Journal of Computational Chemistry
Three-dimensional alpha shapes
ACM Transactions on Graphics (TOG)
A combinatorial approach to protein docking with flexible side-chains
RECOMB '00 Proceedings of the fourth annual international conference on Computational molecular biology
Protein Conformation of a Lattice Model Using Tabu Search
Journal of Global Optimization
Efficient Collision Detection Using Bounding Volume Hierarchies of k-DOPs
IEEE Transactions on Visualization and Computer Graphics
Side Chain-Positioning as an Integer Programming Problem
WABI '01 Proceedings of the First International Workshop on Algorithms in Bioinformatics
The smallest enclosing ball of balls: combinatorial structure and algorithms
Proceedings of the nineteenth annual symposium on Computational geometry
The side-chain positioning problem: a semidefinite programming formulation with new rounding schemes
PCK50 Proceedings of the Paris C. Kanellakis memorial workshop on Principles of computing & knowledge: Paris C. Kanellakis memorial workshop on the occasion of his 50th birthday
A Semidefinite Programming Approach to Side Chain Positioning with New Rounding Strategies
INFORMS Journal on Computing
Optimization Methods & Software - Systems Analysis, Optimization and Data Mining in Biomedicine
Region-expansion for the Voronoi diagram of 3D spheres
Computer-Aided Design
Computer-Aided Design
Euclidean Voronoi diagram of 3D balls and its computation via tracing edges
Computer-Aided Design
Quasi-worlds and quasi-operators on quasi-triangulations
Computer-Aided Design
Three-dimensional beta-shapes and beta-complexes via quasi-triangulation
Computer-Aided Design
Querying simplexes in quasi-triangulation
Computer-Aided Design
Bioinformatics
Rapid protein side-chain packing via tree decomposition
RECOMB'05 Proceedings of the 9th Annual international conference on Research in Computational Molecular Biology
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A molecular structure determines a molecular function(s) and a correct understanding of molecular structure is important for biotechnology. The computational prediction of molecular structure is a frequent requirement for important biomolecular applications such as a homology modeling, a docking simulation, a protein design, etc. where the optimization of molecular structure is fundamental. One of the core problems in the optimization of protein structure is the optimization of side-chains called the side-chain positioning problem. The side-chain positioning problem, assuming the rigidity of backbone and a rotamer library, attempts to optimally assign a rotamer to each residue so that the potential energy of protein is minimized in its entirety. The optimal solution approach using (mixed) integer linear programming, with the dead-end elimination technique, suffers even for moderate-sized proteins because the side-chain positioning problem is NP-hard. On the other hand, popular heuristic approaches focusing on speed produce solutions of low quality. This paper presents an efficient algorithm, called the BetaSCP, for the side-chain positioning problem based on the beta-complex which is a derivative geometric construct of the Voronoi diagram. Placing a higher priority on solution quality, the BetaSCP algorithm produces a solution very close to the optima within a reasonable computation time. The effectiveness and efficiency of the BetaSCP are experimentally shown via a benchmark test against well-known algorithms using twenty test models selected from Protein Data Bank.