Protein Structure Prediction in Structure based drug design : Protein structure prediction in medicinal chemistry
Identifieur interne : 005A83 ( Main/Exploration ); précédent : 005A82; suivant : 005A84Protein Structure Prediction in Structure based drug design : Protein structure prediction in medicinal chemistry
Auteurs : Mayuko Takeda-Shitaka [Japon] ; Daisuke Takaya [Japon] ; Chieko Chiba [Japon] ; Hirokazu Tanaka [Japon] ; Hideaki Umeyama [Japon]Source :
- Current medicinal chemistry [ 0929-8673 ] ; 2004.
Descripteurs français
- KwdFr :
- MESH :
- génétique : Protéines.
- Pascal (Inist)
- Alignement de séquences, Article synthèse, Conception de médicament, Données de séquences moléculaires, Génomique, Humains, Modèles chimiques, Modèles moléculaires, Protéines, Relation structure activité, Prédiction, Simulation numérique, Structure, Protéine, Structure secondaire, Génomique, Interaction moléculaire, Modélisation, Modèle moléculaire, Homologie, Coronavirus, Structure secondaire des protéines, Syndrome respiratoire aigu sévère, RNA-directed RNA polymerase, Site actif, Séquence d'acides aminés, Virus du SRAS.
English descriptors
- KwdEn :
- Active site, Amino Acid Sequence, Computer Simulation, Coronavirus, Drug Design, Genomics, Homology, Humans, Modeling, Models, Chemical, Models, Molecular, Molecular Sequence Data, Molecular interaction, Molecular model, Prediction, Protein, Protein Structure, Secondary, Proteins (chemistry), Proteins (genetics), RNA-directed RNA polymerase, Review, SARS Virus (chemistry), Secondary structure, Sequence Alignment, Severe acute respiratory syndrome, Structure, Structure activity relation.
- MESH :
- chemical , chemistry : Proteins.
- chemical , genetics : Proteins.
- chemistry : SARS Virus.
- Amino Acid Sequence, Computer Simulation, Drug Design, Genomics, Humans, Models, Chemical, Models, Molecular, Molecular Sequence Data, Protein Structure, Secondary, Sequence Alignment.
Abstract
The human genome and other genome sequencing projects have generated huge amounts of protein sequence information. Recently, a structural genomics project that aims to determine at-least one representative three-dimensional structure from every protein family experimentally has been started. Homology modeling will play an essential role in structure based drug design such as in silico screening; because based on these representative structures the three-dimensional structures of the remaining proteins encoded in the various genomes can be predicted by homology modeling. The results of the last Critical Assessment of Techniques for Protein Structure Prediction (CASP5) demonstrated that the quality of homology modeling prediction has improved; reaching a level of reliability that biologists can now confidently use homology modeling. With improvements in modeling software and the growing number of known protein structures, homology modeling is becoming a more and more powerful and reliable tool. The present paper discusses the features and roles of homology modeling in structure based drug design, and describes the CHIMERA and FAMS modeling systems as examples. For a sample application, homology modeling of non-structural proteins of the severe acute respiratory syndrome (SARS) coronavirus is discussed. Many biological functions involve formation of protein-protein complexes; in which the protein molecules behave dynamically in the course of binding. Therefore, an understanding of protein-protein interaction will be very important for structure based drug design. To this end, normal mode analysis is useful. The present paper discusses the prediction of protein-protein interaction using normal mode analysis and examples of applications are given.
Affiliations:
Links toward previous steps (curation, corpus...)
