Journal of Chemical Sciences最新文献

The proposed research aims to investigate the structure and lowest excitation properties of GG-CC and GC-CG (G, guanine; C, cytosine) peptide nucleic acid (PNA) dimers, incorporating different amino acids such as serine, aspartic acid, and histidine using the density functional theory (DFT) and time-dependent density functional theory (TDDFT) methods. The structures under consideration have been optimized at the Becke’s three-parameter hybrid density functional (B3) with correlation function of Lee, Yang and Parr (LYP)/6-31G* level of theory. The study involves calculating the backbone torsions and backbone-base linker torsions, correlating them with experimental data. The computed excitation energy for the GG-CC PNA system is compared with the natural GG-CC DNA system. The lowest excitation properties, such as excitation energy, wavelength, and oscillator strength, reveal their dependency on both the stacking arrangement and the molecular environment, irrespective of whether the PNA is modified or unmodified. Additionally, a highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) analyses were conducted. This study is intended to serve as a foundational tool for understanding the molecular behaviour of PNAs under light absorption, potentially leading to further exploitation in photo-related applications.

Graphical abstract

This article explores the application of conceptual density functional theory (CDFT) and information-theoretic approach (ITA) to various chemical phenomena, demonstrating their predictive power in diverse molecular systems. IT descriptors have been employed to investigate conformational stability, molecular acidity, aromaticity, and electrophilicity/nucleophilicity, revealing strong correlations between information-theoretic measures and experimental observations. Moreover, CDFT-based QSAR and QSPR models have shown significant predictive capabilities in pharmacological toxicity and physicochemical properties, such as partition coefficient and enthalpy of vaporization. The integration of CDFT and IT descriptors has provided deeper insights into reactivity trends in pericyclic reactions, allowing for the classification of mechanisms based on electrophilicity indices. Additionally, periodic trends in CDFT and IT descriptors have been examined, reaffirming the fundamental chemical principles. The review article underscores the robustness of IT and CDFT methodologies in capturing electronic structure variations and predicting the chemical behavior of molecules. The integration of these descriptors offers a comprehensive approach to understanding chemical reactivity, stability, and molecular interactions, paving the way for future advancements in theoretical and computational chemistry.

Graphical abstract

The applications of Conceptual Density Functional Theory (CDFT) and the Information-Theoretic Approach (ITA) have been widely used in predicting the toxicity, activity, and reactivity of chemical systems. Moreover, Quantitative Structure–Activity Relationship (QSAR) studies are conducted using CDFT and ITA descriptors through regression equations.

A recent study by Liam Longo and co-workers at the Earth-Life Science Institute, published in Angewandte Chemie, reports the discovery of an ancient helix-hairpin-helix protein motif capable of functioning in both left- and right-handed forms, thus challenging the concept that biomolecular interactions are strictly dependent on homochirality. This rather rare “ambidextrous” property suggests that such motifs may be molecular relics from a pre-LUCA era when mirror-image life forms coexisted, and offers new insights into the origins and evolution of molecular asymmetry seen in living matter.

Graphical abstract

The ‘helix-hairpin-helix’ motif allows the binding of a simple peptide to both DNA and its mirror image. Credit: Liam M S Longo.

Linoleic acid modified through autoxidation, hydroxylation, and bromination was utilized for the first time in controlled/living radical polymerization methods such as atom transfer radical polymerization (ATRP). A brominated polymeric linoleic acid macromonomer initiator (ATRP–MIM) was synthesized as a macromolecular initiator (MIM) based on polymeric linoleic acid for use in ATRP. Using this ATRP–MIM and styrene monomer, novel graft copolymers were successfully synthesized via ATRP. The effects of various reaction parameters, including monomer concentration, initiator concentration, and polymerization kinetics, were systematically investigated. Additionally, the impact of reaction conditions on molecular weight and polydispersity was studied. The percentage compositions of the structural contents of graft copolymers were determined using ¹H NMR. Detailed characterization, including structural analysis, thermal properties, and molecular weight determination, was performed using techniques such as Fourier-transform infrared spectroscopy (FT-IR), nuclear magnetic resonance (NMR), gel permeation chromatography (GPC), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). The obtained graft copolymers exhibited enhanced thermal stability and well-defined molecular structures, contributing to the development of bio-based polymeric materials with specialized properties for applications in coatings, biocompatible systems, and advanced functional materials.

