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Synthesis and Reactivity of the [NCCCO]– Cyanoketenate Anion
No full textCyanoketene is a fundamental molecule that is actively being searched for in the interstellar medium. Its deprotonated form (cyanoketenate) is a heterocumulene that is isoelectronic to carbon suboxide whose structure has been the subject of debate. These research questions are hampered by a lack of useful synthetic pathways to these molecules. We report the first synthesis of the cyanoketenate anion in [K(18-crown-6)][NCCCO] (1) as a stable molecule on a multigram scale in excellent yields (>90%). The structure of this molecule is probed crystallographically and computationally. We also explore the protonation of 1, and its reaction with triphenylsilylchloride and carbon dioxide. In all cases, anionic dimers are formed. The cyanoketene could be synthesized and crystallographically characterized when stabilized by a N-heterocyclic carbene. The cyanoketenate is a very useful unsaturated building block containing N, C and O atoms that can now be explored with relative ease and will undoubtedly unlock more interesting reactivity
Evaluation of Point Group Symmetry in Lanthanide(III) Complexes – a New Implementation of the Continuous Symmetry Measure with Autonomous Assignment of the Principal Axis
No full textThe structure of molecular systems dictates the physical properties, and symmetry is determining for all electronic properties. This makes group theory a powerful tool in quantum mechanics, when computing molecular properties. For inorganic compounds, the coordination geometry has been estimated as idealized polyhedra of high symmetry, which through ligand field theory provides predictive capabilities. However, real samples rarely have ideal symmetry, and even though continuous symmetry measures can be used to evaluate deviation form ideal symmetry, this often fails for lanthanide(III) complexes with high coordination numbers and no obvious principal axis. In lanthanide complexes, the unique electronic structures and the associated properties are intricately tied to the symmetry around the lanthanide center. Robust methodologies to evaluate and estimate point group symmetry is therefore instrumental for building structure property relationships. Here, we have demonstrated an algorithmic approach that determines the principal axis, and computes a deviation from ideal symmetry. This approach is based on the continuous symmetry measures and evaluates deviations from ideal symmetry for each symmetry operation in all relevant point groups. To demonstrate the methodology we have investigated the structure and symmetry of 8 and 9 coordinated lanthanide(III) aqua complexes, and correlated the luminescence from 3 europium(III) crystals to their actual symmetry. To document the methodology the approach has been tested on 26 molecules with different symmetry. It was concluded that the method is robust and fully autonomous
Metal Ions-Induced Unusual Stability of the Metastable Vesicle-like Intermediates Evolving in the Self-Assembly Process of Phenylalanine: The Role of Hydrophobic Interaction, Metal-Coordination, and Surface Charge Inversion
No full textThe underlying mechanism and the intermediates formation in the self-assembly of aromatic amino acids, peptides and proteins remain elusive despite numerous reports. We, for the first time, report that one can modulate the stability of the intermediates by tuning the metal ions-amino acid interaction of carboxybenzyl (Z)-protected phenylalanine (ZF). The microscopic and spectroscopic investigations reveal that the bivalent metal ions lead to the formation of fibrillar networks after a certain interval similar to blank ZF, whereas the trivalent ions develop vesicle-like intermediates which do not undergo fibrillation for a prolonged time. The time-lapse measurement of surface charge reveals that the surface charge of blank ZF and in the presence of bivalent metal ions alters from negative value to zero implying unstable intermediates leading to the fibril network. Strikingly, a prominent charge inversion from an initial negative to a positive value in the presence of trivalent metal ions imparts unusual stability to the metastable intermediates
The Chan-Lam-type synthesis of thioimidazolium salts for thiol-(hetero)arene conjugation
No full textThe design of stable and variable aryl linkers for conjugating drug moieties to the metabolism-related thiols is of importance in drug discovery, especially in the field of antibody-drug conjugates (ADCs). We disclosed that thioimidazolium groups are unique scaffolds for the thiol-(hetero)arene conjugation under mild conditions. The drug bound thioimidazolium salts, which are easily accessible via a copper-mediated Chan-Lam process in gram-scale, could be successfully applied to the late-stage coupling of bioactive thiols to construct a broad array of drug-like molecules
A Thermally Stable, Alkene-Free Palladium Source for Oxidative Addition Complex Formation and High Turnover Catalysis
No full textOxidative addition complexes play a crucial role in Pd-catalyzed transformations. They are not only key catalytic intermediates, but are also powerful and robust precatalysts, and effective reactants for late-stage functionalization of complex molecules. However, accessing a given oxidative addition complex is often challenging due to a lack of effective and stable palladium sources with the correct reactivity. Herein, we report an easily prepared and bench stable Pd(II) dialkyl complex, DMPDAB–Pd–BTSM (BTSM = bis[trimethylsilylmethyl]), that is a versatile precursor for generating Pd(II) oxidative addition complexes, and a highly active Pd source for in situ catalyst formation in cross-coupling reactions. A crucial aspect of this structure is the absence of alkene-based stabilizing ligands common to other Pd precursors. We demonstrate the utility of this precursor in the formation of several Pd(II) complexes, including phosphine and diimine-ligated oxidative addition complexes, and in high turnover number catalysis of C–O, Suzuki, and Heck coupling reactions
Raney Nickel-Catalyzed Deuterium Labeling of Nitrogen-Containing Heterocycles and Pharmaceuticals under Continuous Flow Conditions
