Molecular networks via reduced reverse degree approach.
Muhammad Mudassar Hassan1, Xiang-Feng Pan1, De-Min Yu2
1School of Mathematical Sciences, Anhui University, Hefei 230601, China.
Journal of Molecular Graphics & Modelling
|December 11, 2024
Summary
Researchers calculated topological indices for porphyrazine and tetrakis porphyrazine using a novel degree-based approach. These indices quantify molecular topology, aiding in the development of new materials and drug design.
Area of Science:
- Organic Chemistry
- Materials Science
- Computational Chemistry
Background:
- Porphyrazine and tetrakis porphyrazine feature complex ring structures with highly conjugated systems.
- These properties impart unique optical and electrical characteristics, making them vital in molecular electronics, sensors, functional materials, and catalysis.
Purpose of the Study:
- To quantify the molecular topology of porphyrazine and tetrakis porphyrazine structures.
- To introduce a formula for calculating reduced reverse degree-based topological indices for these compounds.
- To explore the utility of these indices in structure-activity relationship (SAR/QSAR) modeling and predicting chemical behavior.
Main Methods:
- Modeling molecules as networks with atoms as nodes and bonds as links.
- Employing a reduced reverse degree-based approach to estimate topological indices.
- Calculating specific indices: reduced reverse geometric arithmetic, general Randić, Balaban, redefined Zagreb, forgotten, hyper-Zagreb, and atom-bond connectivity indices.
Main Results:
- A formula for calculating various reduced reverse degree-based topological indices for porphyrazine and tetrakis porphyrazine was successfully derived.
- Graph-theoretical analysis and comparison were performed to validate the obtained results.
- The study provides quantitative descriptors for molecular topology.
Conclusions:
- The calculated topological indices offer valuable insights into the structural and chemical properties of porphyrazine and tetrakis porphyrazine.
- These findings can facilitate the design of novel materials for diverse applications and aid in drug discovery.
- The study highlights the significance of graph-theoretical methods in understanding complex organic molecules.
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