- to stream PascalFrancis, to step Corpus: 000806
- to stream PascalFrancis, to step Curation: 000184
- to stream PascalFrancis, to step Checkpoint: 000790
- to stream Main, to step Merge: 005F41
- to stream PubMed, to step Corpus: 002E92
- to stream PubMed, to step Curation: 002E92
- to stream PubMed, to step Checkpoint: 002B29
- to stream Ncbi, to step Merge: 000699
- to stream Ncbi, to step Curation: 000699
- to stream Ncbi, to step Checkpoint: 000699
- to stream Main, to step Merge: 005565
- to stream Main, to step Curation: 005A83
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" level="a">Protein Structure Prediction in Structure based drug design : Protein structure prediction in medicinal chemistry</title>
<author><name sortKey="Takeda Shitaka, Mayuko" sort="Takeda Shitaka, Mayuko" uniqKey="Takeda Shitaka M" first="Mayuko" last="Takeda-Shitaka">Mayuko Takeda-Shitaka</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>School of Pharmaceutical Sciences, Kitasato University, 5-9-1 Shirokane</s1>
<s2>Minato-ku, Tokyo 108-8641</s2>
<s3>JPN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
</inist:fA14>
<country>Japon</country>
<placeName><settlement type="city">Tokyo</settlement>
<region type="région">Région de Kantō</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Takaya, Daisuke" sort="Takaya, Daisuke" uniqKey="Takaya D" first="Daisuke" last="Takaya">Daisuke Takaya</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>School of Pharmaceutical Sciences, Kitasato University, 5-9-1 Shirokane</s1>
<s2>Minato-ku, Tokyo 108-8641</s2>
<s3>JPN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
</inist:fA14>
<country>Japon</country>
<placeName><settlement type="city">Tokyo</settlement>
<region type="région">Région de Kantō</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Chiba, Chieko" sort="Chiba, Chieko" uniqKey="Chiba C" first="Chieko" last="Chiba">Chieko Chiba</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>School of Pharmaceutical Sciences, Kitasato University, 5-9-1 Shirokane</s1>
<s2>Minato-ku, Tokyo 108-8641</s2>
<s3>JPN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
</inist:fA14>
<country>Japon</country>
<placeName><settlement type="city">Tokyo</settlement>
<region type="région">Région de Kantō</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Tanaka, Hirokazu" sort="Tanaka, Hirokazu" uniqKey="Tanaka H" first="Hirokazu" last="Tanaka">Hirokazu Tanaka</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>School of Pharmaceutical Sciences, Kitasato University, 5-9-1 Shirokane</s1>
<s2>Minato-ku, Tokyo 108-8641</s2>
<s3>JPN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
</inist:fA14>
<country>Japon</country>
<placeName><settlement type="city">Tokyo</settlement>
<region type="région">Région de Kantō</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Umeyama, Hideaki" sort="Umeyama, Hideaki" uniqKey="Umeyama H" first="Hideaki" last="Umeyama">Hideaki Umeyama</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>School of Pharmaceutical Sciences, Kitasato University, 5-9-1 Shirokane</s1>
<s2>Minato-ku, Tokyo 108-8641</s2>
<s3>JPN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
</inist:fA14>
<country>Japon</country>
<placeName><settlement type="city">Tokyo</settlement>
<region type="région">Région de Kantō</region>
</placeName>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">INIST</idno>
<idno type="inist">04-0517242</idno>
<date when="2004">2004</date>
<idno type="stanalyst">PASCAL 04-0517242 INIST</idno>
<idno type="RBID">Pascal:04-0517242</idno>
<idno type="wicri:Area/PascalFrancis/Corpus">000806</idno>
<idno type="wicri:Area/PascalFrancis/Curation">000184</idno>
<idno type="wicri:Area/PascalFrancis/Checkpoint">000790</idno>
<idno type="wicri:explorRef" wicri:stream="PascalFrancis" wicri:step="Checkpoint">000790</idno>
<idno type="wicri:doubleKey">0929-8673:2004:Takeda Shitaka M:protein:structure:prediction</idno>
<idno type="wicri:Area/Main/Merge">005F41</idno>
<idno type="wicri:source">PubMed</idno>
<idno type="RBID">pubmed:15032603</idno>
<idno type="wicri:Area/PubMed/Corpus">002E92</idno>
<idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">002E92</idno>
<idno type="wicri:Area/PubMed/Curation">002E92</idno>
<idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">002E92</idno>
<idno type="wicri:Area/PubMed/Checkpoint">002B29</idno>
<idno type="wicri:explorRef" wicri:stream="Checkpoint" wicri:step="PubMed">002B29</idno>
<idno type="wicri:Area/Ncbi/Merge">000699</idno>
<idno type="wicri:Area/Ncbi/Curation">000699</idno>
<idno type="wicri:Area/Ncbi/Checkpoint">000699</idno>
<idno type="wicri:doubleKey">0929-8673:2004:Takeda Shitaka M:protein:structure:prediction</idno>
<idno type="wicri:Area/Main/Merge">005565</idno>
<idno type="wicri:Area/Main/Curation">005A83</idno>
