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{"title"=>"In silico elucidation of the molecular mechanism defining the adverse effect of selective estrogen receptor modulators", "type"=>"journal", "authors"=>[{"first_name"=>"Lei", "last_name"=>"Xie", "scopus_author_id"=>"37002340900"}, {"first_name"=>"Jian", "last_name"=>"Wang", "scopus_author_id"=>"36077615400"}, {"first_name"=>"Philip E.", "last_name"=>"Bourne", "scopus_author_id"=>"35458582500"}], "year"=>2007, "source"=>"PLoS Computational Biology", "identifiers"=>{"scopus"=>"2-s2.0-36949009488", "pui"=>"350241954", "doi"=>"10.1371/journal.pcbi.0030217", "issn"=>"1553734X", "pmid"=>"18052534", "sgr"=>"36949009488"}, "id"=>"cfa76e51-0c81-365a-8ac8-ba90d441d9b8", "abstract"=>"Early identification of adverse effect of preclinical and commercial drugs is crucial in developing highly efficient therapeutics, since unexpected adverse drug effects account for one-third of all drug failures in drug development. To correlate protein-drug interactions at the molecule level with their clinical outcomes at the organism level, we have developed an integrated approach to studying protein-ligand interactions on a structural proteome-wide scale by combining protein functional site similarity search, small molecule screening, and protein-ligand binding affinity profile analysis. By applying this methodology, we have elucidated a possible molecular mechanism for the previously observed, but molecularly uncharacterized, side effect of selective estrogen receptor modulators (SERMs). The side effect involves the inhibition of the Sacroplasmic Reticulum Ca2+ ion channel ATPase protein (SERCA) transmembrane domain. The prediction provides molecular insight into reducing the adverse effect of SERMs and is supported by clinical and in vitro observations. The strategy used in this case study is being applied to discover off-targets for other commercially available pharmaceuticals. The process can be included in a drug discovery pipeline in an effort to optimize drug leads and reduce unwanted side effects.", "link"=>"http://www.mendeley.com/research/silico-elucidation-molecular-mechanism-defining-adverse-effect-selective-estrogen-receptor-modulator-1", "reader_count"=>60, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>4, "Researcher"=>26, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>11, "Student > Postgraduate"=>3, "Student > Master"=>2, "Other"=>4, "Student > Bachelor"=>4, "Lecturer"=>1, "Professor"=>3}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>4, "Researcher"=>26, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>11, "Student > Postgraduate"=>3, "Student > Master"=>2, "Other"=>4, "Student > Bachelor"=>4, "Lecturer"=>1, "Professor"=>3}, "reader_count_by_subject_area"=>{"Unspecified"=>1, "Environmental Science"=>2, "Nursing and Health Professions"=>1, "Biochemistry, Genetics and Molecular Biology"=>6, "Mathematics"=>2, "Agricultural and Biological Sciences"=>30, "Medicine and Dentistry"=>2, "Pharmacology, Toxicology and Pharmaceutical Science"=>3, "Chemistry"=>11, "Computer Science"=>2}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>2}, "Chemistry"=>{"Chemistry"=>11}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>30}, "Computer Science"=>{"Computer Science"=>2}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>6}, "Mathematics"=>{"Mathematics"=>2}, "Unspecified"=>{"Unspecified"=>1}, "Environmental Science"=>{"Environmental Science"=>2}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>3}}, "reader_count_by_country"=>{"Argentina"=>1, "United States"=>2, "Norway"=>1, "Brazil"=>1, "United Kingdom"=>1, "Germany"=>3}, "group_count"=>0}

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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/941295"], "description"=>"<p>The surface is colored according to the electrostatic potential calculated from APBS [<a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0030217#pcbi-0030217-b060\" target=\"_blank\">60</a>]. Part of the surface that covers the binding site in 1XPC is removed for better visualization. The green stick model is the co-crystallized ligand (2S,3R)-3-(4-hydroxyphenyl)-2-(4-{[(2R)-2-pyrrolidin-1-ylpropyl]oxy}phenyl)-2,3-dihydro-1,4-benzoxathiin-6-ol (AIT). The white stick model is the co-crystallized ligand thapsigargin (TG1). The color scale is set from −30 to 30 kT/e using a linear scale to elucidate ES around the ligand binding sites.</p>", "links"=>[], "tags"=>["ligand", "binding", "predicated", "off-target", "serca"], "article_id"=>611716, "categories"=>["Biotechnology", "Biological Sciences", "Cancer", "Biophysics"], "users"=>["Lei Xie", "Jian Wang", "Philip E Bourne"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.0030217.g005", "stats"=>{"downloads"=>3, "page_views"=>20, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Electrostatic_Potential_ES_of_the_Ligand_Binding_Site_in_A_the_Original_Drug_Target_ER_945_PDB_id_1XPC_and_B_Predicated_Off_Target_SERCA_PDB_id_2AGV_/611716", "title"=>"Electrostatic Potential (ES) of the Ligand Binding Site in: (A) the Original Drug Target ERα (PDB id: 1XPC), and (B) Predicated Off-Target SERCA (PDB id: 2AGV)", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2007-11-30 00:28:36"}
