A new protein binding pocket similarity measure based on comparison of clouds of atoms in 3D: application to ligand prediction

Background: Predicting which molecules can bind to a given binding site of a protein with known 3D structure is important to decipher the protein function, and useful in drug design. A classical assumption in structural biology is that proteins with similar 3D structures have related molecular functions, and therefore may bind similar ligands. However, proteins that do not display any overall sequence or structure similarity may also bind similar ligands if they contain similar binding sites. Quantitatively assessing the similarity between binding sites may therefore be useful to propose new ligands for a given pocket, based on those known for similar pockets. Results: We propose a new method to quantify the similarity between binding pockets, and explore its relevance for ligand prediction. We represent each pocket by a cloud of atoms, and assess the similarity between two pockets by aligning their atoms in the 3D space and comparing the resulting configurations with a convolution ke...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Brice Hoffmann, Mikhail Zaslavskiy, Jean-Philippe Vert, Véronique Stoven
• Keywords: Binding Site, BMCBI 2010, Ligands, Pockets