Comparative evaluation of eight docking tools for docking and virtual screening accuracy

Kellenberger, Esther; Rodrigo, Jordi; Müller, Pascal; Rognan, Didier

doi:10.1002/prot.20149

Cited by 543 publications

(568 citation statements)

References 52 publications

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“…Identifying inhibitors by virtual screening involves multiple steps, and its success depends on several factors: the efficiency of ligand and receptor conformational sampling (4)(5)(6)(7)(8)(9)(10)(11), the quality of the scoring function (12,13), the choice of docking pocket, and finally, the availability of a relevant assay to test the virtual screening candidates.…”

mentioning

confidence: 99%

Use of allostery to identify inhibitors of calmodulin-induced activation of Bacillus anthracis edema factor

Laine

Gonçalves

Karst

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

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Allostery plays a key role in the regulation of the activity and function of many biomolecules. And although many ligands act through allostery, no systematic use is made of it in drug design strategies. Here we describe a procedure for identifying the regions of a protein that can be used to control its activity through allostery. This procedure is based on the construction of a plausible conformational path, which describes protein transition between known active and inactive conformations. The path is calculated by using a framework approach that steers and markedly improves the conjugate peak refinement method. The evolution of conformations along this path was used to identify a putative allosteric site that could regulate activation of Bacillus anthracis adenylyl cyclase toxin (EF) by calmodulin. Conformations of the allosteric site at different steps along the path from the inactive (free) to the active (bound to calmodulin) forms of EF were used to perform virtual screenings and propose candidate EF inhibitors. Several candidates then proved to inhibit calmodulin-induced activation in an in vitro assay. The most potent compound fully inhibited EF at a concentration of 10 μM. The compounds also inhibited the related adenylyl cyclase toxin from Bordetella pertussis (CyaA). The specific homology between the putative allosteric sites in both toxins supports that these pockets are the actual binding sites of the selected inhibitors.anthrax | transition path calculation | molecular dynamics | drug discovery | inhibition of protein-protein association

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mentioning

confidence: 99%

Use of allostery to identify inhibitors of calmodulin-induced activation of Bacillus anthracis edema factor

Laine

Gonçalves

Karst

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

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“…A recent case study by Muthas et al indicated that post-filtering with pharmacophores was shown to increase enrichment rates in their investigated targets compared with docking alone [6] . Several studies have been performed to assess various DBVS methods and compare which docking programs are the most successful in identifying active hits [7][8][9][10] . The conclusion is that no docking program may outperform other docking programs for all the tested targets, and the performance of each tested docking program is highly dependent on the nature of the target binding site [5] .…”

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confidence: 99%

Pharmacophore-based virtual screening versus docking-based virtual screening: a benchmark comparison against eight targets

Chen

Zhang

et al. 2009

Acta Pharmacol Sin

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Aim: This study was conducted to compare the efficiencies of two virtual screening approaches, pharmacophore-based virtual screening (PBVS) and docking-based virtual screening (DBVS) methods. Methods: All virtual screens were performed on two data sets of small molecules with both actives and decoys against eight structurally diverse protein targets, namely angiotensin converting enzyme (ACE), acetylcholinesterase (AChE), androgen receptor (AR), D-alanyl-D-alanine carboxypeptidase (DacA), dihydrofolate reductase (DHFR), estrogen receptors α (ERα), HIV-1 protease (HIV-pr), and thymidine kinase (TK). Each pharmacophore model was constructed based on several X-ray structures of protein-ligand complexes. Virtual screens were performed using four screening standards, the program Catalyst for PBVS and three docking programs (DOCK, GOLD and Glide) for DBVS. Results: Of the sixteen sets of virtual screens (one target versus two testing databases), the enrichment factors of fourteen cases using the PBVS method were higher than those using DBVS methods. The average hit rates over the eight targets at 2% and 5% of the highest ranks of the entire databases for PBVS are much higher than those for DBVS. Conclusion: The PBVS method outperformed DBVS methods in retrieving actives from the databases in our tested targets, and is a powerful method in drug discovery. discovery, especially in the cases when no three-dimensional (3D) structural information on the protein target of interest is available. Even when the 3D structures of targets are known, PBVS is also used as a complementary approach to DBVS for pre-processing databases (libraries) of small molecules to remove compounds not possessing features known to be essential for binding or for post-filtering compounds selected by docking approaches [5] . A recent case study by Muthas et al indicated that post-filtering with pharmacophores was shown to increase enrichment rates in their investigated targets compared with docking alone [6] . Several studies have been performed to assess various DBVS methods and compare which docking programs are the most successful in identifying active hits [7][8][9][10] . The conclusion is that no docking program may outperform other docking programs for all the tested targets, and the performance of each tested docking program is highly dependent on the nature of the target binding site [5] .Nevertheless, few case studies for a direct comparison on the performances between PBVS and DBVS have been reported [11] . To gain a general view for the discrimination between these two types of approach in prioritizing actives from a database with decoys, we performed a benchmark comparison between the performances of PBVS and DBVS. Eight structurally diverse protein targets were selected in this study. The pharmacophore models were generated from the ligand co-crystallized complex structures of these targets using the LigandScout program [12] , and each PBVS was performed using the program Catalyst [13,14] . To avoid the target dependency of docking pro...

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“…Molecular docking is a powerful computational tool that can predict the interaction energy between two molecules (receptor and ligand) and determine which orientation of a ligand would form the lowest energy complex within the receptor's binding pocket [17][18][19][20][21] . In the Surflex docking methodology, Hammerhead's empirical scoring function is paired with a molecular similarity method to generate putative poses of ligand fragments.…”

Section: Introductionmentioning

confidence: 99%

In-silico identification of the binding mode of synthesized adamantyl derivatives inside cholinesterase enzymes

et al. 2015

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Aim: To investigate the binding mode of synthesized adamantly derivatives inside of cholinesterase enzymes using molecular docking simulations. Methods: A series of hybrid compounds containing adamantane and hydrazide moieties was designed and synthesized. Their inhibitory activities against acetylcholinesterase (AChE) and (butyrylcholinesterase) BChE were assessed in vitro. The binding mode of the compounds inside cholinesterase enzymes was investigated using Surflex-Dock package of Sybyl7.3 software. Results: A total of 26 adamantyl derivatives were synthesized. Among them, adamantane-1-carboxylic acid hydrazide had an almost equal inhibitory activity towards both enzymes, whereas 10 other compounds exhibited moderate inhibitory activity against BChE. The molecular docking studies demonstrated that hydrophobic interactions between the compounds and their surrounding residues in the active site played predominant roles, while hydrophilic interactions were also found. When the compounds were docked inside each enzyme, they exhibited stronger interactions with BChE over AChE, possibly due to the larger active site of BChE. The binding affinities of the compounds for BChE and AChE estimated were in agreement with the experimental data. Conclusion:The new adamantly derivatives selectively inhibit BChE with respect to AChE, thus making them good candidates for testing the hypothesis that BChE inhibitors would be more efficient and better tolerated than AChE inhibitors in the treatment of Alzheimer's disease.

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Comparative evaluation of eight docking tools for docking and virtual screening accuracy

Cited by 543 publications

References 52 publications

Use of allostery to identify inhibitors of calmodulin-induced activation of Bacillus anthracis edema factor

Use of allostery to identify inhibitors of calmodulin-induced activation of Bacillus anthracis edema factor

Pharmacophore-based virtual screening versus docking-based virtual screening: a benchmark comparison against eight targets

In-silico identification of the binding mode of synthesized adamantyl derivatives inside cholinesterase enzymes

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