Seeking novel leads through structure-based pharmacophore design

We developed a procedure that identifies "novel" biologically active compounds that are expected to be distinct from known active compounds with respect to specificity and other such characteristics. The procedure involves mapping a set of known active compounds (training set) onto all possible hydrogen bonding and lipophilic interaction sites of an enzyme active site and flagging those interactions that are utilized by the training set. These flagged sites are removed (except for those that are deemed critical binding sites), leaving only potential interaction sites not utilized by the active compounds. Once unflagged sites were enumerated, pharmacophore models were then generated, scored, and prioritized where the top pharmacophore model was used to search 3D databases for identifying new leads. This procedure was applied to HIV-1 protease inhibitors. Several compounds retrieved by the top pharmacophore model were identified as moderately active (in mMolar range).

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Bibliographic Details
Main Authors: Fisher,Luke S., Güner,Osman F.
Format: Digital revista
Language:English
Published: Sociedade Brasileira de Química 2002
Online Access:http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532002000600008
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spelling oai:scielo:S0103-505320020006000082015-11-26Seeking novel leads through structure-based pharmacophore designFisher,Luke S.Güner,Osman F. pharmacophores structure-based design 3D databses We developed a procedure that identifies "novel" biologically active compounds that are expected to be distinct from known active compounds with respect to specificity and other such characteristics. The procedure involves mapping a set of known active compounds (training set) onto all possible hydrogen bonding and lipophilic interaction sites of an enzyme active site and flagging those interactions that are utilized by the training set. These flagged sites are removed (except for those that are deemed critical binding sites), leaving only potential interaction sites not utilized by the active compounds. Once unflagged sites were enumerated, pharmacophore models were then generated, scored, and prioritized where the top pharmacophore model was used to search 3D databases for identifying new leads. This procedure was applied to HIV-1 protease inhibitors. Several compounds retrieved by the top pharmacophore model were identified as moderately active (in mMolar range).info:eu-repo/semantics/openAccessSociedade Brasileira de QuímicaJournal of the Brazilian Chemical Society v.13 n.6 20022002-11-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532002000600008en10.1590/S0103-50532002000600008
institution SCIELO
collection OJS
country Brasil
countrycode BR
component Revista
access En linea
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region America del Sur
libraryname SciELO
language English
format Digital
author Fisher,Luke S.
Güner,Osman F.
spellingShingle Fisher,Luke S.
Güner,Osman F.
Seeking novel leads through structure-based pharmacophore design
author_facet Fisher,Luke S.
Güner,Osman F.
author_sort Fisher,Luke S.
title Seeking novel leads through structure-based pharmacophore design
title_short Seeking novel leads through structure-based pharmacophore design
title_full Seeking novel leads through structure-based pharmacophore design
title_fullStr Seeking novel leads through structure-based pharmacophore design
title_full_unstemmed Seeking novel leads through structure-based pharmacophore design
title_sort seeking novel leads through structure-based pharmacophore design
description We developed a procedure that identifies "novel" biologically active compounds that are expected to be distinct from known active compounds with respect to specificity and other such characteristics. The procedure involves mapping a set of known active compounds (training set) onto all possible hydrogen bonding and lipophilic interaction sites of an enzyme active site and flagging those interactions that are utilized by the training set. These flagged sites are removed (except for those that are deemed critical binding sites), leaving only potential interaction sites not utilized by the active compounds. Once unflagged sites were enumerated, pharmacophore models were then generated, scored, and prioritized where the top pharmacophore model was used to search 3D databases for identifying new leads. This procedure was applied to HIV-1 protease inhibitors. Several compounds retrieved by the top pharmacophore model were identified as moderately active (in mMolar range).
publisher Sociedade Brasileira de Química
publishDate 2002
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532002000600008
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