Discovery of Novel MDR-Mycobacterium tuberculosis Inhibitor by New FRIGATE Computational Screen
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{"title"=>"Discovery of novel MDR-mycobacterium tuberculosis inhibitor by new FRIGATE computational screen", "type"=>"journal", "authors"=>[{"first_name"=>"Christoph", "last_name"=>"Scheich", "scopus_author_id"=>"56619152100"}, {"first_name"=>"Zoltán", "last_name"=>"Szabadka", "scopus_author_id"=>"12240949900"}, {"first_name"=>"Beáta", "last_name"=>"Vértessy", "scopus_author_id"=>"7004513602"}, {"first_name"=>"Vera", "last_name"=>"Pütter", "scopus_author_id"=>"6506707888"}, {"first_name"=>"Vince", "last_name"=>"Grolmusz", "scopus_author_id"=>"7003519592"}, {"first_name"=>"Markus", "last_name"=>"Schade", "scopus_author_id"=>"7004854278"}], "year"=>2011, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"22164290", "doi"=>"10.1371/journal.pone.0028428", "sgr"=>"82555187494", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "scopus"=>"2-s2.0-82555187494", "issn"=>"19326203", "pui"=>"363025066"}, "id"=>"414d6a9e-8b04-3ed5-9f48-37d317b7c648", "abstract"=>"With 1.6 million casualties annually and 2 billion people being infected, tuberculosis is still one of the most pressing healthcare challenges. Here we report on the new computational docking algorithm FRIGATE which unites continuous local optimization techniques (conjugate gradient method) with an inherently discrete computational approach in forcefield computation, resulting in equal or better scoring accuracies than several benchmark docking programs. By utilizing FRIGATE for a virtual screen of the ZINC library against the Mycobacterium tuberculosis (Mtb) enzyme antigen 85C, we identified novel small molecule inhibitors of multiple drug-resistant Mtb, which bind in vitro to the catalytic site of antigen 85C.", "link"=>"http://www.mendeley.com/research/discovery-novel-mdrmycobacterium-tuberculosis-inhibitor-new-frigate-computational-screen", "reader_count"=>27, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>4, "Student > Doctoral Student"=>6, "Researcher"=>2, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>2, "Other"=>1, "Student > Master"=>1, "Student > Bachelor"=>1, "Lecturer"=>1, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>4, "Student > Doctoral Student"=>6, "Researcher"=>2, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>2, "Other"=>1, "Student > Master"=>1, "Student > Bachelor"=>1, "Lecturer"=>1, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Biochemistry, Genetics and Molecular Biology"=>2, "Agricultural and Biological Sciences"=>10, "Medicine and Dentistry"=>3, "Chemistry"=>8, "Computer Science"=>1, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>3}, "Chemistry"=>{"Chemistry"=>8}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>10}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>2}, "Unspecified"=>{"Unspecified"=>2}}, "reader_count_by_country"=>{"Brazil"=>1}, "group_count"=>1}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/707562"], "description"=>"<p>(<b>A</b>) <b>1</b> (C atoms dark green) superimposed on the co-crystal structure of OTG (grey) bound to Ag85C <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0028428#pone.0028428-Ronning1\" target=\"_blank\">[9]</a> using the protein coordinates for the overlay. H bonds between OTG and Ag85C are shown as dashed lines with distances in Å, including the catalytic oxyanion (Oγ) of S124. The semi-transparent surface of Ag85C is color coded from polar (blue) to hydrophobic (brown). (<b>B</b>) Superimposition of <b>2</b> (purple) (<b>C</b>) Superimposition of <b>3</b> (dark brown) (<b>D</b>) Superimposition of <b>1</b> to <b>3</b> onto OTG highlighting the differential pocket coverage. Ligand color-coding identical to (A)–(C).</p>", "links"=>[], "tags"=>["docking", "models", "confirmed", "hits", "catalytic"], "article_id"=>377914, "categories"=>["Microbiology", "Chemistry", "Infectious Diseases"], "users"=>["Christoph Scheich", "Zoltán Szabadka", "Beáta Vértessy", "Vera Pütter", "Vince Grolmusz", "Markus Schade"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0028428.g003", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_FRIGATE_docking_models_of_confirmed_hits_in_the_catalytic_site_of_Ag85C_/377914", "title"=>"FRIGATE docking models of confirmed hits in the catalytic site of Ag85C.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-02 02:11:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/358715", "https://ndownloader.figshare.com/files/358741", "https://ndownloader.figshare.com/files/358771", "https://ndownloader.figshare.com/files/358810", "https://ndownloader.figshare.com/files/358884", "https://ndownloader.figshare.com/files/358924", "https://ndownloader.figshare.com/files/358979"], "description"=>"<div><p>With 1.6 million casualties annually and 2 billion people being infected, tuberculosis is still one of the most pressing healthcare challenges. Here we report on the new computational docking algorithm FRIGATE which unites continuous local optimization techniques (conjugate gradient method) with an inherently discrete computational approach in forcefield computation, resulting in equal or better scoring accuracies than several benchmark docking programs. By utilizing FRIGATE for a virtual screen of the ZINC library against the <em>Mycobacterium tuberculosis</em> (<em>Mtb</em>) enzyme antigen 85C, we identified novel small molecule inhibitors of multiple drug-resistant <em>Mtb</em>, which bind in vitro to the catalytic site of antigen 85C.