rDock: A Fast, Versatile and Open Source Program for Docking Ligands to Proteins and Nucleic Acids
Publication Date
April 10, 2014
Journal
PLOS Computational Biology
Authors
Sergio Ruiz Carmona, Daniel Alvarez Garcia, Nicolas Foloppe, A. Beatriz Garmendia Doval, et al
Volume
10
Issue
4
Pages
e1003571
DOI
https://dx.plos.org/10.1371/journal.pcbi.1003571
Publisher URL
http://journals.plos.org/ploscompbiol/article?id=10.1371%2Fjournal.pcbi.1003571
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/24722481
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983074
Europe PMC
http://europepmc.org/abstract/MED/24722481
Web of Science
000336507500023
Scopus
84901363730
Mendeley
http://www.mendeley.com/research/rdock-fast-versatile-open-source-program-docking-ligands-proteins-nucleic-acids
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Mendeley | Further Information

{"title"=>"rDock: A Fast, Versatile and Open Source Program for Docking Ligands to Proteins and Nucleic Acids", "type"=>"journal", "authors"=>[{"first_name"=>"Sergio", "last_name"=>"Ruiz-Carmona", "scopus_author_id"=>"56178317900"}, {"first_name"=>"Daniel", "last_name"=>"Alvarez-Garcia", "scopus_author_id"=>"56177508200"}, {"first_name"=>"Nicolas", "last_name"=>"Foloppe", "scopus_author_id"=>"34975052500"}, {"first_name"=>"A. Beatriz", "last_name"=>"Garmendia-Doval", "scopus_author_id"=>"55344856300"}, {"first_name"=>"Szilveszter", "last_name"=>"Juhos", "scopus_author_id"=>"6602624427"}, {"first_name"=>"Peter", "last_name"=>"Schmidtke", "scopus_author_id"=>"36764104900"}, {"first_name"=>"Xavier", "last_name"=>"Barril", "scopus_author_id"=>"6602104920"}, {"first_name"=>"Roderick E.", "last_name"=>"Hubbard", "scopus_author_id"=>"7202298710"}, {"first_name"=>"S. David", "last_name"=>"Morley", "scopus_author_id"=>"57198275346"}], "year"=>2014, "source"=>"PLoS Computational Biology", "identifiers"=>{"pui"=>"373163006", "isbn"=>"1553-7358 (Electronic)\\r1553-734X (Linking)", "issn"=>"15537358", "doi"=>"10.1371/journal.pcbi.1003571", "scopus"=>"2-s2.0-84901363730", "pmid"=>"24722481", "sgr"=>"84901363730"}, "id"=>"46ca8c7c-e999-3610-aa6d-edff2c9f5d59", "abstract"=>"Identification of chemical compounds with specific biological activities is an important step in both chemical biology and drug discovery. When the structure of the intended target is available, one approach is to use molecular docking programs to assess the chemical complementarity of small molecules with the target; such calculations provide a qualitative measure of affinity that can be used in virtual screening (VS) to rank order a list of compounds according to their potential to be active. rDock is a molecular docking program developed at Vernalis for high-throughput VS (HTVS) applications. Evolved from RiboDock, the program can be used against proteins and nucleic acids, is designed to be computationally very efficient and allows the user to incorporate additional constraints and information as a bias to guide docking. This article provides an overview of the program structure and features and compares rDock to two reference programs, AutoDock Vina (open source) and Schrödinger's Glide (commercial). In terms of computational speed for VS, rDock is faster than Vina and comparable to Glide. For binding mode prediction, rDock and Vina are superior to Glide. The VS performance of rDock is significantly better than Vina, but inferior to Glide for most systems unless pharmacophore constraints are used; in that case rDock and Glide are of equal performance. The program is released under the Lesser General Public License and is freely available for download, together with the manuals, example files and the complete test sets, at http://rdock.sourceforge.net/", "link"=>"http://www.mendeley.com/research/rdock-fast-versatile-open-source-program-docking-ligands-proteins-nucleic-acids", "reader_count"=>181, "reader_count_by_academic_status"=>{"Unspecified"=>4, "Professor > Associate Professor"=>8, "Researcher"=>43, "Student > Doctoral Student"=>10, "Student > Ph. D. Student"=>55, "Student > Postgraduate"=>4, "Other"=>5, "Student > Master"=>20, "Student > Bachelor"=>18, "Lecturer"=>4, "Lecturer > Senior Lecturer"=>1, "Professor"=>9}, "reader_count_by_user_role"=>{"Unspecified"=>4, "Professor > Associate Professor"=>8, "Researcher"=>43, "Student > Doctoral Student"=>10, "Student > Ph. D. 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CrossRef

