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].

Study the Behavior of Drug Structures via Chemical Invariants Using TOPSIS and SAW

Every year, various experiments emerge in which a strong link between topological chemical structures and their properties is found. These properties are numerous such as melting point, boiling point, and drug toxicity. Topological index is the functional tool to determine these properties. This research paper will analyze some of the molecular drug structures, i.e., hyaluronic acid-paclitaxel conjugates G _n , anticancer drug SP[n], polyomino chain of n-cycle Z _n , triangular benzenoid T _n , and circumcoronene benzenoid series H _k using multicriteria decision-making techniques including TOPSIS and SAW. The topological indices used in this research paper include the Randić index for α = 1, -1, 1/2, the augmented Zagreb index and the forgotten topological index.

Biopolymeric Prodrug Systems as Potential Antineoplastic Therapy

Nowadays, cancer represents a major public health issue, a substantial economic issue, and a burden for society. Limited by numerous disadvantages, conventional chemotherapy is being replaced by new strategies targeting tumor cells. In this context, therapies based on biopolymer prodrug systems represent a promising alternative for improving the pharmacokinetic and pharmacologic properties of drugs and reducing their toxicity. The polymer-directed enzyme prodrug therapy is based on tumor cell targeting and release of the drug using polymer–drug and polymer–enzyme conjugates. In addition, current trends are oriented towards natural sources. They are biocompatible, biodegradable, and represent a valuable and renewable source. Therefore, numerous antitumor molecules have been conjugated with natural polymers. The present manuscript highlights the latest research focused on polymer–drug conjugates containing natural polymers such as chitosan, hyaluronic acid, dextran, pullulan, silk fibroin, heparin, and polysaccharides from Auricularia auricula.

Treatment of COVID-19 Patients Using Some New Topological Indices

COVID-19 is causing havoc to human health and the world economy right now. It is a single standard positive-sense RNA virus which is transferred by inhalation of a viral droplet. Its genome forms four structural proteins such as nucleocapsid protein, membrane protein, spike protein, and envelop protein. The capsid of coronavirus is a protein shell within which a positive strand of RNA is present which enables the virus to control the machinery of human cells. It has several variants, e.g., SARS, MERS, and now a new variant identified in 2019, which is a novel coronavirus that causes novel coronavirus disease (COVID-19). COVID-19 is a novel coronavirus disease that originally arose in Wuhan, China, and quickly spread around the world. Clinically, we identified the virus presence by a PCR-based test. Preventive measures and vaccination are the only treatment against coronavirus. Some of these include Remdesivir (GS-5734), Chloroquine, Hydroxychloroquine, and Theaflavin. A topological index (TI) is a mathematical function that assigns a numerical value to a (molecular) graph and predicts many physical, chemical, biological, thermodynamical, and structural features of that network. In this work, we will calculate a new topological index, namely, the first and second Gourava and Hyper-Gourava indices for the molecular graph of Remdesivir (GS-5734), Chloroquine, Hydroxychloroquine, and Theaflavin. We also plotted our computed results to examine how they were affected by the parameters involved. These findings could contribute in the development of new COVID-19 therapy options.

Cyclic connectivity index of bipolar fuzzy incidence graph

In the performance characterization of chemical molecular structures, several uncertain properties are often encountered, and fuzzy theory is precisely the tool to characterize these uncertainties. When molecular structures are described by molecular graphs, the corresponding fuzzy graph theory is used to characterize the uncertainty of atoms and atomic bonds. In this study, there is introduced cyclic connectivity index and its average version for bipolar fuzzy incidence graph (BFIG), and several theoretical results are obtained in the light of graph theory and fuzzy theory. Finally, the given new fuzzy index is applied to the testing of anti-aging-related drugs yields average uncertainty data for the corresponding molecular structures.

On Ve-Degree and Ev-Degree Topological Properties of Hyaluronic Acid‐Anticancer Drug Conjugates with QSPR

The design of the quantitative structure-property/activity relationships for drug-related compounds using theoretical methods relies on appropriate molecular structure representations. The molecular structure of a compound comprises all the information required to determine its chemical, biological, and physical properties. These properties can be assessed by employing a graph theoretical descriptor tool widely known as topological indices. Generalization of descriptors may reduce not only the number of molecular graph-based descriptors but also improve existing results and provide a better correlation to several molecular properties. Recently introduced ve-degree and ev-degree topological indices have been successfully employed for development of models for the prediction of various biological activities/properties. In this article, we propose the general ve-inverse sum indeg index ${\text{ISI}}_{\left(\alpha ,\beta \right)}^{\text{ve}}\left(G\right)$ and general ve-Zagreb index $M_{\alpha }^{\text{ve}}\left(G\right)$ of graph $G$ and compute ${\text{ISI}}_{\left(\alpha ,\beta \right)}^{\text{ve}}\left(G\right),M_{\alpha }^{\text{ve}}\left(G\right)$ , and $M_{\alpha }^{\text{ev}}\left(G\right)$ (general ev-degree index) of hyaluronic acid-curcumin/paclitaxel conjugates, renowned for its potential anti-inflammatory, antioxidant, and anticancer properties, by using molecular structure analysis and edge partitioning technique. Several ve-degree- and ev-degree-based topological indices are obtained as a special case of ${\text{ISI}}_{\left(\alpha ,\beta \right)}^{\text{ve}}\left(G\right),M_{\alpha }^{\text{ve}}\left(G\right)$ , and $M_{\alpha }^{\text{ev}}\left(G\right)$ . Furthermore, QSPR analysis of ${\text{ISI}}_{\left(\alpha ,\beta \right)}^{\text{ve}}\left(G\right),M_{\alpha }^{\text{ve}}\left(G\right)$ , and $M_{\alpha }^{\text{ev}}\left(G\right)$ for particular values of $\alpha$ and $\beta$ is performed, which reveals their predicting power. These results allow researchers to better understand the physicochemical properties and pharmacological characteristics of these conjugates.

