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Arthur J. Olson – One of the best experts on this subject based on the ideXlab platform.

  • The AutoDock suite at 30
    Protein Science, 2020
    Co-Authors: David S Goodsell, Arthur J. Olson, Michel F. Sanner, Stefano Forli

    Abstract:

    The AutoDock suite provides a comprehensive toolset for computational ligand docking and drug design and development. The suite builds on 30 years of methods development, including empirical free energy force fields, docking engines, methods for site prediction, and interactive tools for visualization and analysis. Specialized tools are available for challenging systems, including covalent inhibitors, peptides, compounds with macrocycles, systems where ordered hydration plays a key role, and systems with substantial receptor flexibility. All methods in the AutoDock suite are freely available for use and reuse, which has engendered the continued growth of a diverse community of primary users and third-party developers. This article is protected by copyright. All rights reserved.

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  • covalent docking using AutoDock two point attractor and flexible side chain methods
    Protein Science, 2016
    Co-Authors: Giulia Bianco, David S Goodsell, Stefano Forli, Arthur J. Olson

    Abstract:

    We describe two methods of automated covalent docking using AutoDock4: the two-point attractor method and the flexible side chain method. Both methods were applied to a training set of 20 diverse protein–ligand covalent complexes, evaluating their reliability in predicting the crystallographic pose of the ligands. The flexible side chain method performed best, recovering the pose in 75% of cases, with failures for the largest inhibitors tested. Both methods are freely available at the AutoDock website (http://AutoDock.scripps.edu).

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  • Covalent docking using AutoDock: Two‐point attractor and flexible side chain methods
    Protein Science, 2015
    Co-Authors: Giulia Bianco, David S Goodsell, Stefano Forli, Arthur J. Olson

    Abstract:

    We describe two methods of automated covalent docking using AutoDock4: the two-point attractor method and the flexible side chain method. Both methods were applied to a training set of 20 diverse protein–ligand covalent complexes, evaluating their reliability in predicting the crystallographic pose of the ligands. The flexible side chain method performed best, recovering the pose in 75% of cases, with failures for the largest inhibitors tested. Both methods are freely available at the AutoDock website (http://AutoDock.scripps.edu).

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David S Goodsell – One of the best experts on this subject based on the ideXlab platform.

  • The AutoDock suite at 30
    Protein Science, 2020
    Co-Authors: David S Goodsell, Arthur J. Olson, Michel F. Sanner, Stefano Forli

    Abstract:

    The AutoDock suite provides a comprehensive toolset for computational ligand docking and drug design and development. The suite builds on 30 years of methods development, including empirical free energy force fields, docking engines, methods for site prediction, and interactive tools for visualization and analysis. Specialized tools are available for challenging systems, including covalent inhibitors, peptides, compounds with macrocycles, systems where ordered hydration plays a key role, and systems with substantial receptor flexibility. All methods in the AutoDock suite are freely available for use and reuse, which has engendered the continued growth of a diverse community of primary users and third-party developers. This article is protected by copyright. All rights reserved.

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  • covalent docking using AutoDock two point attractor and flexible side chain methods
    Protein Science, 2016
    Co-Authors: Giulia Bianco, David S Goodsell, Stefano Forli, Arthur J. Olson

    Abstract:

    We describe two methods of automated covalent docking using AutoDock4: the two-point attractor method and the flexible side chain method. Both methods were applied to a training set of 20 diverse protein–ligand covalent complexes, evaluating their reliability in predicting the crystallographic pose of the ligands. The flexible side chain method performed best, recovering the pose in 75% of cases, with failures for the largest inhibitors tested. Both methods are freely available at the AutoDock website (http://AutoDock.scripps.edu).

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  • Covalent docking using AutoDock: Two‐point attractor and flexible side chain methods
    Protein Science, 2015
    Co-Authors: Giulia Bianco, David S Goodsell, Stefano Forli, Arthur J. Olson

    Abstract:

    We describe two methods of automated covalent docking using AutoDock4: the two-point attractor method and the flexible side chain method. Both methods were applied to a training set of 20 diverse protein–ligand covalent complexes, evaluating their reliability in predicting the crystallographic pose of the ligands. The flexible side chain method performed best, recovering the pose in 75% of cases, with failures for the largest inhibitors tested. Both methods are freely available at the AutoDock website (http://AutoDock.scripps.edu).

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Robert Günther – One of the best experts on this subject based on the ideXlab platform.

  • research article pso AutoDock a fast flexible molecular docking program based on swarm intelligence
    Chemical Biology & Drug Design, 2007
    Co-Authors: Vigneshwaran Namasivayam, Robert Günther

    Abstract:

    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 A), 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 A is significantly lower then those obtained with the other docking programs, which are all above 2.0 A. 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.

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  • pso@AutoDock: a fast flexible molecular docking program based on Swarm intelligence.
    Chemical Biology & Drug Design, 2007
    Co-Authors: Namasivayam, Robert Günther

    Abstract:

    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 A), 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 A is significantly lower then those obtained with the other docking programs, which are all above 2.0 A. 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.

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  • pso AutoDock a fast flexible molecular docking program based on swarm intelligence
    Chemical Biology & Drug Design, 2007
    Co-Authors: Robert Günther

    Abstract:

    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 A), 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 A is significantly lower then those obtained with the other docking programs, which are all above 2.0 A. 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.

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