Scopus | Further Information

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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/1459279"], "description"=>"1<p>Average and standard deviation taking 100 random sets of 100 docking poses out of a pool of 1000 solutions.</p>", "links"=>[], "tags"=>["Biochemistry", "Biochemical simulations", "Biomacromolecule-ligand interactions", "chemical biology", "Computational biology", "Clinical medicine", "pharmacology", "Drug research and development", "drug discovery", "chemistry", "computational chemistry", "medicinal chemistry", "top-ranked", "poses", "rmsd"], "article_id"=>994860, "categories"=>["Biological Sciences"], "users"=>["Sergio Ruiz-Carmona", "Daniel Alvarez-Garcia", "Nicolas Foloppe", "A. Beatriz Garmendia-Doval", "Szilveszter Juhos", "Peter Schmidtke", "Xavier Barril", "Roderick E. Hubbard", "S. David Morley"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003571.t002", "stats"=>{"downloads"=>1, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Percentage_of_top_ranked_poses_with_an_RMSD_below_2_197_/994860", "title"=>"Percentage of top-ranked poses with an RMSD below 2 Å.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-04-10 03:27:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/1459277"], "description"=>"1<p>Default program parameters were used.</p>2<p>On HTVS mode, the average number of docking runs needed for these 4 systems is 10.</p>3<p>50 docking runs are used for default docking.</p><p>All figures were obtained on Intel Xeon X5660 CPUs at 2.80 GHz.</p>", "links"=>[], "tags"=>["Biochemistry", "Biochemical simulations", "Biomacromolecule-ligand interactions", "chemical biology", "Computational biology", "Clinical medicine", "pharmacology", "Drug research and development", "drug discovery", "chemistry", "computational chemistry", "medicinal chemistry", "computing", "times", "seconds", "dud"], "article_id"=>994857, "categories"=>["Biological Sciences"], "users"=>["Sergio Ruiz-Carmona", "Daniel Alvarez-Garcia", "Nicolas Foloppe", "A. Beatriz Garmendia-Doval", "Szilveszter Juhos", "Peter Schmidtke", "Xavier Barril", "Roderick E. Hubbard", "S. David Morley"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003571.t004", "stats"=>{"downloads"=>4, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Average_computing_times_in_seconds_per_ligand_on_4_DUD_systems_/994857", "title"=>"Average computing times (in seconds per ligand) on 4 DUD systems.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-04-10 03:27:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/1459275"], "description"=>"<p>The boxplot indicates the median value (out of 1000 possible solutions) and the first and last quartile, while the whiskers span the 10% to 90% range. The whole set (black) has been sub-divided into ligands with 5 or fewer rotatable bonds (green) and the rest (red).</p>", "links"=>[], "tags"=>["Biochemistry", "Biochemical simulations", "Biomacromolecule-ligand interactions", "chemical biology", "Computational biology", "Clinical medicine", "pharmacology", "Drug research and development", "drug discovery", "chemistry", "computational chemistry", "medicinal chemistry", "docking", "runs", "protein-ligand", "complexes", "ccdc-astex"], "article_id"=>994855, "categories"=>["Biological Sciences"], "users"=>["Sergio Ruiz-Carmona", "Daniel Alvarez-Garcia", "Nicolas Foloppe", "A. Beatriz Garmendia-Doval", "Szilveszter Juhos", "Peter Schmidtke", "Xavier Barril", "Roderick E. Hubbard", "S. David Morley"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003571.g001", "stats"=>{"downloads"=>7, "page_views"=>24, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Relative_score_vs_the_number_of_docking_runs_for_all_the_protein_ligand_complexes_in_the_CCDC_Astex_set_/994855", "title"=>"Relative score vs. the number of docking runs for all the protein-ligand complexes in the CCDC-Astex set.