Fundamental Aspects of Skin Cancer Drugs via Degree-Based Chemical Bonding Topological Descriptors

Khan, Abdul Rauf; Awan, Nadeem Ul Hassan; Ghani, Muhammad Usman; Eldin, Sayed M.; Karamti, Hanen; Jawhari, Ahmed Hussain; Mukhrish, Yousef E.

doi:10.3390/molecules28093684

Cited by 23 publications

(7 citation statements)

References 25 publications

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“…Earlier studies on covid-19, blood cancer, anti-cancer, and QSPR different TIs for various chemical structures motivate us much. Recently QSPR Analysis of varying skin cancer drugs are presented by Khan et al in [ 21 ]. Sultana [ 22 ] probe into infertility drugs QSPR modeling in well versed way and made valuable contribution.…”

Section: Methodsmentioning

confidence: 99%

Multicriteria decision making attributes and estimation of physicochemical properties of kidney cancer drugs via topological descriptors

Husin,

Khan,

Awan

et al. 2024

PLoS ONE

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Based on topological descriptors, QSPR analysis is an incredibly helpful statistical method for examining many physical and chemical properties of compounds without demanding costly and time-consuming laboratory tests. Firstly, we discuss and provide research on kidney cancer drugs using topological indices and done partition of the edges of kidney cancer drugs which are based on the degree. Secondly, we examine the attributes of nineteen drugs casodex, eligard, mitoxanrone, rubraca, and zoladex, etc and among others, using linear QSPR model. The study in the article not only demonstrates a good correlation between TIs and physical characteristics with the QSPR model being the most suitable for predicting complexity, enthalpy, molar refractivity, and other factors and a best-fit model is attained in this study. This theoretical approach might benefit chemists and professionals in the pharmaceutical industry to forecast the characteristics of kidney cancer therapies. This leads towards new opportunities to paved the way for drug discovery and the formation of efficient and suitable treatment options in therapeutic targeting. We also employed multicriteria decision making techniques like COPRAS and PROMETHEE-II for ranking of said disease treatment drugs and physicochemical characteristics.

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Section: Methodsmentioning

confidence: 99%

Multicriteria decision making attributes and estimation of physicochemical properties of kidney cancer drugs via topological descriptors

Husin,

Khan,

Awan

et al. 2024

PLoS ONE

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“…Lei Huang et al [26] looked into topological indices and QSPR modeling of new antiviral drugs for cancer treatment using curve-fitting models in 2022. Abdul Rauf Khan et al [27] discussed fundamental aspects of skin cancer drugs using degree-based chemical bonding topological descriptors in 2023. Dhanajayamurthy et al [28] investigated reduced neighbourhood degree-based topological indices on anti-cancer drugs with QSPR analysis in 2022.…”

Section: Fundamental Definitions and Literature Reviewmentioning

confidence: 99%

“…From table 13, it is observed that the calculated value of χ 2 for all the properties except C and MV are less than the critical value of χ 2 obtained from the χ 2 distribution table at 5% level of significance with degrees of freedom 18. Thus, we accept all the regression models except models (27) and (28).…”

Section: Multi-variate Regression Analysismentioning

confidence: 99%

Estimating physico-chemical properties of drugs for prostate cancer using degree-based and neighbourhood degree-based topological descriptors

Balasubramaniyan,

Chidambaram,

Ravi

2024

Phys. Scr.

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Prostate cancer is one of the most alarming diseases among men and leads to various illnesses. The main flaw in this disease is that there is not a single test that can find it. Prostate-specific antigens and prostate biopsies are used to identify this type of cancer. Many pharmaceutical industries do active research to identify non-steroidal drugs that can be used to treat prostate cancer effectively. QSPR analysis is one of the best practices that aid scientists in getting a deep insight into the physico-chemical properties of drugs without actually performing experiments in a wet lab, thereby cutting down on the cost of manufacturing such drugs. In this article, we perform a QSPR analysis of nineteen drugs primarily used to treat prostate cancer by using a set of ten degree-based indices and another set of ten novel neighbourhood-degree-based indices. In addition, we have done a comparative study of the findings obtained through these two different sets of indices over thirteen physico-chemical properties of prostate cancer drugs.

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“…Applying the npdegree approach to the harmonic index has led to its success. Khan et al examine the drugs used to treat skin cancer by degree-related TIs, especially H-index [27]. The harmonic index measures a molecule's structural complexity by considering the distances between atoms.…”

Section: Basic Definitions and Literature Reviewmentioning

confidence: 99%

Investigating the properties of octane isomers by novel neighborhood product degree-based topological indices

Rasheed,

Mahboob,

Hanif

2024

Front. Phys.

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A topological index is a real number calculated from the structure of a chemical compound to describe its topology. The use of molecular descriptors has been increasing in recent years, helping to determine the physicochemical and biological properties of drugs. The main purpose of this article is to investigate the properties of the octane isomers using the theoretical method. To study the structures of octane isomers, we have introduced a new approach called “neighborhood product degree” to calculate all the classical degree-based topological indices. The np-degree approach is applied to approximate eight properties of octane isomers, such as the acentric factor, density, refractive index, critical volume, molar volume, radius of curvature, critical pressure, and LogP. The np-degree-based topological indices are the estimated values of the properties of octane structures, so the linear and quadratic regression models and correlation coefficients are applied to check the validity of the estimated results. The quantitative structure property relation are obtained by using the linear, quadratic, exponential, logarithmic and sinusoidal regression methods with the help of SPSS. Two models are applied to all the compuations and three regression models are applied to the np-degree Randic index. The computation showed that quadratic regression model is suitable for study octane isomers and np-degree based graph invariants. If the values of the correlation coefficient r ⩾ 0.7, p-values ⩽ 0.05, and F-values ⩾ 2.5, then the results are significant. The results of np-degree-based topological indices satisfy all the criteria for being significant, so these newly introduced indices are valid to study octane isomers. The information determined in this article is beneficial for chemists and pharmacists.

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Fundamental Aspects of Skin Cancer Drugs via Degree-Based Chemical Bonding Topological Descriptors

Cited by 23 publications

References 25 publications

Multicriteria decision making attributes and estimation of physicochemical properties of kidney cancer drugs via topological descriptors

Multicriteria decision making attributes and estimation of physicochemical properties of kidney cancer drugs via topological descriptors

Estimating physico-chemical properties of drugs for prostate cancer using degree-based and neighbourhood degree-based topological descriptors

Investigating the properties of octane isomers by novel neighborhood product degree-based topological indices

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