• {"files"=>["https://ndownloader.figshare.com/files/941396"], "description"=>"<p>(A) TAM, (B) OHT, (C) ORM, (D) LAS, (E) RAL, and (F) BAZ. SERCA is represented as a white backbone. Side chains of Phe256/834 and Glu255 are represented with stick models. SERMs are represented as ball and stick models. Carbon atoms are colored green; oxygens red; nitrogens blue; sulphur orange. The potential salt bridge interaction between the amine and Glu255 is indicated by an orange dashed line.</p>", "links"=>[], "tags"=>["poses", "serms", "serca", "tg1"], "article_id"=>611818, "categories"=>["Biotechnology", "Biological Sciences", "Cancer", "Biophysics"], "users"=>["Lei Xie", "Jian Wang", "Philip E Bourne"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.0030217.g007", "stats"=>{"downloads"=>1, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Docking_Poses_of_Six_SERMs_at_the_SERCA_TG1_Site_/611818", "title"=>"Docking Poses of Six SERMs at the SERCA TG1 Site", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2007-11-30 00:30:18"}
• {"files"=>["https://ndownloader.figshare.com/files/941150"], "description"=>"<p>The ERα is ranked top in both cases as shown by the arrows.</p>", "links"=>[], "tags"=>["binding", "scores", "searching", "825", "structures", "serca", "bhq", "tg1"], "article_id"=>611568, "categories"=>["Biotechnology", "Biological Sciences", "Cancer", "Biophysics"], "users"=>["Lei Xie", "Jian Wang", "Philip E Bourne"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.0030217.g003", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Distribution_of_Binding_Site_Similarity_Scores_from_Searching_825_Representative_Structures_against_SERCA_for_BHQ_A_and_TG1_B_Sites_Respectively_/611568", "title"=>"Distribution of Binding Site Similarity Scores from Searching 825 Representative Structures against SERCA for BHQ (A) and TG1 (B) Sites, Respectively", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2007-11-30 00:26:08"}
• {"files"=>["https://ndownloader.figshare.com/files/941512"], "description"=>"<p>N-Moiety (A) and C-Moiety (B) Molecular Fragments Used in the 2D Graph Similarity Search for Decoy Molecules</p>", "links"=>[], "tags"=>["c-moiety", "molecular", "fragments", "2d", "graph", "decoy"], "article_id"=>611925, "categories"=>["Biotechnology", "Biological Sciences", "Cancer", "Biophysics"], "users"=>["Lei Xie", "Jian Wang", "Philip E Bourne"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.0030217.g009", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_N_Moiety_A_and_C_Moiety_B_Molecular_Fragments_Used_in_the_2D_Graph_Similarity_Search_for_Decoy_Molecules_/611925", "title"=>"N-Moiety (A) and C-Moiety (B) Molecular Fragments Used in the 2D Graph Similarity Search for Decoy Molecules", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2007-11-30 00:32:05"}
• {"files"=>["https://ndownloader.figshare.com/files/941461"], "description"=>"<div><p>(A,B) N- and C-moieties to ERα and SERCA TG1 sites, respectively.</p><p>(C,D) N- and C-moieties to ERα and SERCA BHQ site, respectively. The red line represents the linear regression of docking scores. The green line indicates the optimal score correlation between two identical binding sites. The docking score is from eHits [<a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0030217#pcbi-0030217-b031\" target=\"_blank\">31</a>]. Docking score correlations from Surfex [<a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0030217#pcbi-0030217-b032\" target=\"_blank\">32</a>] show the same trends although the absolute values are different (unpublished data).</p></div>", "links"=>[], "tags"=>["binding", "affinity", "scores", "docking", "molecular", "analogs", "n-moiety", "c-moiety", "serms", "serca"], "article_id"=>611870, "categories"=>["Biotechnology", "Biological Sciences", "Cancer", "Biophysics"], "users"=>["Lei Xie", "Jian Wang", "Philip E Bourne"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.0030217.g008", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Correlation_of_Binding_Affinity_Scores_by_Docking_Molecular_Analogs_of_N_Moiety_and_C_Moiety_of_SERMs_to_ER_945_and_SERCA_Proteins_/611870", "title"=>"Correlation of Binding Affinity Scores by Docking Molecular Analogs of N-Moiety and C-Moiety of SERMs to ERα and SERCA Proteins", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2007-11-30 00:31:10"}
• {"files"=>["https://ndownloader.figshare.com/files/941220"], "description"=>"<p>The known bound ligand is shown in a ball-and-stick representation (gold).</p>", "links"=>[], "tags"=>["ligand", "binding", "querying", "serca", "tg1"], "article_id"=>611642, "categories"=>["Biotechnology", "Biological Sciences", "Cancer", "Biophysics"], "users"=>["Lei Xie", "Jian Wang", "Philip E Bourne"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.0030217.g004", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Predicated_ER_945_Ligand_Binding_Site_from_Reverse_Search_by_Querying_the_SERCA_TG1_Site_White_Spheres_/611642", "title"=>"Predicated ERα Ligand Binding Site from Reverse Search by Querying the SERCA TG1 Site (White Spheres)", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2007-11-30 00:27:22"}
