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AQME, automated quantum mechanical environments, is a free and open‐source Python package for the rapid deployment of automated workflows using cheminformatics and quantum chemistry. AQME workflows integrate tasks performed across multiple computational chemistry packages and data formats, preserving all computational protocols, data, and metadata for machine and human users to access and reuse. AQME has a modular structure of independent modules that can be implemented in any sequence, allowing the users to use all or only the desired parts of the program. The code has been developed for researchers with basic familiarity with the Python programming language. The CSEARCH module interfaces to molecular mechanics and semi‐empirical QM (SQM) conformer generation tools (e.g., RDKit and Conformer–Rotamer Ensemble Sampling Tool, CREST) starting from various initial structure formats. The CMIN module enables geometry refinement with SQM and neural network potentials, such as ANI. The QPREP module interfaces with multiple QM programs, such as Gaussian, ORCA, and PySCF. The QCORR module processes QM results, storing structural, energetic, and property data while also enabling automated error handling (i.e., convergence errors, wrong number of imaginary frequencies, isomerization, etc.) and job resubmission. The QDESCP module provides easy access to QM ensemble‐averaged molecular descriptors and computed properties, such as NMR spectra. Overall, AQME provides automated, transparent, and reproducible workflows to produce, analyze and archive computational chemistry results. SMILES inputs can be used, and many aspects of tedious human manipulation can be avoided. Installation and execution on Windows, macOS, and Linux platforms have been tested, and the code has been developed to support access through Jupyter Notebooks, the command line, and job submission (e.g., Slurm) scripts. Examples of pre‐configured workflows are available in various formats, and hands‐on video tutorials illustrate their use.

This article is categorized under:

Data Science > Chemoinformatics

Data Science > Computer Algorithms and Programming

Software > Quantum Chemistry

 

Fluoroalkyl groups profoundly affect the physical properties of pharmaceuticals and influence virtually all metrics associated with their pharmacokinetic and pharmacodynamic profiles. Drug candidates increasingly contain CF3 and CF2H groups, and the same trend in agrochemical development shows that the effect of fluoroalkylation translates across human, insect, and plant life. New fluoroalkylation reactions have undoubtedly stimulated this uptake; however, methods that directly convert C–H bonds into C–CF2X (X = F or H) groups in complex drug-like molecules are rare. For pyridine, the most common aromatic heterocycle in pharmaceuticals, only one approach, via fluoroalkyl radicals, is viable for pyridyl C–H fluoroalkylation in the elaborate structures encountered during drug development. Here, we have developed a set of bench-stable fluoroalkylphosphines that directly convert the C–H bonds in pyridine building blocks, drug-like fragments, and pharmaceuticals into fluoroalkyl derivatives. No pre-installed functional groups or directing groups are required; the reaction tolerates a variety of sterically and electronically distinct pyridines and is exclusively selective for the 4-position in most cases. The reaction proceeds via initial phosphonium salt formation followed by sp2-sp3 phosphorus ligand-coupling, an underdeveloped manifold for C–C bond formation. 

The importance of modified peptides and proteins for applications in drug discovery, and for illuminating biological processes at the molecular level, is fueling a demand for efficient methods that facilitate the precise modification of these biomolecules. Herein, we describe the development of a photocatalytic method for the rapid and efficient dimerization and site-specific functionalization of peptide and protein diselenides. This methodology, dubbed the photocatalytic diselenide contraction, involves irradiation at 450 nm in the presence of an iridium photocatalyst and a phosphine and results in rapid and clean conversion of diselenides to reductively stable selenoethers. A mechanism for this photocatalytic transformation is proposed, which is supported by photoluminescence spectroscopy and density functional theory calculations. The utility of the photocatalytic diselenide contraction transformation is highlighted through the dimerization of selenopeptides, and by the generation of two families of protein conjugates via the site-selective modification of calmodulin containing the 21^stamino acid selenocysteine, and the C-terminal modification of a ubiquitin diselenide.

 

GoodVibes is an open-source Python toolkit for processing the results of quantum chemical calculations. Thermochemical data are not simply parsed, but evaluated by evaluation of translational, rotational, vibrational and electronic partition functions. Changes in concentration, pressure, and temperature can be applied, and deficiencies in the rigid rotor harmonic oscillator treatment can be corrected. Vibrational scaling factors can also be applied by automatic detection of the level of theory and basis set. Absolute and relative thermochemical values are output to text and graphical plots in seconds. GoodVibes provides a transparent and reproducible way to process raw computational data into publication-quality tables and figures without the use of spreadsheets. 

[3+2] cycloadditions of nitroolefins have emerged as a selective and catalyst‐free alternative for the synthesis of 1,2,3‐triazoles from azides. We describe mechanistic studies into the cycloaddition/rearomatization reaction sequence. DFT calculations revealed a rate‐limiting cycloaddition step proceeding via an asynchronous TS with high kinetic selectivity for the 1,5‐triazole. Kinetic studies reveal a second‐order rate law, and¹³C kinetic isotopic effects at natural abundance were measured with a significant normal effect at the conjugated olefinic centers of 1.0158 and 1.0216 at the α and β‐carbons of β‐nitrostyrene. Distortion/interaction‐activation strain and energy decomposition analyses revealed that the major regioisomeric pathway benefits from an earlier and less‐distorted TS, while intermolecular interaction terms dominate the preference for 1,5‐ over 1,4‐cycloadducts. In addition, the major regioisomer also has more favorable electrostatic and dispersion terms. Additionally, while static DFT calculations suggest a concerted but highly asynchronousEi‐type HNO₂elimination mechanism, quasiclassical direct‐dynamics calculations reveal the existence of a dynamic intermediate.

 

Heterobiaryls composed of pyridine and diazine rings are key components of pharmaceuticals and are often central to pharmacological function. We present an alternative approach to metal-catalyzed cross-coupling to make heterobiaryls using contractive phosphorus C–C couplings, also termed phosphorus ligand coupling reactions. The process starts by regioselective phosphorus substitution of the C–H bonds para to nitrogen in two successive heterocycles; ligand coupling is then triggered via acidic alcohol solutions to form the heterobiaryl bond. Mechanistic studies imply that ligand coupling is an asynchronous process involving migration of one heterocycle to the ipso position of the other around a central pentacoordinate P(V) atom. The strategy can be applied to complex drug-like molecules containing multiple reactive sites and polar functional groups, and also enables convergent coupling of drug fragments and late-stage heteroarylation of pharmaceuticals.