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Docking Methods (docking + methods)

Distribution by Scientific Domains

Chemistry	60%

Selected Abstracts

Soft protein,protein docking in internal coordinates

PROTEIN SCIENCE, Issue 2 2002
Juan Fernández-Recio
PDB, Protein Data Bank; ICM, Internal Coordinate Mechanics; RMSD, root-mean-square deviation Abstract The association of two biological macromolecules is a fundamental biological phenomenon and an unsolved theoretical problem. Docking methods for ab initio prediction of association of two independently determined protein structures usually fail when they are applied to a large set of complexes, mostly because of inaccuracies in the scoring function and/or difficulties on simulating the rearrangement of the interface residues on binding. In this work we present an efficient pseudo-Brownian rigid-body docking procedure followed by Biased Probability Monte Carlo Minimization of the ligand interacting side-chains. The use of a soft interaction energy function precalculated on a grid, instead of the explicit energy, drastically increased the speed of the procedure. The method was tested on a benchmark of 24 protein,protein complexes in which the three-dimensional structures of their subunits (bound and free) were available. The rank of the near-native conformation in a list of candidate docking solutions was <20 in 85% of complexes with no major backbone motion on binding. Among them, as many as 7 out of 11 (64%) protease-inhibitor complexes can be successfully predicted as the highest rank conformations. The presented method can be further refined to include the binding site predictions and applied to the structures generated by the structural proteomics projects. All scripts are available on the Web. [source]

Study of a highly accurate and fast protein,ligand docking method based on molecular dynamics

CONCURRENCY AND COMPUTATION: PRACTICE & EXPERIENCE, Issue 14 2005
M. Taufer
Abstract Few methods use molecular dynamics simulations in concert with atomically detailed force fields to perform protein,ligand docking calculations because they are considered too time demanding, despite their accuracy. In this paper we present a docking algorithm based on molecular dynamics which has a highly flexible computational granularity. We compare the accuracy and the time required with well-known, commonly used docking methods such as AutoDock, DOCK, FlexX, ICM, and GOLD. We show that our algorithm is accurate, fast and, because of its flexibility, applicable even to loosely coupled distributed systems such as desktop Grids for docking. Copyright © 2005 John Wiley & Sons, Ltd. [source]

A semiempirical free energy force field with charge-based desolvation

JOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 6 2007
Ruth Huey
Abstract The authors describe the development and testing of a semiempirical free energy force field for use in AutoDock4 and similar grid-based docking methods. The force field is based on a comprehensive thermodynamic model that allows incorporation of intramolecular energies into the predicted free energy of binding. It also incorporates a charge-based method for evaluation of desolvation designed to use a typical set of atom types. The method has been calibrated on a set of 188 diverse protein,ligand complexes of known structure and binding energy, and tested on a set of 100 complexes of ligands with retroviral proteases. The force field shows improvement in redocking simulations over the previous AutoDock3 force field. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2007 [source]

SODOCK: Swarm optimization for highly flexible protein,ligand docking

JOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 2 2007
Hung-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]

Research Article: pso@autodock: A Fast Flexible Molecular Docking Program Based on Swarm Intelligence

CHEMICAL BIOLOGY & DRUG DESIGN, Issue 6 2007
Vigneshwaran Namasivayam
On the quest of novel therapeutics, molecular docking methods have proven to be valuable tools for screening large libraries of compounds determining the interactions of potential drugs with the target proteins. A widely used docking approach is the simulation of the docking process guided by a binding energy function. On the basis of the molecular docking program autodock, we present pso@autodock as a tool for fast flexible molecular docking. Our novel Particle Swarm Optimization (PSO) algorithms varCPSO and varCPSO-ls are suited for rapid docking of highly flexible ligands. Thus, a ligand with 23 rotatable bonds was successfully docked within as few as 100 000 computing steps (rmsd = 0.87 Å), which corresponds to only 10% of the computing time demanded by autodock. In comparison to other docking techniques as gold 3.0, dock 6.0, flexx 2.2.0, autodock 3.05, and sodock, pso@autodock provides the smallest rmsd values for 12 in 37 protein,ligand complexes. The average rmsd value of 1.4 Å is significantly lower then those obtained with the other docking programs, which are all above 2.0 Å. Thus, pso@autodock is suggested as a highly efficient docking program in terms of speed and quality for flexible peptide,protein docking and virtual screening studies. [source]