Search for: All records

Given the prevalence of nitrogen-containing heterocycles in commercial drugs, selectively incorporating a single nitrogen atom is a promising scaffold hopping approach to enhance chemical diversity in drug discovery libraries. We harness the distinct reactivity of sulfenylnitrenes, which insert a single nitrogen atom to transform readily available pyrroles, indoles, and imidazoles into synthetically challenging pyrimidines, quinazolines, and triazines, respectively. Our additive-free method for skeletal editing employs easily accessible, benchtop-stable sulfenylnitrene precursors over a broad temperature range (−30 to 150°C). This approach is compatible with diverse functional groups, including oxidation-sensitive functionalities such as phenols and thioethers, and has been applied to various natural products, amino acids, and pharmaceuticals. Furthermore, we have conducted mechanistic studies and explored regioselectivity outcomes through density functional theory calculations. 

1,2-cis-Furanosides are present in various biomedically relevant glycosides, and their stereoselective synthesis remains a significant challenge. In this vein, we have developed a stereoselective approach to 1,2-cis-furanosylations using earth-abundant copper catalysis. This protocol proceeds under mild conditions at room temperature and employs readily accessible benchtop stable enynalderived furanose donors. This chemistry accommodates a variety of alcohols, including primary, secondary, and tertiary, as well as mannosyl alcohol acceptors, which have been incompatible with most known methods of furanosylation. The resulting 1,2-cisfuranoside products exhibit high yields and anomeric selectivity with both the ribose and arabinose series. Furthermore, the anomeric selectivity is independent of the C2 oxygen-protecting group and the anomeric configuration of the starting donor. Experimental evidence and computational studies support our hypothesis that copper chelation between the C2 oxygen of the furanose donor and an incoming alcohol nucleophile is responsible for the observed 1,2-cisstereoselectivity. 

Abstract In the last several years, there has been a surge in the development of machine learning potential (MLP) models for describing molecular systems. We are interested in a particular area of this field — the training of system‐specific MLPs for reactive systems — with the goal of using these MLPs to accelerate free energy simulations of chemical and enzyme reactions. To help new members in our labs become familiar with the basic techniques, we have put together a self‐guided Colab tutorial (https://cc-ats.github.io/mlp_tutorial/), which we expect to be also useful to other young researchers in the community. Our tutorial begins with the introduction of simple feedforward neural network (FNN) and kernel‐based (using Gaussian process regression, GPR) models by fitting the two‐dimensional Müller‐Brown potential. Subsequently, two simple descriptors are presented for extracting features of molecular systems: symmetry functions (including the ANI variant) and embedding neural networks (such as DeepPot‐SE). Lastly, these features will be fed into FNN and GPR models to reproduce the energies and forces for the molecular configurations in a Claisen rearrangement reaction. 

This work is devoted to deriving and implementing analytic second- and third-order energy derivatives with respect to the nuclear coordinates and external electric field within the framework of the hybrid quantum mechanics/molecular mechanics method with induced charges and dipoles (QM/DIM). Using these analytic energy derivatives, one can efficiently compute the harmonic vibrational frequencies, infrared (IR) and Raman scattering (RS) spectra of the molecule in the proximity of noble metal clusters/nanoparticles. The validity and accuracy of these analytic implementations are demonstrated by the comparison of results obtained by the finite-difference method and the analytic approaches and by the full QM and QM/DIM calculations. The complexes formed by pyridine and two sizes of gold clusters (Au18 and Au32) at varying intersystem distances of 3, 4, and 5 Å are used as the test systems, and Raman spectra of 4,4′-bipyridine in the proximity of Au2057 and Ag2057 metal nanoparticles (MNP) are calculated by the QM/DIM method and compared with experimental results as well. We find that the QM/DIM model can well reproduce the IR spectra obtained from full QM calculations for all the configurations, while although it properly enhances some of the vibrational modes, it artificially overestimates RS spectral intensities of several modes for the systems with very short intersystem distance. We show that this could be improved, however, by incorporating the hyperpolarizability of the gold metal cluster in the evaluation of RS intensities. Additionally, we address the potential impact of charge migration between the adsorbate and MNPs.