<idno type="wicri:Area/Main/Exploration">005A83</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Protein Structure Prediction in Structure based drug design : Protein structure prediction in medicinal chemistry</title>
<author><name sortKey="Takeda Shitaka, Mayuko" sort="Takeda Shitaka, Mayuko" uniqKey="Takeda Shitaka M" first="Mayuko" last="Takeda-Shitaka">Mayuko Takeda-Shitaka</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>School of Pharmaceutical Sciences, Kitasato University, 5-9-1 Shirokane</s1>
<s2>Minato-ku, Tokyo 108-8641</s2>
<s3>JPN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
</inist:fA14>
<country>Japon</country>
<placeName><settlement type="city">Tokyo</settlement>
<region type="région">Région de Kantō</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Takaya, Daisuke" sort="Takaya, Daisuke" uniqKey="Takaya D" first="Daisuke" last="Takaya">Daisuke Takaya</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>School of Pharmaceutical Sciences, Kitasato University, 5-9-1 Shirokane</s1>
<s2>Minato-ku, Tokyo 108-8641</s2>
<s3>JPN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
</inist:fA14>
<country>Japon</country>
<placeName><settlement type="city">Tokyo</settlement>
<region type="région">Région de Kantō</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Chiba, Chieko" sort="Chiba, Chieko" uniqKey="Chiba C" first="Chieko" last="Chiba">Chieko Chiba</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>School of Pharmaceutical Sciences, Kitasato University, 5-9-1 Shirokane</s1>
<s2>Minato-ku, Tokyo 108-8641</s2>
<s3>JPN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
</inist:fA14>
<country>Japon</country>
<placeName><settlement type="city">Tokyo</settlement>
<region type="région">Région de Kantō</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Tanaka, Hirokazu" sort="Tanaka, Hirokazu" uniqKey="Tanaka H" first="Hirokazu" last="Tanaka">Hirokazu Tanaka</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>School of Pharmaceutical Sciences, Kitasato University, 5-9-1 Shirokane</s1>
<s2>Minato-ku, Tokyo 108-8641</s2>
<s3>JPN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
</inist:fA14>
<country>Japon</country>
<placeName><settlement type="city">Tokyo</settlement>
<region type="région">Région de Kantō</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Umeyama, Hideaki" sort="Umeyama, Hideaki" uniqKey="Umeyama H" first="Hideaki" last="Umeyama">Hideaki Umeyama</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>School of Pharmaceutical Sciences, Kitasato University, 5-9-1 Shirokane</s1>
<s2>Minato-ku, Tokyo 108-8641</s2>
<s3>JPN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
</inist:fA14>
<country>Japon</country>
<placeName><settlement type="city">Tokyo</settlement>
<region type="région">Région de Kantō</region>
</placeName>
</affiliation>
</author>
</analytic>
<series><title level="j" type="main">Current medicinal chemistry</title>
<title level="j" type="abbreviated">Curr. med. chem.</title>
<idno type="ISSN">0929-8673</idno>
<imprint><date when="2004">2004</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
<seriesStmt><title level="j" type="main">Current medicinal chemistry</title>
<title level="j" type="abbreviated">Curr. med. chem.</title>
<idno type="ISSN">0929-8673</idno>
</seriesStmt>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Active site</term>
<term>Amino Acid Sequence</term>
<term>Computer Simulation</term>
<term>Coronavirus</term>
<term>Drug Design</term>
<term>Genomics</term>
<term>Homology</term>
<term>Humans</term>
<term>Modeling</term>
<term>Models, Chemical</term>
<term>Models, Molecular</term>
<term>Molecular Sequence Data</term>
<term>Molecular interaction</term>
<term>Molecular model</term>
<term>Prediction</term>
<term>Protein</term>
<term>Protein Structure, Secondary</term>
<term>Proteins (chemistry)</term>
<term>Proteins (genetics)</term>
<term>RNA-directed RNA polymerase</term>
<term>Review</term>
<term>SARS Virus (chemistry)</term>
<term>Secondary structure</term>
<term>Sequence Alignment</term>
<term>Severe acute respiratory syndrome</term>
<term>Structure</term>
<term>Structure activity relation</term>
</keywords>
<keywords scheme="KwdFr" xml:lang="fr"><term>Alignement de séquences</term>
<term>Conception de médicament</term>
<term>Données de séquences moléculaires</term>
<term>Génomique</term>
<term>Humains</term>
<term>Modèles chimiques</term>
<term>Modèles moléculaires</term>
<term>Protéines ()</term>
<term>Protéines (génétique)</term>
<term>Simulation numérique</term>
<term>Structure secondaire des protéines</term>
<term>Séquence d'acides aminés</term>
<term>Virus du SRAS ()</term>
</keywords>
<keywords scheme="MESH" type="chemical" qualifier="chemistry" xml:lang="en"><term>Proteins</term>
</keywords>
