Investigating the Connection between Atom Connectivity, Connectivity Energy, and the Physico-Chemical Properties of Amino Acids

This research explores the use of molecular graph theory to predict the physical and chemical properties of twenty amino acids. Specifically, it examines how the energy of a graph, derived from the eigenvalues of an adjacency matrix, correlates with the chemical reactivity of amino acids. In molecular graph theory, a chemical compound is represented as a graph, where atoms are treated as nodes and bonds as edges. The energy of the graph is calculated by summing the absolute values of the eigenvalues of the adjacency matrix. However, the basic adjacency matrix treats all atoms and bonds as equivalent, which can limit the accuracy of predictions. To address this, the research introduces atom-connectivity matrices and connectivity matrices to better differentiate between different types of atoms and bond connectivity. The key proposition of this research is that by incorporating atom-connectivity matrices, predictions of amino acid properties are more accurate than those based solely on the adjacency matrix.