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New developments in the field of chemical graph theory have made it easier to comprehend how chemical structures relate to the graphs that underlie them on a more profound level using the ideas of classical graph theory. Chemical graphs can be effectively probed with the help of quantitative structure-property relationship (QSPR) analysis. In order to statistically correlate physical attributes. Earlier research on medications motivated us to explore the quantitative structure-property relationships (QSPR) of babesiosis. We examined the babesiosis drugs data and used topological indices to do this. A measurement that reflects the theoretical characteristics of drugs is a topological index. The chemical structures of drugs that relieve pain are studied using well-known degree-based topological indices. Mepron, azithromycin, clindamycin, imidocarb, triclosan and other medications are among them. These drugs are administered to minimize or eliminate the discomfort that is felt in the affected location. The chemical structure of a molecule is represented as a graph. Further research into topological indices' QSPR analysis revealed so as a substantial link with the physical characteristics of drugs utilized in the production of drugs to halt the disease. The analysis of topological indices served as evidence for this. The results demonstrate how well the QSPR experiments on applying regression technique are useful in development of novel drugs for babesiosis and predict the characteristics of babesiosis drugs. The usefulness of applying TIs in this situation is demonstrated by the linear regression model's minimum error and correct prediction of these attributes.

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.

A topological index is a real number obtained from the chemical graph structure. It can predict the physicochemical and biological properties of many anticancer medicines like blood, breast and skin cancer. This can be done through degree-based topological indices.. In this article, the drugs, azacitidine, buslfan, mercaptopurine, tioguanine, nelarabine, etc. which are used in order to cure blood cancer are discussed and the purpose of the QSPR study is to determine the mathematical relation between the properties under investigation (eg, boiling point, flash point etc.) and different descriptors related to molecular structure of the drugs. It is found that topological indices (TIs) applied on said drugs have a good correlation with physicochemical properties in this context.

A topological index is a real number derived from the structure of a chemical graph. It helps determine the physicochemical and biological properties of a wide range of drugs, and it better reflects the theoretical properties of organic compounds. This is accomplished using degree-based topological indices. We examined some of the physiochemical characteristics of thirteen HIV therapy medications and created a QSPR model utilizing nine of the medication’s topological indices. The melting point, boiling point, flash point, complexity, surface tension, etc., of HIV medicines are closely related according to this QSPR model. This work can help to design and synthesize new HIV treatments and other disease drugs.

Due to significant advancements being made in the field of drug design, the use of topological descriptors remains the primary approach. When combined with QSPR models, descriptors illustrate a molecule’s chemical properties numerically. Numbers relating to chemical composition topological indices are structures that link chemical composition to physical characteristics. This research concentrates on the analysis of curvilinear regression models and degree-based topological descriptors for thirteen skin cancer drugs. The physicochemical characteristics of the skin cancer drugs are examined while regression models are built for computed index values. An analysis is performed for several significant results based on the acquired data.

A topological index is a molecular descriptor derived from the molecular structure of a chemical substance. These indices can be used to analyze mathematical values and predict various physical properties of drugs. This article discusses tofacitinib, leflunomide, upadacinib, baricitinib, filgotinib, methotrexate, and other drugs used to treat rheumatoid arthritis, and the goal of the QSPR study is to calculate the relationship between the properties under investigation (e.g., boiling point, polarity, and molar volume) and molecular descriptors. Topological indices (TIs) were imposed on said drugs to calculate the correlation with physicochemical properties in this course.

A topological index is a real number obtained from the chemical graph structure. It is helpful to calculate the physicochemical and biological properties of numerous drugs. This is done through degree-based topological indices. In this paper, acarbose, tolazamide, miglitol, prandin, metformin, and so on used to treat diabetes are discussed, and the purpose of the QSPR study is to determine the mathematical relation between the properties under investigation (e.g., boiling point and flash point) and different descriptors related to the molecular structure of the drugs. In this study, it is observed that topological indices (TIs) applied to said drugs have a good correlation with physicochemical properties in this course.

Counting polynomials are closely related to certain features of chemical graphs and provide an elegant means of expressing graph topological invariants. The current paper aims to calculate four polynomials for double benzenoid chains, Sadhana, omega, theta, and Padmakar–Ivan (PI). The edge-cut method is used to derive analytical closed expressions for these polynomials.

A topological index is a score function that changes each molecular structure to a unique real number. It aids in determining the physicochemical and biological properties of a wide range of drugs, and it more accurately reflects the theoretical properties of drugs. The task is accomplished through the use of degree-based topological indices (TIs). Heart disease refers to a group of disorders that affect our hearts. Heart diseases include blood vessel disorders such as irregular heartbeat and heart muscle disease. In this article, Eliquis, metoprolol, valsartan, etc., and other drugs employed to treat cardiovascular disease are studied and the QSPR analysis goal will probe the mathematical relationship of properties such as (polarity, boiling point, enthalpy, etc.) and assorted descriptors associated to drug’s structure. The present study on TIs imposed on drugs was found to have a good correlation with physical properties.