Rong Fan , Abdul Rauf , Manal Elzain Mohamed Abdalla , Arif Nazir , Muhammad Faisal , Adnan Aslam
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引用次数: 0
Abstract
Nonsteroidal Anti-Inflammatory Drugs (NSAIDs) are a class of medications that are used for different therapeutic uses. They effectively alleviate pain, reduce inflammation, and manage fever. These drugs are available in various forms. NSAIDs are prescribed by healthcare professionals to address a wide range of symptoms, from headaches and dental pain to conditions like arthritis and muscle stiffness. In this work, we use ve-degree-based reducible topological descriptors in quantitative structure-property relationship (QSPR) analysis to estimate the physicochemical properties of NSAIDs. In the first step, we have developed a MAPLE-based code to compute the reducible ve-degree-based topological descriptors of NSAIDs. Then, a linear regression model was used to estimate four physicochemical properties of seventy NSAIDs. It has been observed that two physicochemical properties, namely Molecular Weight and Complexity show a very strong correlation with the reducible ve-degree-based topological descriptors. For both cases, the value of correlation coefficient is greater than 0.9. Finally, quadratic and cubic regression models were constructed, and a comparative analysis with these models is presented. These results may help enhance the understanding of NSAIDs medication structures and aid in predicting their pharmacological activity.
期刊介绍:
Chemometrics and Intelligent Laboratory Systems publishes original research papers, short communications, reviews, tutorials and Original Software Publications reporting on development of novel statistical, mathematical, or computer techniques in Chemistry and related disciplines.
Chemometrics is the chemical discipline that uses mathematical and statistical methods to design or select optimal procedures and experiments, and to provide maximum chemical information by analysing chemical data.
The journal deals with the following topics:
1) Development of new statistical, mathematical and chemometrical methods for Chemistry and related fields (Environmental Chemistry, Biochemistry, Toxicology, System Biology, -Omics, etc.)
2) Novel applications of chemometrics to all branches of Chemistry and related fields (typical domains of interest are: process data analysis, experimental design, data mining, signal processing, supervised modelling, decision making, robust statistics, mixture analysis, multivariate calibration etc.) Routine applications of established chemometrical techniques will not be considered.
3) Development of new software that provides novel tools or truly advances the use of chemometrical methods.
4) Well characterized data sets to test performance for the new methods and software.
The journal complies with International Committee of Medical Journal Editors'' Uniform requirements for manuscripts.