Evaluations of Molecular Docking Programs for Virtual Screening

Onodera, Kenji; Satou, Kazuhito; Harada, Hiroshi

doi:10.1021/ci7000378

Cited by 152 publications

(119 citation statements)

References 20 publications

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“…Compared with the success rate using programs DOCK, AutoDock and GOLD, 15) shown in the table of Fig. 4b, the success rates of our ChooseLD program are almost equivalent to those of the docking program, GOLD.…”

Section: Resultsmentioning

confidence: 71%

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Bioinformatics Based Ligand-Docking and in-Silico Screening

et al. 2008

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We report a novel method, ChooseLD (CHOOse biological information Semi-Empirically on the Ligand Docking), which uses simulated annealing (SA) based on bioinformatics for protein-ligand flexible docking. The fingerprint alignment score (FPAScore) value is used to determine the docking conformation of the ligand. This method includes the matching of chemical descriptors such as fingerprints (FPs) and the root mean square deviation (rmsd) calculation of the coordinates of atoms of the chemical descriptors. Here, the FPAScore optimization for the translation and rotation of a rigid body is performed using the Metropolis Monte Carlo method. Our ChooseLD method will find wide application in the field of biochemistry and medicine to improve the search for new drugs targeting various proteins implicated in diseases.Key words flexible docking; in-silico screening; fingerprint; Tanimoto coefficient; simulated annealing; CHOOse biological information Semi-Empirically on the Ligand Docking Many protein targets implicated in diseases have been discovered through biochemical experiments.1,2) As a result, the competition between pharmaceutical companies and other organizations to discover drug-like compounds, which inhibit or activate those protein targets, is fierce.3,4) Experimental screening for drug-like compounds has usually been performed using an industrial robot to determine the interaction of the compound with a drug target protein. Since the cost of such screening is extremely high, in-silico screening of compounds for potential activity against the target protein is becoming popular. Many pharmaceutical companies are using in-silico screening programs, such as DOCK 5) AutoDock 6) and GOLD 7) created by Ewing et al., Goodsel et al. and Jones et al., respectively. DOCK 4.0 is a program used for automated molecular docking of flexible molecules, where the intermolecular interaction is described with the nonbonded terms of the AMBER 8) molecular mechanic potential of Lennard Jones, 12-6 dispersion term and 12-10 hydrogen bond term. AutoDock also uses the Lennard Jones 12-6 dispersion and 12-10 hydrogen bond terms. The screening program GOLD is based on a different 8-4 dipersion 7) force field. All three programs, DOCK, AutoDock and GOLD, use classical mechanical potentials. Here, we report a novel method, ChooseLD (CHOOse biological information SemiEmpirically on the Ligand Docking), which uses simulated annealing based on bioinformatics for protein-ligand flexible docking. Our docking method is mainly based on information such as fingerprint (FP) of a chemical descriptor, with some use of available information on the predicted protein structure and X-ray or NMR structures of protein-ligand complexes. Figure 1 shows the schematic diagram of our protein-ligand docking protocol. In the upper left corner of the diagram, we placed a target protein of interest and aim to select one or more ligands with low molecular weight. The query amino acid sequence of the target protein is aligned in a filter with a CE Z-Score of 3.7 ...

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Section: Resultsmentioning

confidence: 71%

“…The success rate of ChooseLD is compared with DOCK, AutoDock and GOLD. Corina 17) and MINI 15) show the method to determine initial ligand conformation. ChooseLD uses the furthest conformation from the experimental conformation.…”

Section: Methodsmentioning

confidence: 99%

Bioinformatics Based Ligand-Docking and in-Silico Screening

et al. 2008

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“…It has been found that Dock shows an unexpectedly better screening performance in the enrichment rates, although each of these programs has a merit over others. 25 Therefore, Dock (https://dock.compbio.ucsf.edu/retrieve_ dock_distribution.html) is used in this study. Chimera tools are used to prepare the ligand (Wangzaozin A) and receptor structures for docking.…”

Section: Dockmentioning

confidence: 99%

Study on Wangzaozin-A-Inducing Cancer Apoptosis and Its Theoretical Protein Targets

Chen

Wang

2016

Technol Cancer Res Treat

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Wangzaozin A is the most representative cytotoxic C-20-nonoxide compound of Isodon plants of Labiatae. The protein targets of the 2 isomers (X and X 0 ) of Wangzaozin A are, respectively, extracted from target fishing dock Web site. Each isomer has 23 targets with good energy scores. The binding modes of each isomer and its targets are, respectively, analyzed by Dock. The energy score of the binding mode between the isomer X and the inositol-1(or 4)-monophosphatase is the smallest. The apoptosis, antiproliferative, and lethal effects of human gastric cancer cells induced by Wangzaozin A are assessed by trypan blue exclusion, hoechst33258 stain in SGC-7901, and flow cytometric measurement. The mechanism of Wangzaozin-A-inducing cancer apoptosis is analyzed. Wangzaozin A inhibits the growth of human gastric cancer SGC-7901 cell lines at the lower concentration (<4.0 mmol/L) and results in the lethal effect at the relative higher concentration (>8.0 mmol/L).

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“…[1][2][3][4][5][6][7][8] A variety of commercially or publicly available programs exist to enrich molecule databases, i.e., to select a fraction of the original database that is predicted to be enriched in potential ligands. 3,9 Docking programs rely on fast search algorithms to identify the best position of a potential ligand in the active site of a given target and to estimate the corresponding binding affinity using empirical scoring functions. 10 Modern high-performance computing (HPC) architectures, 11 which now extend to over 100,000 cores, open the door to massive VHTD of extremely large chemical databases by simultaneous use of a large number of processors, thus potentially increasing the probability of identifying potential new ligands against a variety of protein targets.…”

Section: Introductionmentioning

confidence: 99%

Task‐parallel message passing interface implementation of Autodock4 for docking of very large databases of compounds using high‐performance super‐computers

et al. 2010

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A message passing interface (MPI)-based implementation (Autodock4.lga.MPI) of the grid-based docking program Autodock4 has been developed to allow simultaneous and independent docking of multiple compounds on up to thousands of central processing units (CPUs) using the Lamarkian genetic algorithm. The MPI version reads a single binary file containing precalculated grids that represent the protein-ligand interactions, i.e., van der Waals, electrostatic, and desolvation potentials, and needs only two input parameter files for the entire docking run. In comparison, the serial version of Autodock4 reads ASCII grid files and requires one parameter file per compound. The modifications performed result in significantly reduced input/output activity compared with the serial version. Autodock4.lga.MPI scales up to 8192 CPUs with a maximal overhead of 16.3%, of which two thirds is due to input/ output operations and one third originates from MPI operations. The optimal docking strategy, which minimizes docking CPU time without lowering the quality of the database enrichments, comprises the docking of ligands preordered from the most to the least flexible and the assignment of the number of energy evaluations as a function of the number of rotatable bounds. In 24 h, on 8192 high-performance computing CPUs, the present MPI version would allow docking to a rigid protein of about 300K small flexible compounds or 11 million rigid compounds.

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Evaluations of Molecular Docking Programs for Virtual Screening

Cited by 152 publications

References 20 publications

Bioinformatics Based Ligand-Docking and in-Silico Screening

Bioinformatics Based Ligand-Docking and in-Silico Screening

Study on Wangzaozin-A-Inducing Cancer Apoptosis and Its Theoretical Protein Targets

Task‐parallel message passing interface implementation of Autodock4 for docking of very large databases of compounds using high‐performance super‐computers

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