-CD [13] and β-CD [14

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

Anion-dependent ion-pairing assemblies of triazatriangulenium cation that interferes with stacking structures

• Yohei Haketa,
• Takuma Matsuda and
• Hiromitsu Maeda

Beilstein J. Org. Chem. 2024, 20, 2567–2576, doi:10.3762/bjoc.20.215

• NMR spectra of new ion pairs, details for crystal structures, and theoretical calculations. Acknowledgements Theoretical calculations were partially performed at the Research Center for Computational Science, Okazaki, Japan (Projects: 22-IMS-C077, 23-IMS-C069, and 24-IMS-C067). The synchrotron

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

• compute reaction enthalpy for particular types of reactions [30], this approach often demands significant computational resources to determine accurate TSs and activation energies. The complexity increases further when considering the impacts of solvents and catalysts, which means that large-scale

• -scale global models, descriptors with longer feature lengths and higher computational efficiency, such as the first four methods, are preferred. However, for small-scale local models, QM features can offer more compact and accurate information, but they require sampling and optimizing the 3D conformers

• -driven approaches in chemistry. A community dedicated to openly sharing data and findings will likely accelerate innovation and enhance the robustness of ML tools. Moreover, computational models that integrate theoretical chemistry and ML could unlock deeper insights into poorly understood or complex

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

• ]-rearrangement of ene-aldimines 149, catalysed by the BINOL-derived chiral phosphoric acid (CPA) (R)-151 (Scheme 31) [46]. DFT computational analysis suggested that the reaction proceeds via a complex cascade that involves the fragmentation of ene-aldimine 149 to form an imine methylene cation, which in turn

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

• and reliable development is highly desirable [16]. In the spirit of accelerated discovery, the development of organocatalysts has been augmented with computational catalyst design [17][18]. Multiple programs for automated catalyst simulation have been developed in the last decade. Notable examples

• reduce the number of required experiments. As such, these methods contribute to the acceleration of catalyst discovery, for example through high-throughput virtual screening. Predating these computational techniques is the desire to understand and explain experimental outcomes in organic chemistry with

• 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

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

• Research Areas (A) (Grant Number JP20H05865, T. K.), and by research grant from The Murata Science Foundation (T. N.). Quantum chemical calculations were performed at the Research Center for Computational Science, Okazaki, Japan (Project: 23-IMS-C212 and 24-IMS-C214). This work was the result of using

Metal-free double azide addition to strained alkynes of an octadehydrodibenzo[12]annulene derivative with electron-withdrawing substituents

• Naoki Takeda,
• Shuichi Akasaka,
• Susumu Kawauchi and
• Tsuyoshi Michinobu

Beilstein J. Org. Chem. 2024, 20, 2234–2241, doi:10.3762/bjoc.20.191

• substituents has a lower Ea than DBA with electron-donating substituents. DFT calculations The reaction mechanism was investigated by computational calculations. The reaction mechanism between 5 and benzyl azide was supported by the ωB97X-D/6-31G(d,p) calculations with the CH2Cl2 polarizable continuum model

Heterocycle-guided synthesis of m-hetarylanilines via three-component benzannulation

• Andrey R. Galeev,
• Maksim V. Dmitriev,
• Alexander S. Novikov and
• Andrey N. Maslivets

Beilstein J. Org. Chem. 2024, 20, 2208–2216, doi:10.3762/bjoc.20.188

• with heterocyclic substituents, acetone and various amines has been developed. The success of this three-component reaction is governed by the electron-withdrawing ability of the heterocyclic substituent in the 1,3-diketone, which can be evaluated with computational Hammett constants. As a rule-of

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

• through iterative design. Beyond pharmaceutical design, we expect these methods to be easily deployable for other chemical endeavors to support material design and prioritization. Although pairwise methods like ActiveDelta exhibit increased computational costs during active learning given the

• complex computational architectures with improved hit retrieval rates in place of faster, but less effective, architectures should continue to be a good choice for most real-world projects. In the future, subsampling techniques may be employed to reduce computational costs and even potentially improve

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

• online software ProTox 3.0 for computational toxicity assessment of the products as their LD50 values. The tested compounds mainly belong to the 4th class of acute oral toxicity with 300 < LD50 ≤ 2000 mg/kg. In addition, we used MolPredictX (https://www.molpredictx.ufpb.br) [46] to evaluate potential

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

• numerous biological processes, ranging from cellular recognition to immune response modulation. Understanding the intricate details of these interactions is crucial for deciphering the molecular mechanisms underlying various physiological and pathological conditions. Computational techniques have emerged

• as powerful tools that can help in drawing, building and visualising complex biomolecules and provide insights into their dynamic behaviour at atomic and molecular levels. This review provides an overview of the main computational tools useful for studying biomolecular systems, particularly glycans

• 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

Allostreptopyrroles A–E, β-alkylpyrrole derivatives from an actinomycete Allostreptomyces sp. RD068384