Graphical abstract

This study introduces the use of modified linoleic acid, altered through autoxidation, hydroxylation, and bromination, in controlled radical polymerization methods such as atom transfer radical polymerization (ATRP) for the first time. The research focuses on the synthesis of graft copolymers by using a brominated polymeric linoleic acid initiator (ATRP-MIM) in copolymerization with styrene.

In a previous communication (Comp. Theor. Chem. 1091 (2016) 150), concerted isomerization reactions of 15 C₇H₇⁺ cations in the gas phase had been studied. The present study deals with the kinetics of these concerted isomerization reactions using the M06-2X functional. From the potential energy profiles of these reactions, the rate coefficients are estimated by using transition state theory along with the estimation of Wigner’s empirical transmission coefficient for quantum tunnelling. The rate coefficient values are calculated over a temperature range of 200–500 K, where the Arrhenius activation energies, along with the pre-exponential factors, are determined for each of these reactions.

Graphical abstract

The graphical abstract highlight the two representative isomerisation reactions of bicyclo[3.2.0]heptadienyl cation 4 to tropyl cation 1 (global minimum) by C-C σ-bond collapse to π-bond via transition state TS1 and o-tolyl cation 5 to benzyl cation 2 by 1,3-hydride shift via TS4.

Due to the high computational scaling of correlated quantum chemical methods, their application to large molecular systems presents significant challenges, particularly for computation of infrared (IR) and Raman spectra, which is often prohibitively expensive. The fragment-based Molecular Tailoring Approach (MTA), an indigenously developed methodology, has significantly broadened the scope of such studies. The MTA-based software package, MTASpec https://doi.org/10.17632/m5b5zhxkfh.1, enables the computation of molecular properties such as the electronic energy, vibrational IR and Raman spectra of large molecules and molecular clusters. This short review provides a comprehensive overview of the capabilities of such MTA-based studies which strike an effective balance between computational efficiency and accuracy. Future directions for enhancing and expanding the applicability of MTASpec for other spectroscopic methods are also discussed, highlighting its potential as a user-friendly, black-box tool for routine quantum chemical spectral investigations.

Graphical abstract

Molecular tailoring approach (MTA) and MTASpec codes provide an accurate yet inexpensive calculation of vibrational infrared and Raman spectra of spatially extended molecular systems using minimal hardware. Vibrational features of large molecular clusters and biomolecules such as carbohydrates, polypeptides and proteins can thereby be explored in gas- and solvent phases using HF, DFT and correlated methods with extended basis sets.

The ability to tailor the optical properties of graphene quantum dots (GQDs) is critical for their application in optoelectronics, bioimaging and sensing. However, a comprehensive understanding of how shape, size and doping influence their emission properties remains elusive. In this study, we conduct a systematic high-throughput time-dependent density functional theory (TDDFT) and machine learning analysis of 284 distinct GQDs, varying in shape (square, hexagonal, amorphous), size ((sim)1–2 nm) and doping configurations with elements B, N, O, S and P at varying concentrations (1.5–7%). Our findings reveal clear design principles for tuning emission wavelengths based on dopant type, concentration and GQD geometry. Notably, sulfur doping at specific concentrations consistently results in higher emission energies, with certain configurations yielding emissions within the visible range. By elucidating how quantum confinement effects, symmetry breaking and dopant-induced modifications govern GQD optical properties, we provide practical design rules for tailoring emission spectra for next-generation optoelectronic, bioimaging and sensing applications.

Graphical Abstract