Three-dimensional alpha shapes
ACM Transactions on Graphics (TOG)
Finding and filling protein cavities using cellular logic operations
Journal of Molecular Graphics
On the definition and the construction of pockets in macromolecules
Discrete Applied Mathematics - Special volume on computational molecular biology DAM-CMB series volume 2
Extreme elevation on a 2-manifold
SCG '04 Proceedings of the twentieth annual symposium on Computational geometry
An efficient algorithm for three-dimensional β-complex and β-shape via a quasi-triangulation
Proceedings of the 2007 ACM symposium on Solid and physical modeling
Molecular surfaces on proteins via beta shapes
Computer-Aided Design
Computer-Aided Design
Euclidean Voronoi diagram of 3D balls and its computation via tracing edges
Computer-Aided Design
Protein-Ligand Docking Based on β-shape
ISVD '09 Proceedings of the 2009 Sixth International Symposium on Voronoi Diagrams
Manifoldization of β-shapes in O(n) time
Computer-Aided Design
Manifoldization of β-shapes by topology operators
GMP'08 Proceedings of the 5th international conference on Advances in geometric modeling and processing
Convex hull and voronoi diagram of additively weighted points
ESA'05 Proceedings of the 13th annual European conference on Algorithms
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Protein-ligand docking is to predict the location and orientation of a ligand with respect to a protein within its binding site, and has been known to be essential for the development of new drugs. The protein-ligand docking problem is usually formulated as an energy minimization problem to identify the docked conformation of the ligand. A ligand usually docks around a depressed region, called a pocket, on the surface of a protein. Presented in this paper is a docking method, called BetaDock, based on the newly developed geometric construct called the β-shape and the β-complex. To cope with the computational intractability, the global minimum of the potential energy function is searched using the genetic algorithm. The proposed algorithm first locates initial chromosomes at some locations within the pocket recognized according to the local shape of the β-shape. Then, the algorithm proceeds generations by taking advantage of powerful properties of the β-shape to achieve an extremely fast and good solution. We claim that the proposed method is much faster than other popular docking softwares including AutoDock.