Context shapes: Efficient complementary shape matching for protein-protein docking
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Updated: Jul 11, 2026

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
Published on: June 20, 2025
Zujun Shentu1, Mohammad Al Hasan, Christopher Bystroff
1Department 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.
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