<keywords scheme="MESH" type="chemical" qualifier="genetics" xml:lang="en"><term>Proteins</term>
</keywords>
<keywords scheme="MESH" qualifier="chemistry" xml:lang="en"><term>SARS Virus</term>
</keywords>
<keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Protéines</term>
</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Amino Acid Sequence</term>
<term>Computer Simulation</term>
<term>Drug Design</term>
<term>Genomics</term>
<term>Humans</term>
<term>Models, Chemical</term>
<term>Models, Molecular</term>
<term>Molecular Sequence Data</term>
<term>Protein Structure, Secondary</term>
<term>Sequence Alignment</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr"><term>Alignement de séquences</term>
<term>Article synthèse</term>
<term>Conception de médicament</term>
<term>Données de séquences moléculaires</term>
<term>Génomique</term>
<term>Humains</term>
<term>Modèles chimiques</term>
<term>Modèles moléculaires</term>
<term>Protéines</term>
<term>Relation structure activité</term>
<term>Prédiction</term>
<term>Simulation numérique</term>
<term>Structure</term>
<term>Protéine</term>
<term>Structure secondaire</term>
<term>Génomique</term>
<term>Interaction moléculaire</term>
<term>Modélisation</term>
<term>Modèle moléculaire</term>
<term>Homologie</term>
<term>Coronavirus</term>
<term>Structure secondaire des protéines</term>
<term>Syndrome respiratoire aigu sévère</term>
<term>RNA-directed RNA polymerase</term>
<term>Site actif</term>
<term>Séquence d'acides aminés</term>
<term>Virus du SRAS</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">The human genome and other genome sequencing projects have generated huge amounts of protein sequence information. Recently, a structural genomics project that aims to determine at-least one representative three-dimensional structure from every protein family experimentally has been started. Homology modeling will play an essential role in structure based drug design such as in silico screening; because based on these representative structures the three-dimensional structures of the remaining proteins encoded in the various genomes can be predicted by homology modeling. The results of the last Critical Assessment of Techniques for Protein Structure Prediction (CASP5) demonstrated that the quality of homology modeling prediction has improved; reaching a level of reliability that biologists can now confidently use homology modeling. With improvements in modeling software and the growing number of known protein structures, homology modeling is becoming a more and more powerful and reliable tool. The present paper discusses the features and roles of homology modeling in structure based drug design, and describes the CHIMERA and FAMS modeling systems as examples. For a sample application, homology modeling of non-structural proteins of the severe acute respiratory syndrome (SARS) coronavirus is discussed. Many biological functions involve formation of protein-protein complexes; in which the protein molecules behave dynamically in the course of binding. Therefore, an understanding of protein-protein interaction will be very important for structure based drug design. To this end, normal mode analysis is useful. The present paper discusses the prediction of protein-protein interaction using normal mode analysis and examples of applications are given.</div>
</front>
</TEI>
<affiliations><list><country><li>Japon</li>
</country>
<region><li>Région de Kantō</li>
</region>
<settlement><li>Tokyo</li>
</settlement>
</list>
<tree><country name="Japon"><region name="Région de Kantō"><name sortKey="Takeda Shitaka, Mayuko" sort="Takeda Shitaka, Mayuko" uniqKey="Takeda Shitaka M" first="Mayuko" last="Takeda-Shitaka">Mayuko Takeda-Shitaka</name>
</region>
<name sortKey="Chiba, Chieko" sort="Chiba, Chieko" uniqKey="Chiba C" first="Chieko" last="Chiba">Chieko Chiba</name>
<name sortKey="Takaya, Daisuke" sort="Takaya, Daisuke" uniqKey="Takaya D" first="Daisuke" last="Takaya">Daisuke Takaya</name>
<name sortKey="Tanaka, Hirokazu" sort="Tanaka, Hirokazu" uniqKey="Tanaka H" first="Hirokazu" last="Tanaka">Hirokazu Tanaka</name>
<name sortKey="Umeyama, Hideaki" sort="Umeyama, Hideaki" uniqKey="Umeyama H" first="Hideaki" last="Umeyama">Hideaki Umeyama</name>
</country>
</tree>
</affiliations>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Sante/explor/SrasV1/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 005A83 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 005A83 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Sante |area= SrasV1 |flux= Main |étape= Exploration |type= RBID |clé= Pascal:04-0517242 |texte= Protein Structure Prediction in Structure based drug design : Protein structure prediction in medicinal chemistry }}
This area was generated with Dilib version V0.6.33. |