• {"files"=>["https://ndownloader.figshare.com/files/463521", "https://ndownloader.figshare.com/files/463533", "https://ndownloader.figshare.com/files/463538", "https://ndownloader.figshare.com/files/463545", "https://ndownloader.figshare.com/files/463555"], "description"=>"<div><p>Early identification of adverse effect of preclinical and commercial drugs is crucial in developing highly efficient therapeutics, since unexpected adverse drug effects account for one-third of all drug failures in drug development. To correlate protein–drug interactions at the molecule level with their clinical outcomes at the organism level, we have developed an integrated approach to studying protein–ligand interactions on a structural proteome-wide scale by combining protein functional site similarity search, small molecule screening, and protein–ligand binding affinity profile analysis. By applying this methodology, we have elucidated a possible molecular mechanism for the previously observed, but molecularly uncharacterized, side effect of selective estrogen receptor modulators (SERMs). The side effect involves the inhibition of the Sacroplasmic Reticulum Ca2+ ion channel ATPase protein (SERCA) transmembrane domain. The prediction provides molecular insight into reducing the adverse effect of SERMs and is supported by clinical and in vitro observations. The strategy used in this case study is being applied to discover off-targets for other commercially available pharmaceuticals. The process can be included in a drug discovery pipeline in an effort to optimize drug leads and reduce unwanted side effects.</p></div>", "links"=>[], "tags"=>["silico", "elucidation", "molecular", "defining", "adverse", "selective", "estrogen", "receptor", "modulators"], "article_id"=>151356, "categories"=>["Biotechnology", "Biological Sciences", "Cancer", "Biophysics"], "users"=>["Lei Xie", "Jian Wang", "Philip E Bourne"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.0030217.sg001", "https://dx.doi.org/10.1371/journal.pcbi.0030217.sg002", "https://dx.doi.org/10.1371/journal.pcbi.0030217.sg003", "https://dx.doi.org/10.1371/journal.pcbi.0030217.st001", "https://dx.doi.org/10.1371/journal.pcbi.0030217.st002"], "stats"=>{"downloads"=>19, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/In_Silico_Elucidation_of_the_Molecular_Mechanism_Defining_the_Adverse_Effect_of_Selective_Estrogen_Receptor_Modulators/151356", "title"=>"In Silico Elucidation of the Molecular Mechanism Defining the Adverse Effect of Selective Estrogen Receptor Modulators", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2007-11-30 00:22:36"}
• {"files"=>["https://ndownloader.figshare.com/files/940991"], "description"=>"<p>The predicted binding site is represented by white spheres, BHQ by purple spheres, and TG1 by cyan spheres. (A) and (B) are two different perspectives centered on BHQ and TG1, respectively.</p>", "links"=>[], "tags"=>["serca", "ligand", "binding", "inhibitors", "tg1"], "article_id"=>611418, "categories"=>["Biotechnology", "Biological Sciences", "Cancer", "Biophysics"], "users"=>["Lei Xie", "Jian Wang", "Philip E Bourne"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.0030217.g001", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_the_Predicted_SERCA_Ligand_Binding_Site_with_That_of_Known_SERCA_Inhibitors_TG1_and_BHQ_/611418", "title"=>"Comparison of the Predicted SERCA Ligand Binding Site with That of Known SERCA Inhibitors TG1 and BHQ", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2007-11-30 00:23:38"}
• {"files"=>["https://ndownloader.figshare.com/files/941353"], "description"=>"<p>N- and C-moieties are broken down by bonds marked with red bars and on the left and the right sides of 2D schema, respectively.</p>", "links"=>[], "tags"=>["selective", "estrogen", "receptor", "modulators", "commercially"], "article_id"=>611774, "categories"=>["Biotechnology", "Biological Sciences", "Cancer", "Biophysics"], "users"=>["Lei Xie", "Jian Wang", "Philip E Bourne"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.0030217.g006", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Six_Selective_Estrogen_Receptor_Modulators_Either_Commercially_Available_or_in_Clinical_Trial_/611774", "title"=>"Six Selective Estrogen Receptor Modulators Either Commercially Available or in Clinical Trial", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2007-11-30 00:29:34"}
• {"files"=>["https://ndownloader.figshare.com/files/941067"], "description"=>"<p>Comparison of the Predicted SERCA Ligand Binding Site (White Spheres) and the Two Calcium Ions (Orange Spheres)</p>", "links"=>[], "tags"=>["serca", "ligand", "binding", "calcium", "ions"], "article_id"=>611487, "categories"=>["Biotechnology", "Biological Sciences", "Cancer", "Biophysics"], "users"=>["Lei Xie", "Jian Wang", "Philip E Bourne"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.0030217.g002", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_the_Predicted_SERCA_Ligand_Binding_Site_White_Spheres_and_the_Two_Calcium_Ions_Orange_Spheres_/611487", "title"=>"Comparison of the Predicted SERCA Ligand Binding Site (White Spheres) and the Two Calcium Ions (Orange Spheres)", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2007-11-30 00:24:47"}

PMC Usage Stats | Further Information

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Relative Metric

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F1000Prime