Results on Certain Biopolymers Using M‐Polynomial and NM‐Polynomial of Topological Indices

Yasin, H. Mohammed; Suresh, M.; Abebe, Girma; Fufa, Samuel Asefa

doi:10.1155/2023/4668505

Cited by 2 publications

(2 citation statements)

References 46 publications

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“…Research worldwide has applied the Mpolynomial and NM-polynomial to graphene structures (see [30][31][32][33][34]). Recently, Mohammed Yasin et al [29,35] have calculated the M-polynomial and NM-polynomial concepts for biopolymer structures. In recent years, there has been a signifcant increase in research activity, particularly in the feld of topological indices and their practical applications.…”

Section: M-polynomial and Nm-polynomialmentioning

confidence: 99%

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M-Polynomial and NM-Polynomial Methods for Topological Indices of Polymers

Yasin H,

Suresh,

Tefera

et al. 2024

International Journal of Mathematics and Mathematical Sciences

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Topological indices (TIs) are numerical tools widely applied in chemometrics, biomedicine, and bioinformatics for predicting diverse physicochemical attributes and biological activities within molecular structures. Despite their significance, the challenges in deriving TIs necessitate novel approaches. This study addresses the limitations of conventional methods in dealing with dynamic molecular structures, focusing on the neighborhood M-polynomial (NM-polynomial), a pivotal polynomial for calculating degree-based TIs. Current literature acknowledges these polynomials but overlooks their limited adaptability to intricate biopolymer relationships. Our research advances by computing degree-based and neighborhood degree-based indices for prominent biopolymers, including polysaccharides, poly-γ-glutamic acid, and poly-L-lysine. Through innovative utilization of the NM-polynomial and the M-polynomial, we establish a fresh perspective on molecular structure and topological indices. Moreover, we present diverse graph representations highlighting the nuanced correlations between indices and structural parameters. By systematically investigating these indices and their underlying polynomials, our work contributes to predictive modelling in various fields. This exploration sheds light on intricate biochemical systems, offering insights into applications encompassing medicine, the food industry, and wastewater treatment. This research deepens our understanding of complex molecular interactions and paves the way for enhanced applications in diverse industries.

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Section: M-polynomial and Nm-polynomialmentioning

confidence: 99%

“…We would like to acknowledge the presentation of the manuscript as a preprint on Research Square [35]. Te corresponding author expresses gratitude for the support received from EMS-Simons for Africa, particularly during the continuation of research that is directly associated with the activities outlined in this paper.…”

Section: Acknowledgmentsmentioning

confidence: 99%

M-Polynomial and NM-Polynomial Methods for Topological Indices of Polymers

Yasin H,

Suresh,

Tefera

et al. 2024

International Journal of Mathematics and Mathematical Sciences

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QSPR/QSAR analysis of some eccentricity based topological descriptors of antiviral drugs used in COVID-19 treatment via $ \mathscr{D}\varepsilon $- polynomials

Sarkarai,

Desikan

2023

MBE

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<abstract><p>In the field of chemical and medical sciences, topological indices are used to study the chemical, biological, clinical, and therapeutic aspects of pharmaceuticals. The COVID-19 pandemic is largely recognized as the most life-threatening crisis confronting medical advances. Scientists have tested various antiviral drugs and discovered that they help people recover from viral infections like COVID-19. Antiviral medications, such as Arbidol, Chloroquine, Hydroxy-Chloroquine, Lopinavir, Remdesivir, Ritonavir, Thalidomide and Theaflavin, are often used to treat COVID-19. In this paper, we define Diameter Eccentricity Based vertex degree and employ it to introduce a new polynomial called $ D\varepsilon- $ Polynomial. Using the newly introduced polynomial, we derive new topological indices, namely, diameter eccentricity based and hyper diameter eccentricity based indices. In order to check the efficacy of our indices, we derive the $ D\varepsilon- $ polynomials for the eight COVID-19 drugs mentioned above. Using these polynomials, we compute our proposed topological descriptors for the eight COVID-19 drugs. We perform quantitative structure-property relationship (QSPR) analysis by identifying the best fit curvilinear/multilinear regression models based on our topological descriptors for 8 physico- chemical properties of the COVID-19 drugs. We also perform quantitative structure-activity relationship (QSAR) analysis by identifying the best fit multilinear regression model for predicting the $ IC_{50} $ values for the eight COVID-19 drugs. Our findings and models may be useful in the development of new COVID-19 medication.</p></abstract>

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Results on Certain Biopolymers Using M‐Polynomial and NM‐Polynomial of Topological Indices

Cited by 2 publications

References 46 publications

M-Polynomial and NM-Polynomial Methods for Topological Indices of Polymers

M-Polynomial and NM-Polynomial Methods for Topological Indices of Polymers

QSPR/QSAR analysis of some eccentricity based topological descriptors of antiviral drugs used in COVID-19 treatment via $ \mathscr{D}\varepsilon $- polynomials

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