Exploration of structural and physicochemical requirements and search of virtual hits for aminopeptidase N inhibitors
Identifieur interne : 000305 ( Pmc/Curation ); précédent : 000304; suivant : 000306Exploration of structural and physicochemical requirements and search of virtual hits for aminopeptidase N inhibitors
Auteurs : Amit K. Halder [Inde] ; Achintya Saha [Inde] ; Tarun Jha [Inde]Source :
- Molecular Diversity [ 1381-1991 ] ; 2013.
Abstract
Aminopeptidase N (APN) inhibitors have been reported to be effective in treating of life threatening diseases including cancer. Validated ligand- and structure-based pharmacophore mapping approaches were combined with Bayesian modeling and recursive partitioning to identify structural and physicochemical requirements for highly active APN inhibitors. Based on the assumption that ligand- and structure-based pharmacophore models are complementary, the efficacy of ‘multiple pharmacophore screening’ for filtering true positive virtual hits was investigated. These multiple pharmacophore screening methods were utilized to search novel virtual hits for APN inhibition. The number of hits was refined and reduced by recursive partitioning, drug-likeliness, pharmacokinetic property prediction, and comparative molecular-docking studies. Four compounds were proposed as the potential virtual hits for APN enzyme inhibition.
The online version of this article (doi:10.1007/s11030-013-9422-5) contains supplementary material, which is available to authorized users.
Url:
DOI: 10.1007/s11030-013-9422-5
PubMed: 23341006
PubMed Central: 7089330
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Box 17020, Kolkata, 700032 India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>P.O. Box 17020, Kolkata</wicri:regionArea></affiliation></author></analytic><series><title level="j">Molecular Diversity</title><idno type="ISSN">1381-1991</idno><idno type="eISSN">1573-501X</idno><imprint><date when="2013">2013</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Aminopeptidase N (APN) inhibitors have been reported to be effective in treating of life threatening diseases including cancer. Validated ligand- and structure-based pharmacophore mapping approaches were combined with Bayesian modeling and recursive partitioning to identify structural and physicochemical requirements for highly active APN inhibitors. Based on the assumption that ligand- and structure-based pharmacophore models are complementary, the efficacy of ‘multiple pharmacophore screening’ for filtering true positive virtual hits was investigated. These multiple pharmacophore screening methods were utilized to search novel virtual hits for APN inhibition. The number of hits was refined and reduced by recursive partitioning, drug-likeliness, pharmacokinetic property prediction, and comparative molecular-docking studies. Four compounds were proposed as the potential virtual hits for APN enzyme inhibition.</p><sec><title>Electronic supplementary material</title><p>The online version of this article (doi:10.1007/s11030-013-9422-5) contains supplementary material, which is available to authorized users.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Zhang, X" uniqKey="Zhang X">X Zhang</name></author><author><name sortKey="Fang, H" uniqKey="Fang H">H Fang</name></author><author><name sortKey="Zhang, J" uniqKey="Zhang J">J Zhang</name></author><author><name sortKey="Yuan, Y" uniqKey="Yuan Y">Y Yuan</name></author><author><name sortKey="Xu, W" uniqKey="Xu W">W Xu</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Ito, K" uniqKey="Ito K">K Ito</name></author><author><name sortKey="Nakashima, Y" uniqKey="Nakashima Y">Y Nakashima</name></author><author><name sortKey="Onohara, Y" uniqKey="Onohara Y">Y 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Mol Divers</journal-id><journal-id journal-id-type="iso-abbrev">Mol. Divers</journal-id><journal-title-group><journal-title>Molecular Diversity</journal-title></journal-title-group><issn pub-type="ppub">1381-1991</issn><issn pub-type="epub">1573-501X</issn><publisher><publisher-name>Springer Netherlands</publisher-name><publisher-loc>Dordrecht</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">23341006</article-id><article-id pub-id-type="pmc">7089330</article-id><article-id pub-id-type="publisher-id">9422</article-id><article-id pub-id-type="doi">10.1007/s11030-013-9422-5</article-id><article-categories><subj-group subj-group-type="heading"><subject>Full-Length Paper</subject></subj-group></article-categories><title-group><article-title>Exploration of structural and physicochemical requirements and search of virtual hits for aminopeptidase N inhibitors</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Halder</surname><given-names>Amit K.</given-names></name><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author"><name><surname>Saha</surname><given-names>Achintya</given-names></name><xref ref-type="aff" rid="Aff2">2</xref></contrib><contrib contrib-type="author" corresp="yes"><name><surname>Jha</surname><given-names>Tarun</given-names></name><address><phone>+919433187443</phone><fax>+913324146927</fax><email>tjupharm@yahoo.com</email></address><xref ref-type="aff" rid="Aff1">1</xref></contrib><aff id="Aff1"><label>1</label><institution-wrap><institution-id institution-id-type="GRID">grid.216499.1</institution-id><institution-id institution-id-type="ISNI">0000000107223459</institution-id><institution>Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology,</institution><institution>Jadavpur University,</institution></institution-wrap>P.O. Box 17020, Kolkata, 700032 India</aff><aff id="Aff2"><label>2</label><institution-wrap><institution-id institution-id-type="GRID">grid.59056.3f</institution-id><institution-id institution-id-type="ISNI">0000000106649773</institution-id><institution>Department of Chemical Technology,</institution><institution>University of Calcutta,</institution></institution-wrap>92, APC Ray Road, Kolkata, 700009 India</aff></contrib-group><pub-date pub-type="epub"><day>23</day><month>1</month><year>2013</year></pub-date><pub-date pub-type="ppub"><year>2013</year></pub-date><volume>17</volume><issue>1</issue><fpage>123</fpage><lpage>137</lpage><history><date date-type="received"><day>10</day><month>8</month><year>2012</year></date><date date-type="accepted"><day>7</day><month>1</month><year>2013</year></date></history><permissions><copyright-statement>© Springer Science+Business Media Dordrecht 2013</copyright-statement><license><license-p>This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.</license-p></license></permissions><abstract id="Abs1"><p>Aminopeptidase N (APN) inhibitors have been reported to be effective in treating of life threatening diseases including cancer. Validated ligand- and structure-based pharmacophore mapping approaches were combined with Bayesian modeling and recursive partitioning to identify structural and physicochemical requirements for highly active APN inhibitors. Based on the assumption that ligand- and structure-based pharmacophore models are complementary, the efficacy of ‘multiple pharmacophore screening’ for filtering true positive virtual hits was investigated. These multiple pharmacophore screening methods were utilized to search novel virtual hits for APN inhibition. The number of hits was refined and reduced by recursive partitioning, drug-likeliness, pharmacokinetic property prediction, and comparative molecular-docking studies. Four compounds were proposed as the potential virtual hits for APN enzyme inhibition.</p><sec><title>Electronic supplementary material</title><p>The online version of this article (doi:10.1007/s11030-013-9422-5) contains supplementary material, which is available to authorized users.</p></sec></abstract><kwd-group xml:lang="en"><title>Keywords</title><kwd>Aminopeptidase N</kwd><kwd>Pharmacophore mapping</kwd><kwd>Bayesian modeling</kwd><kwd>Recursive partitioning</kwd><kwd>Molecular docking</kwd><kwd>Virtual hits</kwd></kwd-group><custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name><meta-value>© Springer Science+Business Media Dordrecht 2013</meta-value></custom-meta></custom-meta-group></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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