π-Hydrogen bonding interactions are ubiquitous in both materials and biology. Despite their relatively weak nature, great progress has been made in their investigation by experimental and theoretical methods, but this becomes significantly more complicated when secondary intermolecular interactions are present. In this study, the effect of successive methyl substitution on the supramolecular structure and interaction energy of indole⋅⋅⋅methylated benzene (ind⋅⋅⋅n-mb, n=1-6) complexes is probed through a combination of supersonic jet experiments and benchmark-quality quantum chemical calculations. It is demonstrated that additional secondary interactions introduce a subtle interplay among electrostatic and dispersion forces, as well as steric repulsion, which fine-tunes the overall structural motif. Resonant two-photon ionization and IR-UV double-resonance spectroscopy techniques are used to probe jet-cooled ind⋅⋅⋅n-mb (n=2, 3, 6) complexes, with redshifting of the N-H IR stretching frequency showing that increasing the degree of methyl substitution increases the strength of the primary N-H⋅⋅⋅π interaction. Ab initio harmonic frequency and binding energy calculations confirm this trend for all six complexes. Electronic spectra of the three dimers are broad and structureless, with quantum chemical calculations revealing that this is likely to be due to multiple tilted conformations of each dimer possessing similar stabilization energies.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1002/cphc.201601405 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Branched-chain amino acids and specific phosphatidylinositols are plasma metabolite pairs associated with menstrual pain severity.
Sci Rep
January 2025
Center for Cancer Immunotherapy and Immunobiology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Menstrual pain affects women's quality of life and productivity, yet objective molecular markers for its severity have not been established owing to the variability in blood levels and chemical properties of potential markers such as plasma steroid hormones, lipid mediators, and hydrophilic metabolites. To address this, we conducted a metabolomics study using five analytical methods to identify biomarkers that differentiate menstrual pain severity. This study included 20 women, divided into mild (N = 12) and severe (N = 8) pain groups based on their numerical pain rating scale.
View Article and Find Full Text PDFA multiscale molecular structural neural network for molecular property prediction.
Mol Divers
January 2025
Key Laboratory for Macromolecular Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an, 710119, People's Republic of China.
Molecular Property Prediction (MPP) is a fundamental task in important research fields such as chemistry, materials, biology, and medicine, where traditional computational chemistry methods based on quantum mechanics often consume substantial time and computing power. In recent years, machine learning has been increasingly used in computational chemistry, in which graph neural networks have shown good performance in molecular property prediction tasks, but they have some limitations in terms of generalizability, interpretability, and certainty. In order to address the above challenges, a Multiscale Molecular Structural Neural Network (MMSNet) is proposed in this paper, which obtains rich multiscale molecular representations through the information fusion between bonded and non-bonded "message passing" structures at the atomic scale and spatial feature information "encoder-decoder" structures at the molecular scale; a multi-level attention mechanism is introduced on the basis of theoretical analysis of molecular mechanics in order to enhance the model's interpretability; the prediction results of MMSNet are used as label values and clustered in the molecular library by the K-NN (K-Nearest Neighbors) algorithm to reverse match the spatial structure of the molecules, and the certainty of the model is quantified by comparing virtual screening results across different K-values.
View Article and Find Full Text PDFEnhancing Activation Energy Predictions under Data Constraints Using Graph Neural Networks.
J Chem Inf Model
January 2025
Department of Chemical Engineering, National Taiwan University, No. 1, Section 4, Roosevelt Road, Taipei 10617, Taiwan.
Accurately predicting activation energies is crucial for understanding chemical reactions and modeling complex reaction systems. However, the high computational cost of quantum chemistry methods often limits the feasibility of large-scale studies, leading to a scarcity of high-quality activation energy data. In this work, we explore and compare three innovative approaches (transfer learning, delta learning, and feature engineering) to enhance the accuracy of activation energy predictions using graph neural networks, specifically focusing on methods that incorporate low-cost, low-level computational data.
View Article and Find Full Text PDFGreen and Sustainable Spectrofluorometric Determination of Nitrofurantoin in Pure Form and Water Samples Using Functionalized Carbon Quantum Dots.
Luminescence
January 2025
Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Al-Azhar University, Cairo, Egypt.
The environmental impact of chemicals used in aquaculture, particularly nitrofurantoin, has raised global concern. Nitrofurantoin, a broad-spectrum antimicrobial, is commonly used in aquaculture despite safety risks. Determination of nitrofurantoin in water samples of fish ponds is necessary to ensure the safety and quality of seafood.
View Article and Find Full Text PDFHerbicidal and Antibacterial Secondary Metabolites Isolated from the -Derived Endophytic Fungus TE-739D.
Plants (Basel)
January 2025
Tobacco Research Institute of Chinese Academy of Agricultural Sciences, Qingdao 266101, China.
Endophytic fungi possess a unique ability to produce abundant secondary metabolites, which play an active role in the growth and development of host plants. In this study, chemical investigations on the endophytic fungus TE-739D derived from the cultivated tobacco ( L.) afforded two new polyketide derivatives, namely japoniones A () and B (), as well as four previously reported compounds -.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!