GReMLIN: A Graph Mining Strategy to Infer Protein-Ligand Interaction Patterns

Interactions between proteins and ligands are relevant in many biological processes. In the last years, such interactions have gained even more attention as the comprehension of protein-ligand molecular recognition is an important step to ligand prediction, target identificantion, and drug design, among others. This article presents GReMLIN (Graph Mining strategy to infer protein-Ligand INteraction patterns), a strategy to search for conserved protein-ligand interactions in a set of related proteins, based on frequent subgraph mining, that is able to perceive structural arrangements relevant for protein-ligand interaction. When compared to experimentally determined interactions, our in silico strategy was able to find many of relevant binding site residues/atoms for CDK2 and active site residues/atoms for Ricin.