</p> </div>", "links"=>[], "tags"=>["inhibitor", "frigate", "computational"], "article_id"=>130918, "categories"=>["Cancer", "Chemistry", "Microbiology"], "users"=>["Christoph Scheich", "Zoltán Szabadka", "Beáta Vértessy", "Vera Pütter", "Vince Grolmusz", "Markus Schade"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0028428.s001", "https://dx.doi.org/10.1371/journal.pone.0028428.s002", "https://dx.doi.org/10.1371/journal.pone.0028428.s003", "https://dx.doi.org/10.1371/journal.pone.0028428.s004", "https://dx.doi.org/10.1371/journal.pone.0028428.s005", "https://dx.doi.org/10.1371/journal.pone.0028428.s006", "https://dx.doi.org/10.1371/journal.pone.0028428.s007"], "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Discovery_of_Novel_MDR_Mycobacterium_tuberculosis_Inhibitor_by_New_FRIGATE_Computational_Screen/130918", "title"=>"Discovery of Novel MDR-<em>Mycobacterium tuberculosis</em> Inhibitor by New FRIGATE Computational Screen", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2011-12-02 00:15:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/707390"], "description"=>"<p>(<b>A</b>) FRIGATE docks ∼68% (horizontal line) of the 30 top scoring ligand poses within 2 Å of the crystallographic pose, which matches the average performance of the benchmark programs. (<b>B</b>) FRIGATE scores ∼52% of the top scoring ligand poses within 2 Å of the crystallographic pose, which exceeds the performance of FRED1.1 (arrow) by ∼23%.</p>", "links"=>[], "tags"=>["scoring", "frigate", "compared", "benchmark", "programs"], "article_id"=>377743, "categories"=>["Microbiology", "Chemistry", "Infectious Diseases"], "users"=>["Christoph Scheich", "Zoltán Szabadka", "Beáta Vértessy", "Vera Pütter", "Vince Grolmusz", "Markus Schade"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0028428.g002", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Docking_top_and_scoring_bottom_accuracy_of_FRIGATE_compared_with_benchmark_programs_15_/377743", "title"=>"Docking (top) and scoring (bottom) accuracy of FRIGATE compared with benchmark programs [15].", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-02 02:09:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/707256"], "description"=>"<p>(<b>A</b>) The number of test cases that were successfully optimized within a certain energy threshold from the reference value. On the left figure the reference value was the current estimate for the global optimum, and on the right it was the energy of the local optimized X-ray conformation of the ligand. (<b>B</b>) For all training set ligands with 6–14 degrees of freedom, the CMS algorithm finds an energy minimum within +0.5 kcal/mol of the crystallographic complex (ΔE<sub>Xray</sub>). For ligands with 15 or more degrees of freedom, the CMS minimization performance becomes worse than ΔE<sub>Xray</sub>+0.5 kcal/mol for an increasing number of complexes.</p>", "links"=>[], "tags"=>["limitations", "optimization", "algorithm"], "article_id"=>377616, "categories"=>["Microbiology", "Chemistry", "Infectious Diseases"], "users"=>["Christoph Scheich", "Zoltán Szabadka", "Beáta Vértessy", "Vera Pütter", "Vince Grolmusz", "Markus Schade"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0028428.g001", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Performance_and_limitations_of_the_global_optimization_algorithm_CMS_/377616", "title"=>"Performance and limitations of the global optimization algorithm CMS.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-02 02:06:56"}
  • {"files"=>["https://ndownloader.figshare.com/files/707681"], "description"=>"<p>(<b>a</b>) The <sup>15</sup>N-HSQC spectra of Ag85C in the presence of 50 µM (purple), 100 µM (green) and 200 µM (red) <b>1</b> show mono-directional (arrows) CSPs for exemplary residues (numbered, eg 42) as compared with apo-Ag85C (blue). Twelve randomly selected reference residues (labeled r1–r12) remain unchanged. (<b>b</b>) Plotting the CSPs vs. the concentration of <b>1</b> allows one to fit a binding curve with an average Kd value of 177 µM. CSP numbering identical to (a).</p>", "links"=>[], "tags"=>["binding", "assay"], "article_id"=>378038, "categories"=>["Microbiology", "Chemistry", "Infectious Diseases"], "users"=>["Christoph Scheich", "Zoltán Szabadka", "Beáta Vértessy", "Vera Pütter", "Vince Grolmusz", "Markus Schade"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0028428.g004", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_NMR_binding_assay_of_1_/378038", "title"=>"NMR binding assay of 1.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-02 02:13:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/707822"], "description"=>"<p>Addition of 50 and 100 µg/mL of <b>1</b> and <b>3</b>, respectively, blocks the growth of <i>Msmeg</i> beyond the level of visible detection, whereas <i>Msmeg</i> grows in the presence of 50–200 µg/mL of <b>2</b>. The reference antibiotic ampicillin (Amp) inhibits <i>Msmeg</i> growth at 16 µg/mL as published previously <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0028428#pone.0028428-Stephan1\" target=\"_blank\">[37]</a>. Growth medium with (labeled ‘untreated’) and without bacteria inoculum (labeled ‘no bacteria’) is colored black and pale yellow, respectively.</p>", "links"=>[], "tags"=>["inhibition", "assay"], "article_id"=>378180, "categories"=>["Microbiology", "Chemistry", "Infectious Diseases"], "users"=>["Christoph Scheich", "Zoltán Szabadka", "Beáta Vértessy", "Vera Pütter", "Vince Grolmusz", "Markus Schade"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0028428.g005", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Msmeg_growth_inhibition_assay_of_1_to_3_/378180", "title"=>"<i>Msmeg</i> growth inhibition assay of 1 to 3.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-02 02:16:20"}

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Relative Metric

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