Linear versus cubic regression models for analyzing generalized reverse degree based topological indices of certain latest corona treatment drug molecules

The major challenges encountered by medical researchers in developing new drugs are time consumption, increased cost, establishing a safety profile for the drugs, poor solubility, and inadequate experimental data. In its theoretical aspects, chemical graph theory plays a vital role in drug design an...

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Bibliographic Details
Published in:International journal of quantum chemistry 2023-08, Vol.123 (16), p.n/a
Main Authors: Arockiaraj, Micheal, Greeni, A. Berin, Kalaam, AR. Abul
Format: Article
Language:English
Subjects:
Ascorbic acid
Chemistry
COVID‐19 drugs
Dexamethasone
Drugs
Graph theory
Medical research
Molecular structure
Parameters
Physical chemistry
quantitative structure property relationship
Quantum physics
Regression models
reverse degree edge partition: topological indices
Topology
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Summary:The major challenges encountered by medical researchers in developing new drugs are time consumption, increased cost, establishing a safety profile for the drugs, poor solubility, and inadequate experimental data. In its theoretical aspects, chemical graph theory plays a vital role in drug design and development by analyzing the structural parameters of molecules. Topological indices aim at the mathematical representation of a molecular structure, which is used to analyze the effectiveness of drugs and enhance the drug development process. In this study, we consider certain recently used drugs such as dexamethasone, molnupiravir, nirmatrelvir, ivermectin, ribavirin, baricitinib, favipiravir, duvelisib, L‐ascorbic acid, sofosbuvir, remdesivir, and pioglitazone for omicron, delta and other variants of coronaviruses. For these drug molecules, we propose a generalized form of reverse degree parameters and compute their associated topological indices with limiting behaviors. We undertake QSPR study on the potential of generalized reverse‐degree indices using linear and cubic regression models. Medical researchers look for theoretical information in order to develop new drugs with reduced experimental costs, and topological indices can provide such information based on the structural properties of drug compounds. We examined a few recently used drug compounds in the COVID treatment and analyzed their structural properties, which in turn led to the development of linear models for predicting the physicochemical information of drug compounds.
ISSN:0020-7608
1097-461X
DOI:10.1002/qua.27136