Protein structure prediction in structure based drug design.
Identifieur interne : 005565 ( Main/Merge ); précédent : 005564; suivant : 005566Protein structure prediction in structure based drug design.
Auteurs : Mayuko Takeda-Shitaka [Japon] ; Daisuke Takaya ; Chieko Chiba ; Hirokazu Tanaka ; Hideaki UmeyamaSource :
- Current medicinal chemistry [ 0929-8673 ] ; 2004.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- 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.
DOI: 10.2174/0929867043455837
PubMed: 15032603
Links toward previous steps (curation, corpus...)
- 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
Links to Exploration step
pubmed:15032603Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Protein structure prediction in structure based drug design.</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"><nlm:affiliation>School of Pharmaceutical Sciences, Kitasato University, 5-9-1 Shirokane, Minato-ku, Tokyo 108-8641, Japan. shitakam@pharm.kitasato-u.ac.jp</nlm:affiliation><country xml:lang="fr">Japon</country><wicri:regionArea>School of Pharmaceutical Sciences, Kitasato University, 5-9-1 Shirokane, Minato-ku, Tokyo 108-8641</wicri:regionArea><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></author><author><name sortKey="Chiba, Chieko" sort="Chiba, Chieko" uniqKey="Chiba C" first="Chieko" last="Chiba">Chieko Chiba</name></author><author><name sortKey="Tanaka, Hirokazu" sort="Tanaka, Hirokazu" uniqKey="Tanaka H" first="Hirokazu" last="Tanaka">Hirokazu Tanaka</name></author><author><name sortKey="Umeyama, Hideaki" sort="Umeyama, Hideaki" uniqKey="Umeyama H" first="Hideaki" last="Umeyama">Hideaki Umeyama</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2004">2004</date><idno type="RBID">pubmed:15032603</idno><idno type="pmid">15032603</idno><idno type="doi">10.2174/0929867043455837</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></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Protein structure prediction in structure based drug design.</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"><nlm:affiliation>School of Pharmaceutical Sciences, Kitasato University, 5-9-1 Shirokane, Minato-ku, Tokyo 108-8641, Japan. shitakam@pharm.kitasato-u.ac.jp</nlm:affiliation><country xml:lang="fr">Japon</country><wicri:regionArea>School of Pharmaceutical Sciences, Kitasato University, 5-9-1 Shirokane, Minato-ku, Tokyo 108-8641</wicri:regionArea><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></author><author><name sortKey="Chiba, Chieko" sort="Chiba, Chieko" uniqKey="Chiba C" first="Chieko" last="Chiba">Chieko Chiba</name></author><author><name sortKey="Tanaka, Hirokazu" sort="Tanaka, Hirokazu" uniqKey="Tanaka H" first="Hirokazu" last="Tanaka">Hirokazu Tanaka</name></author><author><name sortKey="Umeyama, Hideaki" sort="Umeyama, Hideaki" uniqKey="Umeyama H" first="Hideaki" last="Umeyama">Hideaki Umeyama</name></author></analytic><series><title level="j">Current medicinal chemistry</title><idno type="ISSN">0929-8673</idno><imprint><date when="2004" type="published">2004</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" 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>Proteins (chemistry)</term><term>Proteins (genetics)</term><term>SARS Virus (chemistry)</term><term>Sequence Alignment</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="MESH" 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>Simulation numérique</term><term>Structure secondaire des protéines</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></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Sante/explor/SrasV1/Data/Main/Merge
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 005565 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Merge/biblio.hfd -nk 005565 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Sante
|area= SrasV1
|flux= Main
|étape= Merge
|type= RBID
|clé= pubmed:15032603
|texte= Protein structure prediction in structure based drug design.
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Main/Merge/RBID.i -Sk "pubmed:15032603" \
| HfdSelect -Kh $EXPLOR_AREA/Data/Main/Merge/biblio.hfd \
| NlmPubMed2Wicri -a SrasV1
| This area was generated with Dilib version V0.6.33. |  |