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The study focused on QSPR (Quantitative Structure-Property Relationship) analysis using a variety of topological indices on the medications Mefloquinone, Sertraline, Niclosamide, Tizoxanide, PHA-690509, Ribavirin, Emricasan, and Sofosbuvir. Through the use of computational modeling approaches, the study sought to determine how these medications' chemical structures relate to their individual qualities. The discovered results provided information on the quantitative correlations between structural characteristics and pharmacological qualities, allowing for better comprehension and forecast of their behavior. The results of this study make a positive contribution to the field of medication discovery and design by offering important knowledge about the structure-property correlations of these medicinal molecules. In this article, we focus on using topological indices and a linear regression model to successfully predict various pharmacological features. This method enables more effective drug discovery and development by providing insights into the connection between molecular structure and pharmacological characteristics. We can improve our comprehension of drug behavior and assist targeted drug design by utilizing topological indices and regression analysis. [ABSTRACT FROM AUTHOR]

QSPR analysis can be used in a variety of applications, such as drug discovery, materials science, and environmental chemistry. For example, QSPR models can be used to predict the toxicity of new chemicals, to design more effective drugs, or to optimize the properties of materials for specific applications. Phenolic compounds act as anti-oxidants, anti-carcinogenic, and anti-bacterial agents present in Moringa oleifera. These Phenolic compounds have significant antioxidant properties as they can scavenge free radicals, slow the aging process, and improve glucose uptake in muscles. They are also used to prevent the accumulation of lipids in the liver and subsequently prevent fatty liver disease, protect kidneys, prevent cancer, prevent whitening skin, chemopreventive for cancer, induce apoptosis in ovarian cancer, protect kidneys, decrease pro-inflammatory enzymes, and increase antioxidants enzymes. Furthermore, phenolic compounds inhibit enzymes linked to diabetes type-2 and they can be used to cure diabetes. Owing to the significance of these phenolic compounds, we carried out QSPR analysis using degree-based indices to know the physical characteristics affiliated with them. The outcomes indicate that these phenolic compounds could be investigated further by pharmacists and chemists when designing drugs using these topological indices values. Since the correlation for the topological indices has been discovered, positively correlated compounds may be considered for the combination of novel drug designs. Also, the computed results are useful to predict the physical properties of the phenolic compounds. [ABSTRACT FROM AUTHOR]

For a graph G an edge-covering of G is a family of subgraphs H1, H2, . . . , Ht such that each edge of E(G) belongs to at least one of the subgraphs Hi, i = 1, 2, . . . , t. In this case we say that G admits an (H1, H2, . . . , Ht)-(edge) covering. An H-covering of graph G is an (H1, H2, . . . , Ht)-(edge) covering in which every subgraph Hi is isomorphic to a given graph H.

Porous materials, for example, metalnatural structures (MOFs) and their discrete partners metalnatural polyhedra (MOPs), that are built from coordinatively unsaturated inorganic hubs show incredible potential for application in gas adsorption/partition cycles, catalysis, and arising openings in hardware, optics, detecting, and biotechnology. A well-known hetero-bimetallic metalorganic polyhedra of this discrete partners metalnatural polyhedra (MOPs) class is cuboctahedral bi-metallic stricture. In this paper, we discuss the stricture of Hetero-bimetallic metalorganic polyhedra (cuboctahedral bi-metallic). Also, we computed the topological indices based on the degree of atoms in this cuboctahedral bi-metallic structure.

A topological descriptor is a mathematical illustration of a molecular construction that relates particular physicochemical properties of primary molecular structure as well its mathematical depiction. Topological co-indices are usually applied for quantitative structure actions relationships (QSAR) and quantitative structures property relationships (QSPR). Topological co-indices are topological descriptors which are considered the noncontiguous vertex set. We study the accompanying some renowned topological co-indices: first and second Zagreb co-indices, first and second multiplicative Zagreb co-indices and the F-coindex, and some other degree-based indices of the co-indices of ceria oxide.

A polymer is a substance or material consisting of very large molecules called macromolecules, composed of many repeating subunits. The bulky and normal polymers are graphs of aromatic organic compounds. The main idea of this article is to elaborate the expected results of Zagreb connection, sombor and reduced sombor indices in bulky and normal polymers. The generalized expected results with the help of probability technique for all the chains like polyonino, pentachain, polyphenyl, cyclooctane cyclodecane and so on different chains for Alkanes have been determined which are connected with and without any bond (edge). The Sombor topological index is named after the city of Sombor in Serbia, where it was introduced by a group of researchers in the field of chemoinformatics and mathematical chemistry. At the end, we have find the meta, ortho and para polymers to define the average values of Zagreb connection, Sombor and reduced Sombor indices. [ABSTRACT FROM AUTHOR]

The use of chemical graph theory has been increased in almost every field of science in the last two decades. The graph invariants called topological descriptor are the numbers used to understand the physical and chemical properties of compounds. The use of narcotics causes many health and social issues in society. Narcotic drug addiction results in decreased pain perception, euphoria, dizziness, physical dependence, decreased breathing, and sleepiness in people. The overuse of narcotics may cause death. For the care and treatment of drug addictions, special health institutes provide proper medicines. The structures of narcotic drugs are explored with the help of degree-based graph invariants. In this article, we used degree-based topological indices to estimate the properties of narcotic drugs. Moreover, we have obtained that the topological indices utilize the antinarcotics drugs have a very strong correlation with the physicochemical properties mentioned in this manuscript. [ABSTRACT FROM AUTHOR]

Asthma is a widespread disease that has affected more than 300 million people worldwide. There is no efficient or preventive treatment for this disease yet. Drug scientists are striving hard to discover a variety of medicines that can treat asthma effectively. Quantitative structure‐property relationship (QSPR) analysis of drugs used in the treatment of a specific disease through topological descriptors is one of the best techniques adopted by drug scientists to cut down unnecessary laboratory expenses. In this article, we have done a QSPR analysis to identify the best predictor for the six properties namely, boiling point, enthalpy, flash point, log P, molar volume, and molar refractivity of 19 different anti‐asthmatic drugs using a set of 16 distance‐based topological indices. Also, we compare our results with QSPR analysis done by using certain degree‐based indices for the chosen drugs and obtain new directions. [ABSTRACT FROM AUTHOR]