SODOCK: Swarm optimization for highly flexible protein–ligand docking
By Hung-Ming Chen, Bo-Fu Liu, Hui-Ling Huang, Shiow-Fen Hwang, Shinn-Ying Ho. 2007
128 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Molecular Biology
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Theory and Mathematics
- Shengyou Huang
- Xiaoqin Zou
- Jeffrey J. Gray
- David Baker
- Stefano Moro
- Veronica Salmaso
- Brian Kuhlman
- Tanja Kortemme
In Molecular Biology
- David Baker
- Jeffrey J. Gray
- Tanja Kortemme
- Brian Kuhlman
- Andrew Leaver-Fay
- Sergey Lyskov
- Jens Meiler
- Shengyou Huang
Citations in the corpus
- Scientific Benchmarks for Guiding Macromolecular Energy Function Improvement (2013, methodology): “OptE uses a combination of a particle swarm minimizer (Chen et al., 2007) and gradientbased minimization to optimize the loss function.”
- Advances and Challenges in Protein-Ligand Docking (2010, methodology): “Examples of docking programs that use swarm optimization algorithms include SODOCK [74], Tribe-PSO [75], PSO@Autodock [76], and PLANTS [77].”
- Software for molecular docking: a review (2017, methodology): “To date, there exists only a handful of swarm-based docking methods: SODOCK, a hybrid of PSO and Solis and Wets’ local search method (Chen et al. 2007); PLANTS, an ant colony optimization method (Korb et al.”
- Bridging Molecular Docking to Molecular Dynamics in Exploring Ligand-Protein Recognition Process: An Overview (2018, background): “Other examples of SOs are SODOCK (Chen et al., 2007), pso@autodock (Namasivayam and Günther, 2007), PSOVina (Ng et al., 2015).”
- Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go (2008, unknown): “, 2005) N/A IC SODOCK (Chen et al., 2007) N/A Swarm Optimisation SG-DOCK/SP-DOCK (Fradera et al.”
- Protein-ligand docking in the new millennium--a retrospective of 10 years in the field. (2013, methodology): “PSO@AUTODOCK is a very fast and efficient proteinligand docking program specifically designed for the treatment of highly flexible ligands and like SODOCK is based on swarm intelligence [172].”