A graph mining based detection and visualization of conserved motifs in 3D protein-ligand interface at the atomic level

Interactions between proteins and non-proteic small molecule ligands play important roles in biological processes of living systems. Thus the development of computational methods to support on the understanding of the ligand-receptor recognition process is of fundamental importance, since this this is a major step towards ligand prediction, target identification, lead discovery, among others. This article presents visGReMLIN, a web server that couples a graph mining based strategy to detect motifs in the protein ligand interface and an interactive platform to visually explore and interpret such motifs in the context of protein-ligand interfaces. We intended to contribute a visual analytics oriented web server to detect and visualize common motifs in protein-ligand interface. To illustrate the ability of visGReMLIN to do so, we conducted 2 use cases in which our strategy was compared with previous experimentally and computationally determined results. Our strategy allowed us to detect patterns previously documented in the literature in a totally visual manner. In addition, we found some motifs we believe are relevant for protein-ligand interaction in the analyzed datasets

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