Journal of Computational Chemistry

doi: 10.1002/jcc.27420pmid: N/A

Patra, Shanti Gopal; Paul, Chhanda; Dutta, Nirmal; Chattaraj, Pratim Kumar

doi: 10.1002/jcc.70242pmid: 41042100

The bonding in transition metal carbonyls is discussed through the Dewar‐Chatt‐Duncanson (DCD) model of σ‐donation from the ligand and π‐back donation from the metal. However, there are no reports of direct quantification of the donation and back donation. Whenever it comes to the aspect of electron transfer, the fundamental concepts that are important are ionization energy (I), electron affinity (A), electronegativity (χ), hardness (η), and electrophilicity (ω). The global reactivity indices are calculated using conceptual density functional theory (CDFT). It was found that the back bonding and hence the experimental CO stretching frequency provide excellent correlation with I, A, and χ with r2 values of 0.963, 0.903, and 0.965, respectively. While in correlation to η, two categories are developed in correlation to νCO. However, the best correlation is achieved from the local electrophilicity description of the multiphilic descriptor (ΔωM). Finally, the directional approach of the back donation is tackled by the extended transition state‐natural orbitals for chemical valence (ETS‐NOCV) method, considering CO as one fragment and the rest as the other. A very good correlation to νCO is found with r2 = 0.964. The back‐bonding aspect is also explained from the second‐order perturbation energy term as obtained from the natural bond orbital analysis. These correlations remain valid upon changing the functional and basis sets. In addition, considering Sc(CO) as the starting complex, hydrogen molecules are added to obtain Sc(CO)(H2)n (n = 1–5) complexes. In these complexes, the Kubas‐type interactions are studied employing ETS‐NOCV and quantum theory of atoms in molecules (QTAIM) analyses.

Andrikopoulos, Prokopis C.; Halimeh, Heba

doi: 10.1002/jcc.70229pmid: 41045250

An extensive computational TDDFT resonance Raman study of lumiflavin is presented including 42 DFT functionals, benchmarked against the experimental Evolution Associated Spectra (EAS) of the equilibrated S1 and T1 states of FMN published earlier. Initially, off‐resonance spectra were computed, yielding adequate agreement, and fine‐tuning was achieved with the inclusion of specific frequency scaling factors. Since the experimental EAS were obtained under resonance for the singlet and near‐resonance for the triplet state, the subsequent inclusion of resonance effects in the calculations improved the correlation for most functionals. Their evaluation according to specific criteria narrowed down the choice to HCTH, OLYP, and TPSSh. Among the included criteria were the percent error of the 0–0 transitions, the quantification of the increase/decrease in correlation due to the addition of resonance enhancements, and the reproduction of the singlet‐triplet peak shifts. Owing to the extensive data set, valuable insights were gained to assist similar studies.

Keresztes, László; Szögi, Evelin; Varga, Bálint; Farkas, Viktor; Perczel, András; Grolmusz, Vince

doi: 10.1002/jcc.70238pmid: 41042117

Hexapeptides are increasingly applied as model systems for studying the amyloidogenic properties of oligo‐ and polypeptides. It is possible to construct 64 million different hexapeptides from the twenty proteinogenic amino acid residues. Today's experimental amyloid databases contain only a fraction of these annotated hexapeptides. For labeling all the possible hexapeptides as “amyloidogenic” or “non‐amyloidogenic” there exist several computational predictors with good accuracy. It may be of interest to define and study a simple graph structure on the 64 million hexapeptides as nodes, when two hexapeptides are connected by an edge if they differ by only a single residue. For example, in this graph, HIKKLM is connected to AIKKLM, or HIKKNM, or HIKKLC, but it is not connected with an edge to VVKKLM or HIKNPM. In the present contribution, we consider our previously published artificial intelligence‐based tool, the Budapest Amyloid Predictor (BAP for short), and demonstrate a spectacular property of this predictor in the graph defined above. We show that for any two hexapeptides predicted to be “amyloidogenic” by the BAP predictor, there exists an easily constructible path of length at most six that passes through neighboring hexapeptides all predicted to be “amyloidogenic” by BAP. For example, the predicted amyloidogenic ILVWIW and FWLCYL hexapeptides can be connected through the length‐6 path ILVWIW‐IWVWIW‐IWVCIW‐IWVCIL‐FWVCIL‐FWLCIL‐FWLCYL in such a way that the neighbors differ in exactly one residue, and all hexapeptides on the path are predicted to be amyloidogenic by BAP. The symmetric statement also holds true for non‐amyloidogenic predicted hexapeptides: For any such pair, there exists a path of length at most six, traversing only predicted non‐amyloidogenic hexapeptides. It is noted that the mentioned property of the Budapest Amyloid Predictor https://pitgroup.org/bap is not proprietary; it is also true for any linear Support Vector Machine (SVM)‐based predictors; therefore, for any future improvements of BAP using the linear SVM prediction technique.

Santra, Souvik; Sen, Sobitri; Bag, Arijit; Pal, Sourav

doi: 10.1002/jcc.70235pmid: 41042082

The development of advanced materials for the detection and safe handling of energetic compounds such as TATB (1,3,5‐triamino‐2,4,6‐trinitrobenzene) and TNT (2,4,6‐trinitrotoluene) is critical for defense, homeland security, and industrial safety. However, current technologies often suffer from limited cost‐efficiency, sensitivity, and real‐world applicability. While traditional carbon allotropes such as graphene, fullerenes, and carbon nanotubes have been explored for explosive sensing and hazard mitigation, emerging sp‐hybridized carbon nanostructures like cyclo[n]carbons remain underexplored. In this article, we present a theoretical investigation of cyclo[16]carbon (C16), a novel sp‐hybridized carbon ring, for interaction with energetic molecules. TNT was selected as a benchmark explosive due to its widespread use, whereas TATB was chosen for its remarkable insensitivity, allowing us to explore safe handling and adsorption scenarios. Our results reveal the formation of stable hollow‐layered and sandwich‐type supramolecular complexes with TNT and TATB via non‐covalent C…O, C…N, and C…C interactions. Notably, the C16–TNT and C16–TATB complexes exhibit enhanced thermodynamic stability and reduced electrostatic sensitivity. Binding energy and electronic structure analyses indicate tunable optical properties, supporting the role of C16 as a metal‐free, spectroscopically active sensor. These findings underscore the dual functionality of cyclo[16]carbon in promoting safe handling and detection of high‐energy materials, positioning it as a promising platform for passive sensing and hazard mitigation in challenging environments.