Computational Approaches to Predict NSAID Characteristics Using Degcity Indices and QSPR Analysis

Abstract

Non-steroidal anti-inflammatory drugs (NSAIDs) represent a widely utilized class of medications renowned for their analgesic, antipyretic, and anti-inflam-matory properties. Commonly prescribed and available over the counter, these drugs play a critical role in managing a variety of conditions, including acute pain, chronic inflammatory diseases, and fever. This paper has concentrated on the application of degcity indices in Quantitative Structure-Property Relationship (QSPR) research of a few physicochemical aspects of non-steroidal anti-inflammatory drugs (NSAIDs). This study also sought to calculate the regression models and degcity indices for five non-steroidal anti-inflammatory drugs (NSAIDs). Additionally, the QSPR model provides a much more accurate estimate of the molecular weight, enthalpy, molar refraction, melting point, boiling point, and polarizability of pharmaceuticals. The drugs’ molecular weight, enthalpy, molar refraction, melting and boiling points, and polarizability are all precisely predicted by the created QSPR model. For example, according to the DC₁^∗ (G) index, the correlation coefficient for molar refraction and molecular weight are 0.9763 and 0.9731, respectively. Strong relationships were found between boiling point 0.9727 and complexity 0.9754 for several indices, including DC₃^∗ (G) and DC₅^∗(G). Conversely, lesser associations were also observed, such as DC₆∗ (G) with polarizability 0.6307. These results highlight how useful degcity indices are for clarifying the physical properties of chemical compounds used in pharmaceutical research. The physical features of chemical compounds employed in the production of painkillers are strongly correlated with degcity indices, as demonstrated by the comparison of estimated and actual values for the medications.