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-04-10 03:27:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/1459276"], "description"=>"<p>Note that Vina does not support pharmacophoric restraints. The numbers in parentheses indicate performance relative to the best non-guided result (Glide).</p>", "links"=>[], "tags"=>["Biochemistry", "Biochemical simulations", "Biomacromolecule-ligand interactions", "chemical biology", "Computational biology", "Clinical medicine", "pharmacology", "Drug research and development", "drug discovery", "chemistry", "computational chemistry", "medicinal chemistry", "metrics", "hsp90", "unbiased", "default", "glide", "optimized", "cavity", "empirical", "pharmacophoric", "restraints"], "article_id"=>994856, "categories"=>["Biological Sciences"], "users"=>["Sergio Ruiz-Carmona", "Daniel Alvarez-Garcia", "Nicolas Foloppe", "A. Beatriz Garmendia-Doval", "Szilveszter Juhos", "Peter Schmidtke", "Xavier Barril", "Roderick E. Hubbard", "S. David Morley"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003571.t005", "stats"=>{"downloads"=>2, "page_views"=>44, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_VS_performance_metrics_for_Hsp90_using_an_unbiased_protocol_with_default_parameters_rDock_Glide_amp_Vina_or_an_optimized_cavity_definition_and_empirical_pharmacophoric_restraints_rDock_guided_amp_Glide_guided_/994856", "title"=>"VS performance metrics for Hsp90 using an unbiased protocol with default parameters (rDock, Glide & Vina) or an optimized cavity definition and empirical pharmacophoric restraints (rDock-guided & Glide-guided).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-04-10 03:27:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/1459296", "https://ndownloader.figshare.com/files/1459297", "https://ndownloader.figshare.com/files/1459298", "https://ndownloader.figshare.com/files/1459299", "https://ndownloader.figshare.com/files/1459300", "https://ndownloader.figshare.com/files/1459301", "https://ndownloader.figshare.com/files/1459302", "https://ndownloader.figshare.com/files/1459303", "https://ndownloader.figshare.com/files/1459304", "https://ndownloader.figshare.com/files/1459305", "https://ndownloader.figshare.com/files/1459306", "https://ndownloader.figshare.com/files/1459307", "https://ndownloader.figshare.com/files/1459308", "https://ndownloader.figshare.com/files/1459309", "https://ndownloader.figshare.com/files/1459310"], "description"=>"<div><p>Identification of chemical compounds with specific biological activities is an important step in both chemical biology and drug discovery. When the structure of the intended target is available, one approach is to use molecular docking programs to assess the chemical complementarity of small molecules with the target; such calculations provide a qualitative measure of affinity that can be used in virtual screening (VS) to rank order a list of compounds according to their potential to be active. rDock is a molecular docking program developed at Vernalis for high-throughput VS (HTVS) applications. Evolved from RiboDock, the program can be used against proteins and nucleic acids, is designed to be computationally very efficient and allows the user to incorporate additional constraints and information as a bias to guide docking. This article provides an overview of the program structure and features and compares rDock to two reference programs, AutoDock Vina (open source) and Schrödinger's Glide (commercial). In terms of computational speed for VS, rDock is faster than Vina and comparable to Glide. For binding mode prediction, rDock and Vina are superior to Glide. The VS performance of rDock is significantly better than Vina, but inferior to Glide for most systems unless pharmacophore constraints are used; in that case rDock and Glide are of equal performance. The program is released under the Lesser General Public License and is freely available for download, together with the manuals, example files and the complete test sets, at <a