CALI: A Novel Visual Model for Frequent Pattern Mining in Protein-Ligand Graphs

Abstract

Protein-ligand interaction (PLI) networks show how proteins interact with small non-protein ligands through noncovalent bonding. Understanding such interactions is a crucial step towards ligand prediction, target identification and drug design. We propose CALI (Complex network-based Analysis of protein-Ligand Interactions), a graph-based, visual strategy coupled with complex network topological properties to summarize and detect frequent patterns in PLIs. Patterns obtained with CALI were compared to experimentally determined protein-ligand interactions from the CDK2 and Ricin dataset. For the CDK2, CALI found 90% of interacting residues, and all residues of the Ricin that interact with ligands. We devised a powerful visual and interactive strategy to analyze the data, providing a general view of the interaction dataset, showing the most common PLIs from a global perspective.