QSPR Modeling of Nonsteroidal Anti-inflammatory Drugs (NSAIDs) Employing Reverse Degree-Based Topological Descriptors

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Rauf Abdul; Nazir Arif; - Faisal; Ali Parvez

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Journal Paper

Paper Information

Journal: ORGANIC CHEMISTRY RESEARCH Year:2024 | Volume:10 | Issue:2 Page(s): 174-187

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Information Journal Paper

Title

QSPR Modeling of Nonsteroidal Anti-inflammatory Drugs (NSAIDs) Employing Reverse Degree-Based Topological Descriptors

Author(s)

Rauf Abdul | Nazir Arif | - Faisal | Ali Parvez | Issue Writer Certificate

Keywords

Reverse degree-based topological indices

Nonsteroidal anti-inflammatory drugs (NSAIDs)

QSAR/QSPR models

Human Health

Abstract

Nonsteroidal anti-inflammatory drugs (NSAIDs) constitute a medication class often utilized to mitigate pain, reduce inflammation, and lower fevers. They are commonly employed to address symptoms such as headaches, dysmenorrhea, sprains, strains, colds, flu, coronavirus, and chronic conditions like arthritis, which entail prolonged discomfort. This study employs reverse degree-based entropy measures in quantitative structure properties relationship (QSPR) analysis to study NSAIDs medications' structure. A MATLAB program aids in computing these descriptors, facilitating the prediction of pharmacological activity. The linear regression model shows a strong relationship between the calculated indices and several physicochemical parameters of NSAIDs drugs. Comparative analysis with quadratic and cubic regression models is presented. It has been found that the reverse third Zagreb entropy, the Reverse Randić entropy and the reverse hyper Zagreb entropy are the best predictors for the considered physicochemical properties. This research enhances the understanding of Lyme medication structures and their pharmacological activity prediction.

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