href=\"http://rdock.sourceforge.net/\" target=\"_blank\">http://rdock.sourceforge.net/</a></p></div>", "links"=>[], "tags"=>["Biochemistry", "Biochemical simulations", "Biomacromolecule-ligand interactions", "chemical biology", "Computational biology", "Clinical medicine", "pharmacology", "Drug research and development", "drug discovery", "chemistry", "computational chemistry", "medicinal chemistry", "versatile", "docking", "ligands", "proteins", "nucleic"], "article_id"=>994873, "categories"=>["Biological Sciences"], "users"=>["Sergio Ruiz-Carmona", "Daniel Alvarez-Garcia", "Nicolas Foloppe", "A. Beatriz Garmendia-Doval", "Szilveszter Juhos", "Peter Schmidtke", "Xavier Barril", "Roderick E. Hubbard", "S. David Morley"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1003571.s001", "https://dx.doi.org/10.1371/journal.pcbi.1003571.s002", "https://dx.doi.org/10.1371/journal.pcbi.1003571.s003", "https://dx.doi.org/10.1371/journal.pcbi.1003571.s004", "https://dx.doi.org/10.1371/journal.pcbi.1003571.s005", "https://dx.doi.org/10.1371/journal.pcbi.1003571.s006", "https://dx.doi.org/10.1371/journal.pcbi.1003571.s007", "https://dx.doi.org/10.1371/journal.pcbi.1003571.s008", "https://dx.doi.org/10.1371/journal.pcbi.1003571.s009", "https://dx.doi.org/10.1371/journal.pcbi.1003571.s010", "https://dx.doi.org/10.1371/journal.pcbi.1003571.s011", "https://dx.doi.org/10.1371/journal.pcbi.1003571.s012", "https://dx.doi.org/10.1371/journal.pcbi.1003571.s013", "https://dx.doi.org/10.1371/journal.pcbi.1003571.s014", "https://dx.doi.org/10.1371/journal.pcbi.1003571.s015"], "stats"=>{"downloads"=>41, "page_views"=>30, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_rDock_A_Fast_Versatile_and_Open_Source_Program_for_Docking_Ligands_to_Proteins_and_Nucleic_Acids_/994873", "title"=>"rDock: A Fast, Versatile and Open Source Program for Docking Ligands to Proteins and Nucleic Acids", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-04-10 03:27:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/1459278"], "description"=>"<p>The values in parentheses indicate the percentage of systems for which the program provides the optimal performance on a given metric.</p>1<p>Area Under the ROC Curve.</p>2<p>Area Under the semilogarithmic ROC Curve.</p>3<p>Maximal Enrichment Factor.</p>4<p>Enrichment Factor when the top x% of the virtual collection is selected.</p>", "links"=>[], "tags"=>["Biochemistry", "Biochemical simulations", "Biomacromolecule-ligand interactions", "chemical biology", "Computational biology", "Clinical medicine", "pharmacology", "Drug research and development", "drug discovery", "chemistry", "computational chemistry", "medicinal chemistry", "metrics", "39"], "article_id"=>994858, "categories"=>["Biological Sciences"], "users"=>["Sergio Ruiz-Carmona", "Daniel Alvarez-Garcia", "Nicolas Foloppe", "A. Beatriz Garmendia-Doval", "Szilveszter Juhos", "Peter Schmidtke", "Xavier Barril", "Roderick E. Hubbard", "S. David Morley"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003571.t003", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Average_values_of_different_VS_performance_metrics_over_the_39_DUD_DUD_E_systems_/994858", "title"=>"Average values of different VS performance metrics over the 39 DUD/DUD-E systems.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-04-10 03:27:58"}

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  • {"unique-ip"=>"31", "full-text"=>"39", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2020", "month"=>"7"}
  • {"unique-ip"=>"31", "full-text"=>"33", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"14", "cited-by"=>"0", "year"=>"2020", "month"=>"8"}

Relative Metric

{"start_date"=>"2014-01-01T00:00:00Z", "end_date"=>"2014-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences/Biochemistry", "average_usage"=>[282]}, {"subject_area"=>"/Computer and information sciences", "average_usage"=>[327, 511]}, {"subject_area"=>"/Computer and information sciences/Computer software", "average_usage"=>[330, 509]}, {"subject_area"=>"/Physical sciences/Mathematics", "average_usage"=>[286]}]}
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