• Marwa Elsbaey,
• Naoya Oku,
• Mohamed S. A. Abdel-Mottaleb and
• Yasuhiro Igarashi

Beilstein J. Org. Chem. 2024, 20, 1981–1987, doi:10.3762/bjoc.20.174

• , Japan Computational Chemistry Lab, Department of Chemistry, Faculty of Science, Ain Shams University, 11566 Abbassia, Cairo, Egypt 10.3762/bjoc.20.174 Abstract Five new β-alkylpyrrole derivatives, allostreptopyrroles A–E (1–5), were isolated from the culture broth of Allostreptomyces RD068384. Their

Regioselective alkylation of a versatile indazole: Electrophile scope and mechanistic insights from density functional theory calculations

• Pengcheng Lu,
• Luis Juarez,
• Paul A. Wiget,
• Weihe Zhang,
• Krishnan Raman and
• Pravin L. Kotian

Beilstein J. Org. Chem. 2024, 20, 1940–1954, doi:10.3762/bjoc.20.170

• Pengcheng Lu Luis Juarez Paul A. Wiget Weihe Zhang Krishnan Raman Pravin L. Kotian Department of Discovery Chemistry, BioCryst Pharmaceuticals Inc., Discovery Center of Excellence, 2100 Riverchase Center Building 200, Suite 200 Birmingham, AL, 35244, USA Department of Computational Chemistry and

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

• on a range of electronic molecular properties of PASs. Keywords: computational chemistry; database; dataset; π-conjugated; polycyclic aromatic hydrocarbons; polycyclic aromatic systems; Introduction Polycyclic aromatic systems (PASs) – molecules made up of fused aromatic rings – are among the most

• PAS chemical space is with data-driven methods, which have proven in the last few years to be extremely successful at uncovering underlying structure–property relationships. To enable such exploration, we initiated the COMPAS Project (COMputational database of PASs), the first database dedicated to

Syntheses and medicinal chemistry of spiro heterocyclic steroids

• Laura L. Romero-Hernández,
• Ana Isabel Ahuja-Casarín,
• Penélope Merino-Montiel,
• Sara Montiel-Smith,
• José Luis Vega-Báez and
• Jesús Sandoval-Ramírez

Beilstein J. Org. Chem. 2024, 20, 1713–1745, doi:10.3762/bjoc.20.152

• steroids 124a–e, adducts 125a–d and 126a–e were easily obtained as single diastereomers via a Pictet–Spengler condensation with coumarins A and B (used as fluorophores) under acidic conditions (Scheme 35). Computational binding studies of compound 126c in the ligand-binding pocket of enzyme 17β-HSD5

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

• publicly available which are typically 5 Mbp in size. Computational mining these genomes with antiSMASH reveals that these bacteria, though not endowed with the biosynthetic prowess of actinomycetes, do still possess BGCs encoding NRPS-derived peptides, polyketides, RiPPs, and siderophores [4][147]. A

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

• methods are evaluated as single-point calculations or optimization and frequency calculations. For comprehensive details, refer to Supporting Information File 1, section “Benchmark study - computational methods”. Hereafter, we check the geometries for imaginary frequencies and use the total thermal energy

Generation of multimillion chemical space based on the parallel Groebke–Blackburn–Bienaymé reaction

• Evgen V. Govor,
• Vasyl Naumchyk,
• Ihor Nestorak,
• Dmytro S. Radchenko,
• Dmytro Dudenko,
• Yurii S. Moroz,
• Olexiy D. Kachkovsky and
• Oleksandr O. Grygorenko

Beilstein J. Org. Chem. 2024, 20, 1604–1613, doi:10.3762/bjoc.20.143

• -component reactions are very effective for the generation of synthetically tractable ultra-large chemical space [30][31][32]. Such virtual but readily accessible (REAL) compound libraries demonstrated excellent performance in early drug discovery programs when combined with modern computational tools such

• the relatively high computational costs of this method, we randomly selected 50,000 compounds to represent each database. The dimension reduction algorithm uses molecular features as the starting inputs to generate a few coordinates (in this case, t-SNE1 and t-SNE2) reflecting the probability of the

Divergent role of PIDA and PIFA in the AlX₃ (X = Cl, Br) halogenation of 2-naphthol: a mechanistic study

• Kevin A. Juárez-Ornelas,
• Manuel Solís-Hernández,
• Pedro Navarro-Santos,
• J. Oscar C. Jiménez-Halla and
• César R. Solorio-Alvarado

Beilstein J. Org. Chem. 2024, 20, 1580–1589, doi:10.3762/bjoc.20.141

• influence of PIDA and PIFA in the chlorination and bromination reactions. Interestingly, we found an excellent agreement between the theoretical predictions and the experimental results. Results and Discussion Computational details The equilibrium geometry of reagents and products, the stationary points