Abstract
<title>Abstract</title> <p> Alanine is a non-essential amino acid used in the biosynthesis of protein and it contains a carboxylic acid group and amine group. It transports nitrogen from muscles converted into glucose to the liver through the glucose-alanine cycle. In this work, Quantitative Structure-Property Relationship (QSPR) study for the physicochemical properties of alanine is carried out using selected energy-based topological indices derived from the molecular graph of alanine. The molecular structures of alanine are represented as graphs, and various energy-based topological indices are computed. Then these energies are correlated with the chosen physicochemical properties using linear regression analysis. The statistical significance and strength of the correlations are calculated using statistical parameters including the coefficient of determination(\(\:{r}^{2}\)) and correlation coefficient(\(\:r\)). The objective of this work is to examine the efficiency of energy-based topological indices using Python techniques in modeling and predicting the physicochemical properties of alanine. <bold>AMS Subject Classification:</bold> 05C09, 05C92, 92E10 </p>