Int. J. Mol. Sci. 2008, 9(1), 65-77; doi:10.3390/ijms9010065
Article

Computational Study for Protein-Protein Docking Using Global Optimization and Empirical Potentials

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Received: 2 December 2007; Accepted: 15 January 2008 / Published: 22 January 2008
(This article belongs to the Special Issue Interaction of Biological Molecules)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: Protein-protein interactions are important for biochemical processes in biological systems. The 3D structure of the macromolecular complex resulting from the protein-protein association is a very useful source to understand its specific functions. This work focuses on computational study for protein-protein docking, where the individually crystallized structures of interacting proteins are treated as rigid, and the conformational space generated by the two interacting proteins is explored extensively. The energy function consists of intermolecular electrostatic potential, desolvation free energy represented by empirical contact potential, and simple repulsive energy terms. The conformational space is six dimensional, represented by translational vectors and rotational angles formed between two interacting proteins. The conformational sampling is carried out by the search algorithms such as simulated annealing (SA), conformational space annealing (CSA), and CSA combined with SA simulations (combined CSA/SA). Benchmark tests are performed on a set of 18 protein-protein complexes selected from various protein families to examine feasibility of these search methods coupled with the energy function above for protein docking study.
Keywords: Global optimization; Protein-protein docking; Conformational space annealing; Simulated annealing; Combined CSA/SA; FastContact.
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MDPI and ACS Style

Lee, K. Computational Study for Protein-Protein Docking Using Global Optimization and Empirical Potentials. Int. J. Mol. Sci. 2008, 9, 65-77.

AMA Style

Lee K. Computational Study for Protein-Protein Docking Using Global Optimization and Empirical Potentials. International Journal of Molecular Sciences. 2008; 9(1):65-77.

Chicago/Turabian Style

Lee, Kyoungrim. 2008. "Computational Study for Protein-Protein Docking Using Global Optimization and Empirical Potentials." Int. J. Mol. Sci. 9, no. 1: 65-77.

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