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Ph.D. ThesesContext Shapes: A Novel Approach for Partial Complementary Shape Matching Proteins
By Zujun Shentu
All biochemical processes involve some kind of molecular recognition, which can be defined as the formation of an energetically favorable docking between two molecules. Docking between proteins is involved in many cellular processes including cell signaling, regulation of enzyme function, intra-cellular trafficking, transcriptional regulation, the immune response, and many others. Interactions between proteins are governed by the kinetics and stability of the docked conformation, or "pose". The kinetics of interactions is governed by the concentration of each molecular species in the cell, its sub-cellular location, and by its surface electrostatics. The stability of a pose is governed by the surface electrostatics and by the surface shape complementarity. Shapes that are more nearly complementary will fill space better when docked. The energetic stability of a pose can be approximated by the amount of surface area excluded from solvent, which is approximately the total area over which the two surfaces are complementary. We describe an efficient method for partial complementary shape matching for use in rigid protein-protein docking. The local shape features of a protein are represented using boolean data structures called Context Shapes. The relative orientation of the receptor and ligand surfaces is searched using pre-calculated lookup tables. Energetic quantities are derived from shape complementarity and buried surface area computations using efficient boolean operations. Preliminary results on 84 bound cases from the latest version of a benchmark indicate that our context shapes based approach outperforms state-of-the-art geometric shape based rigid docking algorithms like ZDOCK(PSC) and PatchDock.
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Research
