ABSTRACT
Topological indices play an essential role in defining a chemical compound numerically and are widely used in QSPR/QSAR analysis. Using this analysis, physicochemical properties of the compounds and the topological indices are studied. Quinolones are synthetic antibiotics employed for treating the diseases caused by bacteria. Across the years, Quinolones have shifted its position from minor drug to a very significant drug to treat the infections caused by bacteria and in the urinary tract. A study is carried out on various Quinolone antibiotic drugs by computing topological indices through QSPR analysis. Curvilinear regression models such as linear, quadratic and cubic regression models are determined for all topological indices. These regression models are depicted graphically by extending for fourth degree and fifth degree models for significant topological indices with its corresponding physical property showing the variation between each model. Various studies have been carried out using linear regression models while this work is extended for curvilinear regression models using a novel concept of finding minimal R M S E . R M S E is a significant measure to find potential predictive index that fits QSAR/QSPR analysis. The goal of R M S E lies in predicting a certain property of a chemical compound based on the molecular structure.
ABSTRACT
The novel applications in chemistry include the mathematical models of molecular structure of the compounds which has numerous findings in this area that refers to mathematical chemistry. Topological descriptors play a major role in QSAR/QSPR studies that analyses the biological and physicochemical properties of the compounds. In the recent times, a new type of topological descriptors are proposed, called K-Banhatti indices. In this study the chemical applicability of K-Banhatti indices are examined for benzenoid hydrocarbons (derivatives of benzene). These indices have shown remarkable results through the study of statistical analysis. Subsequently, triazine-based covalent organic frameworks (CoF's) are studied for which [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and HB(G) of a graph G are computed.
ABSTRACT
The use of topological descriptors is the key method, regardless of great advances taking place in the field of drug design. Descriptors portray the chemical characteristic of a molecule in numerical form, that is used for QSAR/QSPR models. The numerical values related with chemical constitutions that correlate the chemical structure with the physical properties refer to topological indices. The study of chemical structure with chemical reactivity or biological activity is termed quantitative structure activity relationship, in which topological index plays a significant role. Chemical graph theory is one such significant branch of science which plays a key role in QSAR/QSPR/QSTR studies. This work is focused on computing various degree-based topological indices and regression model of nine anti-malaria drugs. Regression models are fitted for computed indices values with 6 physicochemical properties of the anti-malaria drugs are studied. Based on the results obtained, an analysis is carried out for various statistical parameters for which conclusions are drawn.
Subject(s)
Antimalarials , Quantitative Structure-Activity RelationshipABSTRACT
[This corrects the article DOI: 10.1016/j.heliyon.2020.e04235.].
ABSTRACT
From last two to three decades, the world is facing the threat of finding treatment for Cancer. This disease is striking almost ten million people every year throughout the world. Anticancer drugs are those which are used to cure malignant disease i.e. Cancer. These anticancer drugs are available in different forms including alkalyting agents, hormones and anti metabolites. Various examinations reveals that, there will be a adjacent relationship between the characteristics of alkanes and the anticancer drugs viz. Boiling point, melting point, enthalpy etc. with their chemical structures. In this proposed work, various topological indices are defined on some anticancer drugs to help the researchers to know the physical characteristics and chemical reaction associated with them. We also discuss the QSPR analysis of thirteen degree based topological indices. Further, we showcase that the characteristics have good correlation with physico-chemical characteristics of anticancer drugs.
