Introduction to Computational Organic Chemistry

Computational organic chemistry has become an indispensable component of chemical research, providing chemical insight and predictive power that complement research in experimental organic chemistry. While organic chemistry drives the creation of new molecules and processes to improve health and the sustainability of life on our planet, the fundamental questions of how molecules interact and react with each other to make new molecules are near impossible to answer without the help of modern computational tools. Computational approaches enable us to explain the observations we have, design new molecules for the next discoveries, and make the best use of our current knowledge. With the help of computational methods, organic chemistry can play its part in meeting the challenges that we all face.

We are pleased to introduce this themed collection in Organic & Biomolecular Chemistry focusing on Computational Organic Chemistry. This compilation highlights the significant impact of computational chemistry in experimental organic chemistry research. These studies not only show how computational methods can be used to explain experimental observations, but also how they can lead to the design of new systems and to extract the maximum value from every experiment. The topics covered include the following categories: (1) understanding reaction mechanisms, (2) predicting structures and molecular properties, (3) drug design and natural products, (4) optimizing catalytic functions, and (5) computational methods and benchmarking. Here, computational models enable the rapid assessment of properties for a wide range of systems, from small organic molecules to complex transition-state structures and larger natural products with challenging conformational properties.

In category (1)—understanding reaction mechanisms, Zhang et al. investigate the [1,2]-fluorine migration driven by α-electron deficiency. They report a synchronous concerted tight-ion-pair mechanism and the identification of two mechanistic variants (https://doi.org/10.1039/D3OB01335A). Turner et al. investigate the mechanism of hydrogen atom transfer-induced carboxylate elimination from monoacylated 1,2-diol groups in pyranosides. Seven-membered rings are not usually the first thought of people analysing reactions, but this study finds that concerted elimination through a hydrogen-bonded 7-membered transition state is the preferred pathway (https://doi.org/10.1039/D4OB00241E). Das et al. report a strain-promoted azide–alkyne cycloaddition reaction for the synthesis of oxa-azabenzobenzocyclooctynes (O-ABCs), and apply strain-activation analyses to unravel reasons underlying the enhanced reactivity of O-ABC analyses. These insights will be used in the design of future reagents (https://doi.org/10.1039/D3OB01559A). Sánchez-Quesada et al. explore the dehydration of alcohols catalyzed by copper(II) sulfate, revealing that primary alcohols undergo type II dyotropic reactions, while secondary alcohols favor stepwise E1-like processes. This understanding of the detailed effect of the catalyst makes it possible to design syntheses of molecules that are of interest to the fragrance industry (https://doi.org/10.1039/D3OB02052E). Souza et al. investigate the reductive amination of acetophenones using the NaBH₃CN-based Borch approach. Density functional theory calculations highlight the detailed role of the acid catalyst in both the initial nucleophilic step and water elimination and its variation with different substrates (https://doi.org/10.1039/D4OB00160E). Alves and Fernández investigate how substituents alter the reactivity and selectivity of Diels–Alder cycloadditions involving furan and substituted furans with maleic anhydride (https://doi.org/10.1039/D3OB01343J).

In category (2)—predicting structures and molecular properties, Adrion and Lopez investigate hemi-azothiophenes. Whilst absorption maximum and half-life are generally thought to be inversely related, they demonstrate it is possible to optimize them together and so design more effective photoswitches (https://doi.org/10.1039/D3OB01298K). Almacellas et al. calculate that guanine-inspired rosettes with aligned hydrogen bonds show enhanced cooperativity. This suggests how supramolecular systems with this feature may be designed (https://doi.org/10.1039/D3OB01391J). Baranac-Stojanović et al. investigate the factors that influence the tautomerization of 2- and 4-pyridones. The correlation with experiment for well-known systems gives confidence that the results can be trusted for less studied substrates (https://doi.org/10.1039/D3OB01588B). Badri et al. explore the structure of tetraquinolines (TEQs) and show that the removal of two electrons from the system transforms the non-aromatic structures to aromatic, but non-planar, macrocycles (https://doi.org/10.1039/D3OB01616A). Radicals generated from amino acids and peptides have attracted much interest despite being very difficult to study experimentally because of their high reactivity. Moppel et al. examine hydrogen bonding interactions between water and fourteen α-amino acids in their neutral and radical cation forms, helping to elucidate the properties of these key transient intermediates (https://doi.org/10.1039/D4OB00301B).

In category (3)—drug design and natural products, Zhou et al. investigate Pimelea poisoning of cattle, which is a major issue in Australia. The toxin, simplexin, is a complex molecule that causes a natural enzyme to become overactive, with negative health implications. Molecular dynamics simulations unveil the key interactions that lead to this effect and highlight the key role of the C-20 hydroxyl group. This new knowledge provides inspiration towards reducing the effects of Pimelea poisoning (https://doi.org/10.1039/D4OB00065J). Abraham et al. investigate HOO˙ radical scavengers using density functional theory, molecular docking, and molecular dynamics simulations to identify effective antioxidants (https://doi.org/10.1039/D3OB02126B). We note that the work of Moppel et al. (vide supra) analyses some of the consequences of failing to scavenge all radicals.

In category (4)—optimizing catalytic functions, Li and Li investigate the mechanism of chiral phosphoric acid (CPA)-catalyzed Paal–Knorr reactions for synthesizing N–N axially chiral atropisomers. The relationship between the catalyst structure and the absolute configuration of the product is not straightforward for this complex process, but the calculations reveal the sense of the stereoinduction (https://doi.org/10.1039/D3OB02011H). Wang et al. examine a similarly complicated multistep reaction: the nickel-catalyzed decarbonylation of lactones. Changing the ligands on the nickel affects every stage of the reaction and the overall impact on the process is hard to predict. The calculations demonstrate that electron-withdrawing ligands have a beneficial net effect and give rise to more efficient catalytic processes (https://doi.org/10.1039/D3OB01216F).

In category (5)—computational methods and benchmarking, Renningholtz et al. test the performance of a variety of computational methods for predicting thermodynamic stability of various organic radicals (https://doi.org/10.1039/D4OB00532E). Chiari et al. investigate J_FH coupling in fluorinated amino alcohols. DFT calculations on static structures provided insights into some conformational preferences, but did not explain all features of the spectra. Further clarity and new insights were gained by more sophisticated and resource-intensive calculations analysing the dynamic movement of the systems using molecular dynamics simulations (https://doi.org/10.1039/D4OB00049H).

The diverse range of articles in this themed collection highlights the extensive applications of computational organic chemistry across many areas of traditional and modern organic chemistry research. We extend our gratitude to all the contributing authors for their valuable work. We are enthusiastic and optimistic about the future growth of computational organic chemistry, which promises to continue to propel experimental endeavors in exciting new avenues of chemical research. Computational analyses enable us to extract the maximum value from our experimental data, growing the information we require to exploit the emerging possibilities of artificial intelligence. The use of all these approaches together will make possible the sustainable development of transformative science.

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