Related references
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Article
Biochemistry & Molecular Biology
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Summary: A topological index is a real number that describes the relationship between chemical structures and their properties under graph isomorphism. This article focuses on calculating the neighbourhood sum degree-based M-polynomial and entropy measures for graphene, graphyne, and graphdiyne structures. The derived analytical expressions for these indices provide insights for theoretical chemists to study these unique structures further.
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Summary: Quantitative structure-activity relationship (QSAR) is a method that correlates the biological structural features (topological indices) with pharmacological activity. Topological indices are numerical functions used to predict the growth rate of microorganisms in biological networks. Theoretical assessment of microorganisms helps in vaccine design and discovery by understanding their mechanism of actions. This article investigates the biological properties of two important biological networks (hypertree and its corona product) by obtaining novel topological features and deriving closed formulas for them.
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Summary: Topological indices have multiple biological applications in the treatment of blood cancer, including predicting drug efficacy and toxicity, as well as aiding in drug discovery and design. This article examines the use of topological indices in predicting the properties of novel drugs used in blood cancer treatment, such as boiling point, flash point, molar volume, molecular weight, and complexity. The results show the potential of topological indices as a tool for drug discovery and design in cancer treatment.
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Summary: This article aims to encourage original research on topological graph indices for the drugs azacitidine, decitabine, and guadecitabine, and to investigate the genesis of symmetry in actual networks. These hypomethylating drugs are used to treat patients with higher-risk myelodysplastic syndromes, chronic myelomonocytic leukemia, and acute myeloid leukemia who are not candidates for intense regimens.
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Asad Ullah et al.
Summary: Bioconjugate networks are formed by connecting different molecules or particles through covalent or non-covalent interactions, and they have various applications in biology and medicine. Understanding the structure-property relationships of these networks is important for developing more effective antibiotics.
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