Beyond symmetric self-assembly and effective molarity: unlocking functional enzyme mimics with robust organic cages

• Keith G. Andrews

Beilstein J. Org. Chem. 2025, 21, 421–443, doi:10.3762/bjoc.21.30

• ], which in many cases is the only way to understand pure substituent effects (e.g., on catalysis). To enable the validation of this process, experimentalists must collect data relevant to benchmarking computations: binding constants, kinetic barriers, crystal structures. In turn, this process will be

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

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

• open-source way of storing and accessing chemical reaction data, such as the ORD [36][177] or the curated USPTO dataset [35], would facilitate the benchmarking of models in predicting reaction conditions. Moreover, ML models may not always learn to predict meaningful reaction conditions; they may

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

• from the current best training compound to prioritize further data acquisition. We apply the ActiveDelta concept to both graph-based deep (Chemprop) and tree-based (XGBoost) models during exploitative active learning for 99 Ki benchmarking datasets. We show that both ActiveDelta implementations excel

• , MACCS Keys, and Atom Pair Fingerprints) during the initial iterations of active learning (1–15, 16–30, and 31–45) across all 99 benchmarking datasets with three repeats (Supporting Information File 1, Table S2). Random selection consistently selected the least similar molecules of all approaches (p

• number of identified hits of each approach at 100 iterations across all the 99 benchmarking tasks. (E–G) The number of unique scaffolds in hits selected over 100 iterations of active learning. (H) Bar charts of the average number of unique scaffolds identified by each approach at 100 iterations across

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

• on Voronoi tessellation and alpha spheres. It consists of three main programs: Fpocket for pocket identification, Tpocket for benchmarking pocket detection, and Dpocket for collecting pocket descriptor values. Written in C, Fpocket is well-suited for developing new scoring functions and extracting

Stability trends in carbocation intermediates stemming from germacrene A and hedycaryol

• Naziha Tarannam,
• Prashant Kumar Gupta,
• Shani Zev and
• Dan Thomas Major

Beilstein J. Org. Chem. 2024, 20, 1189–1197, doi:10.3762/bjoc.20.101

• calculations with zero damping [35]. Extensive benchmarking on different sets of classical and non-classical carbocations have shown that M06-2X in conjunction with the 6-31+G(d,p) basis set performs well for carbocations [29][36], and here we confirm this finding for hydroxylated carbocations. All gas-phase

Novel route to enhance the thermo-optical performance of bicyclic diene photoswitches for solar thermal batteries

• Akanksha Ashok Sangolkar,
• Rama Krishna Kadiyam and
• Ravinder Pawar

Beilstein J. Org. Chem. 2024, 20, 1053–1068, doi:10.3762/bjoc.20.93

• using the M062X functional in combination with the 6-311++G** Pople-type basis set. This method was employed since the previous benchmarking studies have reported that the M062X/6-311++G** level performs well for prediction of the geometry and photoswitching properties of the BBD based systems. The

• complete active space (CAS) methods like CASPT2 are required to accurately predict the behaviour of TS. However, the multiconfigurational CAS methods are computationally demanding and cannot be routinely employed for the calculations. A previous benchmarking study has demonstrated that the single reference

• [42]. A previous benchmarking study has also suggested that the electronic energy difference (ΔE‡) accounts the TBR barrier closer to the experimental enthalpy difference (ΔH‡) [42]. Therefore, the TBR barriers were predicted with the difference in electronic energy of the TS and photoisomer (ΔE

A laterally-fused N-heterocyclic carbene framework from polysubstituted aminoimidazo[5,1-b]oxazol-6-ium salts

• Andrew D. Gillie,
• Matthew G. Wakeling,
• Bethan L. Greene,
• Louise Male and
• Paul W. Davies

Beilstein J. Org. Chem. 2024, 20, 621–627, doi:10.3762/bjoc.20.54

• seen with imidazolidines (cf. for IPr TEP[Ir] = 2050.2 cm−1) [34]. A benchmarking exercise was then performed looking at the reactivity of 13 compared against reaction of symmetrical IPrAuCl across a range of known gold-mediated transformations of alkynes featuring intermolecular attack [35

