Calculating degree based multiplicative topological indices of Hyaluronic Acid-Paclitaxel conjugates’ molecular structure in cancer treatment

Molecular structural modeling and physical characteristics of anti-breast cancer drugs via some novel topological descriptors and regression models

Research is continuously being pursued to treat cancer patients and prevent the disease by developing new medicines. However, experimental drug design and development is a costly, time-consuming, and challenging process. Alternatively, computational and mathematical techniques play an important role in optimally achieving this goal. Among these mathematical techniques, topological indices (TIs) have many applications in the drugs used for the treatment of breast cancer. TIs can be utilized to forecast the effectiveness of drugs by providing molecular structure information and related properties of the drugs. In addition, these can assist in the design and discovery of new drugs by providing insights into the structure-property/structure-activity relationships. In this article, a Quantitative Structure Property Relationship (QSPR) analysis is carried out using some novel degree-based molecular descriptors and regression models to predict various properties (such as boiling point, melting point, enthalpy, flashpoint, molar refraction, molar volume, and polarizability) of 14 drugs used for the breast cancer treatment. The molecular structures of these drugs are topologically modeled through vertex and edge partitioning techniques of graph theory, and then linear regression models are developed to correlate the computed values with the experimental properties of the drugs to investigate the performance of TIs in predicting these properties. The results confirmed the potential of the considered topological indices as a tool for drug discovery and design in the field of breast cancer treatment.

Curvilinear regression analysis of benzenoid hydrocarbons and computation of some reduced reverse degree based topological indices for hyaluronic acid-paclitaxel conjugates

Graph theoretical molecular descriptors alias topological indices are a convenient means for expressing in numerical form the chemical structure encoded in a molecular graph. The structure descriptors derived from molecular graphs are widely used in quantitative structure-property relationship (QSPR) and quantitative structure-activity relationship (QSAR) studies. The reason for introducing new indices is to obtain predictions of target properties of considered molecules that are better than the predictions obtained using already known indices. In this paper, we apply the reduced reverse degree based indices introduced in 2021 by Vignesh et al. In the QSPR analysis, we first compute the reduced reverse degree based indices for a family of benzenoid hydrocarbon molecules and then we obtain the correlation with the Physico-chemical properties of the considered molecules. We show that all the properties taken into consideration for the benzenoid hydrocarbons can be very effectively predicted by the reduced reverse degree based indices. Also, we have compared the predictive capability of reduced reverse degree based topological descriptors against 16 existing degree based indices. Further, we compute the defined reduced reverse degree based topological indices for Hyaluronic Acid-Paclitaxel Conjugates [Formula: see text], [Formula: see text].

Topological Study of 6.82 D Carbon Allotrope Structure

Carbonallotropes are widely available and can be found in the atmosphere, the earth’s crust, and in living creatures in myriad forms. Allotropes are also used in several fields, including for medicinal and biological applications, due to their intriguing properties such as low resistance, high electron mobility, abnormal quantum hall effect, unconventional superconductivity in graphene, and so on. The theoretical analysis of carbon allotropes can hence be quite useful as it leads to a better understanding of the nature and behavior of these ubiquitous materials and also opens the door for even better applications. The objective of this research is to theoretically analyze the carbon allotrope by using four kinds of vertex degree based (VDB) topological indices (Tis), namely VDB multiplicative topological indices, VDB indices using M-Polynomial, VDB entropy measures, and irregularity indices. This analysis will extend the current body of knowledge available for this allotrope and help future researchers in the synthesis of new allotropes.

Neighborhood degree sum-based molecular descriptors of fractal and Cayley tree dendrimers

Topological index is a connection between the chemical structure and the real number that remains invariant under graph isomorphism. In structure-property and structure-activity modeling, topological indices are considered as essential molecular descriptors to predict different physicochemical properties of molecule. Dendrimers are considered to be the most significant, commercially accessible basic components in nanotechnology. In this report, some neighborhood degree sum-based molecular descriptors are obtained for the fractal tree and the Cayley tree dendrimers. Neighborhood M-polynomial yields a family of topological indices for a molecular graph in less time compared to the usual computation from their definitions. Some indices are obtained using neighborhood M-polynomial approach. In addition, some multiplicative neighborhood degree sum-based molecular descriptors are evaluated for fractal and Cayley tree dendrimers. The graphical representations of the outcomes are presented. A comparative study of the findings with some well-known degree-based indices is performed. Usefulness of the descriptors in modeling different properties and activities is discussed.

On the molecular structure of Remdesivir for the treatment of Covid-19

(SARS-CoV-2), was first identified in December 2019 as the cause of a respiratory illness designated coronavirus disease 2019, or Covid-19. Several therapeutic agents have been evaluated for the treatment of Covid-19, but none have yet been shown to be efficacious. Remdesivir (GS-5734), an inhibitor of the viral RNA-dependent, RNA polymerase with inhibitory activity against SARS-CoV and the Middle East respiratory syndrome (MERS-CoV), was identified early as a promising therapeutic candidate for Covid-19 because of its ability to inhibit SARS-CoV-2 in vitro. Besides, in nonhuman primate studies, remdesivir initiated 12 hours after inoculation with MERS-CoV9,10 reduced lung virus levels and lung damage. In the field of Medical Science, concerning the definition of the topological index on the molecular structure and corresponding medical, biological, chemical, pharmaceutical properties of drugs can be studied by the topological index calculation. In this paper, we compute some of the general temperature topological properties of remdesivir that the results in this paper may be useful in finding new drug and vaccine for the treatment and prevention of COVID-19.