Topological Study of Hydroxychloroquine Conjugated Molecular Structure Used for Novel Coronavirus (COVID-19) Treatment

The novel coronavirus disease 2019 (Covid-19) is a mutating and recombining pandemic that potentially spreading through an infected person in droplet-generated forms that have affected more than 200 countries and endanger the entire globe. There is no clear strategy for the care of COVID-19 cases. Moreover, experts across the globe are working actively to develop medicinal or anti-virus drugs. On the basis of recent clinical findings and recommendations, the study examined a variety of new medications that have shown antiviral activity against SARS-CoV-2, among other drugs, antimalarial medications Chloroquine (CQ) and Hydroxychloroquine (HCQ) have gained significant publicity to have promising effects against SARS-CoV-2. Linking a bioactive substance to a biocompatible polymer typically provides various concerns, such as improved drug solubilization, improved modification, precise restriction, and controlled discharge. An enormous number of medical analyses have confirmed that the characteristics of medical drugs have a nearby connection with their atomic structure. Medication properties can be acquired by considering the atomic structure of relating drugs. The calculation of the topological index of a medication structure empowers researchers to have a superior comprehension of the physical science and bio-organic attributes of drugs. Ev-degree and ve-degree based topological indices are two novel degrees based indices as of late defined in graph theory. Ev-degree and ve-degree based topological indices have been defined as corresponding to their relating partners. In this paper, we have computed topological indices based on ev-degree and ve-degree for the Hydroxyethyl Starch and Hydroxychloroquine (HCQ-HEC) bioconjugate molecular structure.

Degree-based topological indices and polynomials of hyaluronic acid-curcumin conjugates

Quantitative structure–activity relationship (QSAR) represents quantitative correlation of chemical structural features called as molecular descriptors and pharmacological activity as response endpoints. Topological index is a molecular descriptor extensively used to study QSAR of pharmaceuticals to assess their molecular characteristics by numerical computation. Theoretical assessment of drug like molecules helps to expedite the drug design and discovery process by rationalizing the lead identification, lead optimization and understanding their mechanism of actions. Therefore, in this article, we have computed the general inverse sum indeg index, ISIα,β of Hyaluronic acid-curcumin conjugates by using molecular structure analysis and edge partitioning technique. Many standard topological indices are obtained as a special case of ISIα,β. We also proposed general inverse sum indeg polynomial ISIα,β(Gn,x) of Hyaluronic acid-curcumin conjugates from which many well-known polynomials are deduced.

Topological Indices of Some Chemical Structures Applied for the Treatment of COVID-19 Patients

The novel coronavirus disease 2019 (COVID-19) emerged in Wuhan, China, and has spread rapidly to nearly every part of the world. Unfortunately, no drug or vaccine has been accepted for the treatment of this pandemic. Researchers have established the efficacy of some existing antiviral drugs to control COVID-19 in vitro. Some of them are remdesivir (GS-5734), chloroquine, hydroxychloroquine, theaflavin. Topological indices are mathematical interpretations of a molecule generated by an algorithm implemented to a given molecular representation. Topological indices are used to model different physicochemical properties and biological activities of chemical compounds. In this work, some degree-based and neighborhood degree sum-based topological indices are investigated for the aforesaid antiviral drugs using polynomial approach. The results obtained can aid in the design of new medicine for the treatment of COVID-19.

Topological Descriptor of 2-Dimensional Silicon Carbons and Their Applications

The Chemical graph theory is extensively used in finding the atomic supplementary properties of different chemical stuructures. Many results of graph theory are commonly used in molecular structures and in general in Chemisty. In a molcular graph vertices are atoms while chemical bonds are given by edges. This article is about computing the exact values for some degree based toplogical descriptors of two molecular structures. Namely we work on the silicon-carbon Si2C3- III and SiC3-III for dimension two. We also discuss some applications of these results towards Chemistry.

Molecular dynamics simulation of anticancer drug delivery from carbon nanotube using metal nanowires

In this study, we have investigated delivery of cisplatin as the anticancer drug molecules in different carbon nanotubes (CNTs) in the gas phase using molecular dynamics simulation. We examined the shape and composition of the releasing agent by using the different nanowires and nanoclusters. We also investigated the doping effect on the drug delivery process using N-, Si, B-, and Fe-doped CNTs. Different thermodynamics, structural, and dynamical properties have been studied by using the pure and different doped CNTs in this study. Our results show that the doping of the CNT has significant effect on the rate of the drug releasing process regardless of the composition of the releasing agent. © 2019 Wiley Periodicals, Inc.