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

• GalN as well as 8 other molecules. For benchmarking purposes, all spectra were annotated with true labels. By running the model inference for one spectrum multiple times we can measure the variability of its prediction probability for each category. If the model gives consistently a high probability

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

• systematically rotating three bonds (i.e., F–C–C–F, F–C–C=O, and O=C–N–C) in 120° increments and the starting structures were then geometry optimised and their energies calculated. To enable benchmarking against experiment, NMR spin–spin coupling constants were calculated for the lowest-energy final structures

Dawn of a new era in industrial photochemistry: the scale-up of micro- and mesostructured photoreactors

• Emine Kayahan,
• Mathias Jacobs,
• Leen Braeken,
• Leen C.J. Thomassen,
• Simon Kuhn,
• Tom van Gerven and
• M. Enis Leblebici

Beilstein J. Org. Chem. 2020, 16, 2484–2504, doi:10.3762/bjoc.16.202

• concentration of the photoactive molecule is also crucial for an efficient photoreactor operation. In this paper, we are aiming to give a comprehensive understanding for scale-up strategies by benchmarking selected photoreactors and by discussing transport phenomena in several other photoreactors. Keywords

Potent hemithioindigo-based antimitotics photocontrol the microtubule cytoskeleton in cellulo

• Alexander Sailer,
• Franziska Ermer,
• Yvonne Kraus,
• Rebekkah Bingham,
• Ferdinand H. Lutter,
• Julia Ahlfeld and
• Oliver Thorn-Seshold

Beilstein J. Org. Chem. 2020, 16, 125–134, doi:10.3762/bjoc.16.14

• potency determined in this representative mammalian cell line can be translated to other cell types, although their specific response (e.g., EC50 values) would need individual determination. Nocodazole was used as a benchmarking reference and mechanistic positive control in all in cellulo assays since it

Plasma membrane imaging with a fluorescent benzothiadiazole derivative

• Pedro H. P. R. Carvalho,
• Jose R. Correa,
• Karen L. R. Paiva,
• Daniel F. S. Machado,
• Jackson D. Scholten and
• Brenno A. D. Neto

Beilstein J. Org. Chem. 2019, 15, 2644–2654, doi:10.3762/bjoc.15.257

• (GGA level) and ωB97XD (long range-corrected hybrid level) XCFs were employed. Both B97D3 and ωB97XD were strongly recommended by a thoroughly benchmarking of DFT methods for thermochemistry by Goerik and Grimme [55]. The new dye was then submitted to an MTT assay to investigate possible cytotoxicity

The phenyl vinyl ether–methanol complex: a model system for quantum chemistry benchmarking

• Dominic Bernhard,
• Fabian Dietrich,
• Mariyam Fatima,
• Cristóbal Pérez,
• Hannes C. Gottschalk,
• Axel Wuttke,
• Ricardo A. Mata,
• Martin A. Suhm,
• Melanie Schnell and
• Markus Gerhards

Beilstein J. Org. Chem. 2018, 14, 1642–1654, doi:10.3762/bjoc.14.140

• progress made in experiments and theory/computational chemistry, there is still a need for improvement and benchmarking [7]. Many aromatic solute–solvent complexes have been studied in the gas phase (cf. [8][9][10] and references therein). Studied systems involving methanol as attached solvent molecule

• ], there is a need for benchmarking systems in order to improve and develop better theoretical approaches especially for non-covalently bound complexes. The study on PVE–MeOH is meant to present a further benchmark system, probably even more challenging than DPE–t-BuOH. For an experimental elucidation of

Are dispersion corrections accurate outside equilibrium? A case study on benzene

• Tim Gould,
• Erin R. Johnson and
• Sherif Abdulkader Tawfik

Beilstein J. Org. Chem. 2018, 14, 1181–1191, doi:10.3762/bjoc.14.99

• establish the role of effects beyond dipole pairs (including Axilrod–Teller–Muto terms, quadropole and higher multipole terms, and full many-body terms). We hope this work will drive development and use of new benchmarking sets, along these lines, which can test a wider range of physics and chemistry at and

Comparative profiling of well-defined copper reagents and precursors for the trifluoromethylation of aryl iodides

