In silico prediction of SARS protease inhibitors by virtual high throughput screening.
Identifieur interne : 001941 ( Ncbi/Curation ); précédent : 001940; suivant : 001942In silico prediction of SARS protease inhibitors by virtual high throughput screening.
Auteurs : Dariusz Plewczynski [Pologne] ; Marcin Hoffmann ; Marcin Von Grotthuss ; Krzysztof Ginalski ; Leszek RychewskiSource :
- Chemical biology & drug design [ 1747-0277 ] ; 2007.
Descripteurs français
- KwdFr :
- Bases de données de protéines, Biologie informatique (), Conception de médicament, Conformation moléculaire, Endopeptidases (métabolisme), Inhibiteurs de protéases (), Inhibiteurs de protéases (pharmacologie), Ligands, Modèles moléculaires, Relation structure-activité, Simulation numérique, Virus du SRAS (), Virus du SRAS (enzymologie), Évaluation préclinique de médicament ().
- MESH :
- enzymologie : Virus du SRAS.
- métabolisme : Endopeptidases.
- pharmacologie : Inhibiteurs de protéases.
- Bases de données de protéines, Biologie informatique, Conception de médicament, Conformation moléculaire, Inhibiteurs de protéases, Ligands, Modèles moléculaires, Relation structure-activité, Simulation numérique, Virus du SRAS, Évaluation préclinique de médicament.
English descriptors
- KwdEn :
- Computational Biology (methods), Computer Simulation, Databases, Protein, Drug Design, Drug Evaluation, Preclinical (methods), Endopeptidases (metabolism), Ligands, Models, Molecular, Molecular Conformation, Protease Inhibitors (chemistry), Protease Inhibitors (pharmacology), SARS Virus (drug effects), SARS Virus (enzymology), Structure-Activity Relationship.
- MESH :
- chemical , chemistry : Protease Inhibitors.
- chemical , metabolism : Endopeptidases.
- drug effects : SARS Virus.
- enzymology : SARS Virus.
- methods : Computational Biology, Drug Evaluation, Preclinical.
- chemical , pharmacology : Protease Inhibitors.
- Computer Simulation, Databases, Protein, Drug Design, Ligands, Models, Molecular, Molecular Conformation, Structure-Activity Relationship.
Abstract
A structure-based in silico virtual drug discovery procedure was assessed with severe acute respiratory syndrome coronavirus main protease serving as a case study. First, potential compounds were extracted from protein-ligand complexes selected from Protein Data Bank database based on structural similarity to the target protein. Later, the set of compounds was ranked by docking scores using a Electronic High-Throughput Screening flexible docking procedure to select the most promising molecules. The set of best performing compounds was then used for similarity search over the 1 million entries in the Ligand.Info Meta-Database. Selected molecules having close structural relationship to a 2-methyl-2,4-pentanediol may provide candidate lead compounds toward the development of novel allosteric severe acute respiratory syndrome protease inhibitors.
DOI: 10.1111/j.1747-0285.2007.00475.x
PubMed: 17461975
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xml:lang="en"><term>Computational Biology (methods)</term><term>Computer Simulation</term><term>Databases, Protein</term><term>Drug Design</term><term>Drug Evaluation, Preclinical (methods)</term><term>Endopeptidases (metabolism)</term><term>Ligands</term><term>Models, Molecular</term><term>Molecular Conformation</term><term>Protease Inhibitors (chemistry)</term><term>Protease Inhibitors (pharmacology)</term><term>SARS Virus (drug effects)</term><term>SARS Virus (enzymology)</term><term>Structure-Activity Relationship</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Bases de données de protéines</term><term>Biologie informatique ()</term><term>Conception de médicament</term><term>Conformation moléculaire</term><term>Endopeptidases (métabolisme)</term><term>Inhibiteurs de protéases ()</term><term>Inhibiteurs de protéases (pharmacologie)</term><term>Ligands</term><term>Modèles moléculaires</term><term>Relation structure-activité</term><term>Simulation numérique</term><term>Virus du SRAS ()</term><term>Virus du SRAS (enzymologie)</term><term>Évaluation préclinique de médicament ()</term></keywords><keywords scheme="MESH" type="chemical" qualifier="chemistry" xml:lang="en"><term>Protease Inhibitors</term></keywords><keywords scheme="MESH" type="chemical" qualifier="metabolism" xml:lang="en"><term>Endopeptidases</term></keywords><keywords scheme="MESH" qualifier="drug effects" xml:lang="en"><term>SARS Virus</term></keywords><keywords scheme="MESH" qualifier="enzymologie" xml:lang="fr"><term>Virus du SRAS</term></keywords><keywords scheme="MESH" qualifier="enzymology" xml:lang="en"><term>SARS Virus</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Computational Biology</term><term>Drug Evaluation, Preclinical</term></keywords><keywords scheme="MESH" qualifier="métabolisme" xml:lang="fr"><term>Endopeptidases</term></keywords><keywords scheme="MESH" qualifier="pharmacologie" xml:lang="fr"><term>Inhibiteurs de protéases</term></keywords><keywords scheme="MESH" type="chemical" qualifier="pharmacology" xml:lang="en"><term>Protease Inhibitors</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Computer Simulation</term><term>Databases, Protein</term><term>Drug Design</term><term>Ligands</term><term>Models, Molecular</term><term>Molecular Conformation</term><term>Structure-Activity Relationship</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Bases de données de protéines</term><term>Biologie informatique</term><term>Conception de médicament</term><term>Conformation moléculaire</term><term>Inhibiteurs de protéases</term><term>Ligands</term><term>Modèles moléculaires</term><term>Relation structure-activité</term><term>Simulation numérique</term><term>Virus du SRAS</term><term>Évaluation préclinique de médicament</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">A structure-based in silico virtual drug discovery procedure was assessed with severe acute respiratory syndrome coronavirus main protease serving as a case study. First, potential compounds were extracted from protein-ligand complexes selected from Protein Data Bank database based on structural similarity to the target protein. Later, the set of compounds was ranked by docking scores using a Electronic High-Throughput Screening flexible docking procedure to select the most promising molecules. The set of best performing compounds was then used for similarity search over the 1 million entries in the Ligand.Info Meta-Database. Selected molecules having close structural relationship to a 2-methyl-2,4-pentanediol may provide candidate lead compounds toward the development of novel allosteric severe acute respiratory syndrome protease inhibitors.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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