No full textDeuterium-labeled compounds play a pivotal role in physical organic chemistry, life sciences, and materials science. This has resulted in a surge of interest in deuterium-labeled active pharmaceutical ingredients in recent years. In this study, we present a continuous flow Raney nickel-catalyzed hydrogen isotope exchange process that boasts compatibility with a wide spectrum of nitrogen-containing heterocycles and pharmaceutical compounds. The broad applicability of the developed method was demonstrated through successful labeling of various purine bases, imidazoles, pyridines, and active pharmaceutical ingredients, including complex structures like abacavir and remdesivir. Control experiments revealed Raney nickel\u27s crucial role in the exchange process, showcasing the superiority of the continuous flow approach over batch reactions. Furthermore, a scaled-up experiment demonstrated the robustness of the catalyst
Under-representativeness of Physical Chemistry Journals
No full textIn the contemporary landscape of scientific publishing, the categorization and ranking of journals significantly influence academic research and scholarly careers [1-2]. Particularly in chemistry with numerous research fields, the issue of misclassification of journals has emerged as a notable concern. In this comment, we aim to examine the misclassification of physical chemistry journals in the Web of Science (WOS) and how this impacts their ranking in the Journal Citation Reports (JCR). We highlight that due to the erroneous categorization of physical chemistry journals within other fields, they are forced to compete with journals possessing much higher impact factors, adversely affecting their standings in the JCR rankings. This not only undermines the reputation of physical chemistry journals but also negatively impacts the academic research and scholars within the field. Through our analysis, we seek to illuminate the severity of this issue and propose recommendations for a more equitable and accurate evaluation of physical chemistry journals
Exploring the Aggregation Propensity of PHF6 Peptide Segments of the Tau Protein using Ion Mobility Mass Spectrometry Techniques
No full textPeptide and protein aggregation involves the formation of oligomeric species, but the complex interplay between oligomers of different conformations and sizes complicates their structural elucidation. Using ion mobility mass spectrometry (IM-MS), we aim to reveal these early steps of aggregation for the Ac-PHF6-NH2 peptide segment from tau protein, thereby distinguishing between different oligomeric species, and gaining an understanding of the aggregation pathway. An important factor that is often neglected, but which can alter the aggregation propensity of peptides, is the terminal capping groups. Here we demonstrate the use of IM-MS to probe the early stages of aggregate formation of the Ac-PHF6-NH2, Ac-PHF6, PHF6-NH2, and uncapped PHF6 peptide segments. The aggregation propensity of the four PHF6 segments is confirmed using thioflavin T fluorescence assays and transmission electron microscopy. Post-IM fragmentation and quadrupole selection on the TIMS-Qq-ToF (trapped ion mobility) spectrometer are introduced to improve oligomer assignment. In addition, TIMS collision cross section values are compared with travelling wave ion mobility (TWIMS) data to evaluate potential instrumental bias in the trapped ion mobility results. The two IM-MS instrumental platforms are based on different ion mobility principles and have different configurations, thereby providing us with valuable insight into the preservation of weakly bound biomolecular complexes such as peptide aggregate
Comparing Software Tools for Optical Chemical Structure Recognition
No full textThe extraction of chemical information from images, also known as Optical Chemical Structure Recognition (OCSR) has recently gained new attention. This new interest is ignited by various machine learning methods introduced over the last years and the new possibilities to train image models for specific tasks such as OCSR. In the present paper, we have compared 8 open access OCSR methods (DECIMER, ReactionDataExtractor, MolScribe, RxnScribe, SwinOCSR, OCMR, MolVec, and OSRA) using an independent test set of images from patents and patent applications as this is an application area of general interest - precision and recall are highly desired by those who are analysing the intellectual property of chemistry patents. As a result, the used methods have shown different strengths when predicting structures from different images containing different modalities and chemistry categories. These existing methodologies for image extraction overall remain unsatisfactory, indicating a need for further advancements in the field. Further, we have created a machine learning image classifier, classifying images into one out of four image categories and applying the best performing OCSR method for each category. This classifier, the image comparator tools, and datasets have been made available to the public as open access tools
Binding Affinity Prediction with 3D Machine Learning: Training Data and Challenging External Testing
No full textProtein-ligand binding affinity prediction is one of the major challenges in computational assisted drug discovery. An active area of research uses machine learning (ML) models trained on 3D structures of protein ligand complexes to predict binding modes, discriminate active and inactives, or predict affinity. Methodological advances in deep learning, and artificial intelligence along with increased experimental data (3D structures and bioactivities) has led to many studies using different architectures, representation, and features. Unfortunately, many models do not learn details of interactions or the underlying physics that drive protein-ligand affinity, but instead just memorize patterns in the available training data with poor generalizability and future use. In this work we incorporate “dense”, feature rich datasets that contain up to several thousand analogue molecules per drug discovery target. For the training set, PDBbind dataset is used with enrichment from 8 internal lead optimization (LO) datasets and inactive and decoy poses in a variety of combinations. A variety of different model architectures was used and the model performance was validated using the binding affinity for 12 internal LO and 6 ChEMBL external test sets. Results show a significant improvement in the performance and generalization power, especially for virtual screening and suggest promise for the future of ML protein-ligand affinity prediction with a greater emphasis on training using datasets that capture the rich details of the affinity landscape