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Docking Problem (docking + problem)
Selected AbstractsStudies of molecular docking between fibroblast growth factor and heparin using generalized simulated annealingINTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY, Issue 13 2008Samuel Silva da Rocha Pita Abstract Since the middle 70s, the main molecular docking problem consists in limitations to treat adequately the degrees of freedom of protein (or a receptor) due to the energy landscape roughness and the high computational cost. Until recently, only few algorithms considering flexible simultaneously both ligand and receptor at low computational cost were developed. As a recent proposed Statistical Mechanics, generalized simulated annealing (GSA) has been employed at diverse works concerning global optimization problems. In this work, we used this method exploring the molecular docking problem taking into account the FGF-2 and heparin complex. Since the requirements of an efficient docking algorithm are accuracy and velocity, we tested the influence of GSA parameters qA (new configuration acceptance index), qV (energy surface visiting index), and qT (temperature decreasing control) on the performance of GSADOCK program. Our simulations showed that as temperature parameter qT increases, qA parameter follows this behavior in the interval ranging from 1.1 to 2.3. We found that the GSA parameters have the best performance for the qA values ranging from 1.1 to 1.3, qV values from 1.3 to 1.5, and qT values from 1.1 to 1.7. Most of good qV values were equal or next the good qT values. Finally, the implemented algorithm is trustworthy and can be employed as a tool of molecular modeling methods. The final version of the program will be free of charge and will be accessible at our home-page or could be requested to the authors for e-mail. © 2008 Wiley Periodicals, Inc. Int J Quantum Chem, 2008 [source] Protein,protein docking dealing with the unknownJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 2 2010Irina S. Moreira Abstract Protein,protein binding is one of the critical events in biology, and knowledge of proteic complexes three-dimensional structures is of fundamental importance for the biochemical study of pharmacologic compounds. In the past two decades there was an emergence of a large variety of algorithms designed to predict the structures of protein,protein complexes,a procedure named docking. Computational methods, if accurate and reliable, could play an important role, both to infer functional properties and to guide new experiments. Despite the outstanding progress of the methodologies developed in this area, a few problems still prevent protein,protein docking to be a widespread practice in the structural study of proteins. In this review we focus our attention on the principles that govern docking, namely the algorithms used for searching and scoring, which are usually referred as the docking problem. We also focus our attention on the use of a flexible description of the proteins under study and the use of biological information as the localization of the hot spots, the important residues for protein,protein binding. The most common docking softwares are described too. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010 [source] Protein,protein docking with multiple residue conformations and residue substitutionsPROTEIN SCIENCE, Issue 6 2002David M. Lorber Abstract The protein docking problem has two major aspects: sampling conformations and orientations, and scoring them for fit. To investigate the extent to which the protein docking problem may be attributed to the sampling of ligand side-chain conformations, multiple conformations of multiple residues were calculated for the uncomplexed (unbound) structures of protein ligands. These ligand conformations were docked into both the complexed (bound) and unbound conformations of the cognate receptors, and their energies were evaluated using an atomistic potential function. The following questions were considered: (1) does the ensemble of precalculated ligand conformations contain a structure similar to the bound form of the ligand? (2) Can the large number of conformations that are calculated be efficiently docked into the receptors? (3) Can near-native complexes be distinguished from non-native complexes? Results from seven test systems suggest that the precalculated ensembles do include side-chain conformations similar to those adopted in the experimental complexes. By assuming additivity among the side chains, the ensemble can be docked in less than 12 h on a desktop computer. These multiconformer dockings produce near-native complexes and also non-native complexes. When docked against the bound conformations of the receptors, the near-native complexes of the unbound ligand were always distinguishable from the non-native complexes. When docked against the unbound conformations of the receptors, the near-native dockings could usually, but not always, be distinguished from the non-native complexes. In every case, docking the unbound ligands with flexible side chains led to better energies and a better distinction between near-native and non-native fits. An extension of this algorithm allowed for docking multiple residue substitutions (mutants) in addition to multiple conformations. The rankings of the docked mutant proteins correlated with experimental binding affinities. These results suggest that sampling multiple residue conformations and residue substitutions of the unbound ligand contributes to, but does not fully provide, a solution to the protein docking problem. Conformational sampling allows a classical atomistic scoring function to be used; such a function may contribute to better selectivity between near-native and non-native complexes. Allowing for receptor flexibility may further extend these results. [source] SODOCK: Swarm optimization for highly flexible protein,ligand dockingJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 2 2007Hung-Ming Chen Abstract Protein,ligand docking can be formulated as a parameter optimization problem associated with an accurate scoring function, which aims to identify the translation, orientation, and conformation of a docked ligand with the lowest energy. The parameter optimization problem for highly flexible ligands with many rotatable bonds is more difficult than that for less flexible ligands using genetic algorithm (GA)-based approaches, due to the large numbers of parameters and high correlations among these parameters. This investigation presents a novel optimization algorithm SODOCK based on particle swarm optimization (PSO) for solving flexible protein,ligand docking problems. To improve efficiency and robustness of PSO, an efficient local search strategy is incorporated into SODOCK. The implementation of SODOCK adopts the environment and energy function of AutoDock 3.05. Computer simulation results reveal that SODOCK is superior to the Lamarckian genetic algorithm (LGA) of AutoDock, in terms of convergence performance, robustness, and obtained energy, especially for highly flexible ligands. The results also reveal that PSO is more suitable than the conventional GA in dealing with flexible docking problems with high correlations among parameters. This investigation also compared SODOCK with four state-of-the-art docking methods, namely GOLD 1.2, DOCK 4.0, FlexX 1.8, and LGA of AutoDock 3.05. SODOCK obtained the smallest RMSD in 19 of 37 cases. The average 2.29 Å of the 37 RMSD values of SODOCK was better than those of other docking programs, which were all above 3.0 Å. © 2006 Wiley Periodicals, Inc. J Comput Chem 28: 612,623, 2007 [source] | ||||||||||