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Context shapes: Efficient complementary shape matching for protein-protein docking
Authors:Shentu Zujun  Al Hasan Mohammad  Bystroff Christopher  Zaki Mohammed J
Institution:Department of Computer Science, Rensselaer Polytechnic Institute, Troy, New York 12180, USA.
Abstract: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 orientations of the receptor and ligand surfaces are searched using precalculated lookup tables. Energetic quantities are derived from shape complementarity and buried surface area computations, using efficient boolean operations. Preliminary results indicate that our context shapes approach outperforms state-of-the-art geometric shape-based rigid-docking algorithms.
Keywords:protein shape matching  protein docking  local shape features  protein surface representation
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