The structures of three isomorphous compounds, namely bis(2,6-dibromopyridinium) tetrabromidocuprate(II) dihydrate, (C(5)H(4)Br(2)N)(2)[CuBr(4)].2H(2)O, bis(2,6-dibromopyridinium) tetrabromidocadmate(II) dihydrate, (C(5)H(4)Br(2)N)(2)[CdBr(4)].2H(2)O, and bis(2,6-dibromopyridinium) tetrabromidomercurate(II) dihydrate, (C(5)H(4)Br(2)N)(2)[HgBr(4)].2H(2)O, show a crystal supramolecularity represented by M-Br...H-O-H...Br-M intermolecular interactions along with (pi)N-H...OH(2) hydrogen-bonding interactions forming layers connected via aryl-aryl face-to-face stacking of cations, leading to a three-dimensional network. The anions have significantly distorted tetrahedral geometry and crystallographic C(2) symmetry. The stability of this crystal lattice is evidenced by the crystallization of a whole series of isomorphous compounds.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1107/S010827010903772X | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
MMPD-DTA: Integrating Multi-Modal Deep Learning with Pocket-Drug Graphs for Drug-Target Binding Affinity Prediction.
J Chem Inf Model
January 2025
Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Longmian Avenue No. 101, Jiangsu 211166, China.
Predicting drug-target binding affinity (DTA) is a crucial task in drug discovery research. Recent studies have demonstrated that pocket features and interactions between targets and drugs significantly improve the understanding of DTA. However, challenges remain, particularly in the detailed consideration of both global and local information and the further modeling of pocket features.
View Article and Find Full Text PDFA mononuclear iron(II) complex constructed using a complementary ligand pair exhibits intrinsic luminescence-spin-crossover coupling.
Dalton Trans
January 2025
State Key Laboratory of Fine Chemicals, Frontier Science Center for Smart Materials, School of Chemical Engineering, Dalian University of Technology, No. 2 Linggong Road, Dalian 116024, P. R. China.
Molecular materials that exhibit synergistic coupling between luminescence and spin-crossover (SCO) behaviors hold significant promise for applications in molecular sensors and memory devices. However, the rational design and underlying coupling mechanisms remain substantial challenges in this field. In this study, we utilized a luminescent complementary ligand pair as an intramolecular luminophore to construct a new Fe-based SCO complex, namely [FeLL](BF)·HO (1-Fe, L is a 2,2':6',2''-terpyridine (TPY) derivative ligand and L is 2,6-di-1-pyrazol-1-yl-4-pyridinecarboxylic acid), and two isomorphic analogs (2-Co, [CoLL](BF)·HO and 3-Zn, [ZnLL](BF)·HO).
View Article and Find Full Text PDFElectric dipole moment of excited octupolar molecules: Potential qubit implementation.
J Chem Phys
January 2025
Volgograd State University, University Avenue 100, Volgograd 400062, Russia.
The first excited state of conjugated donor-acceptor molecules of C3 symmetry (octupolar molecules) is doubly degenerate. Such a doublet is known to be isomorphic to a spin 1/2. It is shown that a large electric dipole moment is associated with this spin.
View Article and Find Full Text PDFLanthanide-Based Metal-Organic Frameworks Offering Hydrogen Bonding Cavities: Luminescent Characteristics and Sensing Applications.
Chem Asian J
January 2025
Department of Chemistry, University of Delhi, North Campus, Delhi, 110007, India.
This work presents the synthesis and characterization of three isomorphous lanthanide-based metal-organic frameworks (Ln-MOFs) (Ln=Eu (1), Tb (2), and Sm (3)) supported by a pyridine-2,6-dicarboxamide-based linker offering appended arylcarboxylate groups. Single crystal X-ray diffraction studies highlight that these Ln-MOFs present three-dimensional porous architectures offering large cavities decorated with hydrogen bonding (H-bonding) groups. These Ln-MOFs display noteworthy luminescent characteristics.
View Article and Find Full Text PDFDeepTGIN: a novel hybrid multimodal approach using transformers and graph isomorphism networks for protein-ligand binding affinity prediction.
J Cheminform
December 2024
School of Biomedical Engineering and Informatics, Nanjing Medical University, Longmian Avenue No. 101, Nanjing, 211166, Jiangsu, China.
Predicting protein-ligand binding affinity is essential for understanding protein-ligand interactions and advancing drug discovery. Recent research has demonstrated the advantages of sequence-based models and graph-based models. In this study, we present a novel hybrid multimodal approach, DeepTGIN, which integrates transformers and graph isomorphism networks to predict protein-ligand binding affinity.
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!