QSPR Analysis on Bone Marrow Cancer Medications Via Topological Indices and Regression Model

A topological index is a number that describes the topology of a network by using a chemical substance's molecular structure to fictitiously acquire its properties. This study examines and analyses the chemical structures of bone marrow cancer medicines using a cordial label-based topological index. Many features of bone marrow treatments, such as polar surface, boiling point, polarizability, enthalpy, molar refractivity, surface tension, Log P, and molar volume, have been statistically analysed. These results indicate a high link with topological indices, indicating the significance of these calculations. There is a direct association between the molecular descriptors and all positive correlation values. The properties of the bone marrow cancer medications calculated using a mathematical approach are superior compared to the experimental values of the bone marrow cancer medications obtained through costly and time consuming laboratory testing. Chemical structure is viewed as a network in which the elements are viewed as vertices and the boundaries between them as edges. Furthermore, the topological indices with and without hydrogen atoms are considered. In addition to observing that molar refractivity and polarizability exhibit the same correlations in the correlation coefficient and R-squared values in both hydrogen atoms and without hydrogen atoms, we also found that incorporating hydrogen atom analysis is more significant. The physical characteristics of chemical compounds used to treat bone marrow cancer are significantly associated with the aforementioned topological indices, as demonstrated by the QSPR analysis of these indices.  

Authors

Publication Details

Journal
African Journal of Biomedical Research
Published
2024-09-12
DOI
https://doi.org/10.53555/ajbr.v27i1s.1199
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.36
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

QSPR Analysis on Bone Marrow Cancer Medications Via Topological Indices and Regression Model

Nilan Nandish
1 citations
African Journal of Biomedical Research
Computational Drug Discovery Methods
0.36
article

QSPR Analysis on Bone Marrow Cancer Medications Via Topological Indices and Regression Model

Nilan Nandish
article en
1 citations

Abstract

A topological index is a number that describes the topology of a network by using a chemical substance's molecular structure to fictitiously acquire its properties. This study examines and analyses the chemical structures of bone marrow cancer medicines using a cordial label-based topological index. Many features of bone marrow treatments, such as polar surface, boiling point, polarizability, enthalpy, molar refractivity, surface tension, Log P, and molar volume, have been statistically analysed. These results indicate a high link with topological indices, indicating the significance of these calculations. There is a direct association between the molecular descriptors and all positive correlation values. The properties of the bone marrow cancer medications calculated using a mathematical approach are superior compared to the experimental values of the bone marrow cancer medications obtained through costly and time consuming laboratory testing. Chemical structure is viewed as a network in which the elements are viewed as vertices and the boundaries between them as edges. Furthermore, the topological indices with and without hydrogen atoms are considered. In addition to observing that molar refractivity and polarizability exhibit the same correlations in the correlation coefficient and R-squared values in both hydrogen atoms and without hydrogen atoms, we also found that incorporating hydrogen atom analysis is more significant. The physical characteristics of chemical compounds used to treat bone marrow cancer are significantly associated with the aforementioned topological indices, as demonstrated by the QSPR analysis of these indices.  

African Journal of Biomedical Research
Openalex Percentile: Top 36%
Computational Drug Discovery Methods
0.36
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.