• Peter T. Kaplan,
• Jessica A. Lloyd,
• Mason T. Chin and
• David A. Vicic

Beilstein J. Org. Chem. 2017, 13, 2297–2303, doi:10.3762/bjoc.13.225

• employed directly or generated in situ from precursors by published reports. Relative reactivities were also found to highly dependent on the nature of the iodoarenes. Keywords: benchmarking; copper; fluorine; fluoroalkylation; trifluoromethylation; Introduction Selectively fluorinated molecules that

• adequately describe a catalyst’s performance for the community. Explicit benchmarking in catalysis science is rarely reported in the literature (less than 500 mentions in approximately 1 × 106 articles describing catalytic phenomena) [17], and as methodologies for trifluoromethylation reactions continue to

Opportunities and challenges for the sustainable production of structurally complex diterpenoids in recombinant microbial systems

• Katarina Kemper,
• Max Hirte,
• Markus Reinbold,
• Monika Fuchs and
• Thomas Brück

Beilstein J. Org. Chem. 2017, 13, 845–854, doi:10.3762/bjoc.13.85

• natural products has been accomplished with industrially relevant production titers [75][76][77]. However, at present there is no clear preference for one microbial production host as each engineering endeavor requires a de novo benchmarking for a specific terpenoid product, indicating that even minimal

Effective in silico prediction of new oxazolidinone antibiotics: force field simulations of the antibiotic–ribosome complex supervised by experiment and electronic structure methods

• Jörg Grunenberg and
• Giuseppe Licari

Beilstein J. Org. Chem. 2016, 12, 415–428, doi:10.3762/bjoc.12.45

• experimentally known MIC values of eight linezolid analogues were used in order to crosscheck the robustness of our model. In a final step, this benchmarking led to the prediction of several new and promising lead compounds. Synthesis and biological evaluation of the new compounds are on the way. Keywords

Computational study of the rate constants and free energies of intramolecular radical addition to substituted anilines

• Andreas Gansäuer,
• Meriam Seddiqzai,
• Tobias Dahmen,
• Rebecca Sure and
• Stefan Grimme

Beilstein J. Org. Chem. 2013, 9, 1620–1629, doi:10.3762/bjoc.9.185

• enthalpies and relative values for different compounds (trends) should have an error <1 kcal mol−1. Results and Discussion Theoretical methods and benchmarking Computational details The quantum chemical calculations have been performed with the TURBOMOLE 6.4 suite of programs [34]. All geometry optimizations

• optimized gas phase geometries. The solvation contribution was then added to the gas phase free energies. The 5-exo cyclization as benchmark In order to find reliable computational methods for the description of the radical additions, we sought for systems for benchmarking that are structurally related to

• solvation effects, which might be an explanation for the better agreement of the rate constant presented in this work compared to the experimental value [53]. In order to increase the validity of the benchmarking, the rate constants k were calculated for a number of temperatures and compared to the values

Combined bead polymerization and Cinchona organocatalyst immobilization by thiol–ene addition

• Kim A. Fredriksen,
• Tor E. Kristensen and
• Tore Hansen

Beilstein J. Org. Chem. 2012, 8, 1126–1133, doi:10.3762/bjoc.8.125

• benchmarking. As a rough indication of activity, we started out by investigating quinine (1) and supported catalyst 10a–d in the Michael addition of 3-methoxythiophenol and cyclohex-2-enone (Table 1) [17]. Although the performance of quinine in this reaction is poor with regards to selectivity (providing only

• 23% ee), and probably not very useful for benchmarking, the supported catalysts 10a–d were obviously catalytically active, albeit modestly selective compared to the free catalyst, giving quantitative yields and a selectivity of 11–14% ee. Of greater interest was the performance of the primary amine

Halide exchanged Hoveyda-type complexes in olefin metathesis

• Julia Wappel,
• César A. Urbina-Blanco,
• Mudassar Abbas,
• Jörg H. Albering,
• Robert Saf,
• Steven P. Nolan and
• Christian Slugovc

Beilstein J. Org. Chem. 2010, 6, 1091–1098, doi:10.3762/bjoc.6.125

• the slowest catalyst for this transformation. Nevertheless, the performance of 3 is, when taking the results from the benchmarking in ROMP into account, remarkable. Complex 3 is a fairly good catalyst for this easy transformation and outperforms M2 [32]. With these results at our disposal, we