A Novel Geometric Algorithm for Protein Pocket Extraction, Quantification And Visualization

Molecular surfaces of proteins and other bio-molecules, while modeled as smooth analytic interfaces separating the molecule from solvent, often contain a number of pockets, holes and interconnected tunnels, aka molecular features in contact with the solvent. Several of these molecular features are biochemically significant as pockets are often active sites for ligand binding or enzymatic reactions, and tunnels are often solvent ion conductance zones. Since pockets or holes or tunnels share similar surface feature visavis their openings (mouths), we shall sometimes refer to these molecular features collectively as generalized pockets or pockets. In this paper we focus on elucidating all these pocket features of a protein (from its atomistic description), via a simple and practical geometric algorithm. We use a two-step level set marching method to compute a volumetric pocket function P (x) as the result of an outward and backward propagation. The regions inside pockets can be represented as P (x) > 0 and the pocket bounding surface is computed as the level set P (x) = 0. The pocket function P (x) can be computed efficiently by fast distance transforms. This volumetric representation allows pockets to be analyzed quantitatively and visualized with various techniques. Such feature analysis and quantitative visualization approaches work with any description of molecular surfaces and are also generalizable to many other classes of smooth and analytic free-form surfaces or interface boundaries.