In Silico Discovery of Candidate Drugs against Covid-19.
Identifieur interne : 000560 ( 2020/Analysis ); précédent : 000559; suivant : 000561In Silico Discovery of Candidate Drugs against Covid-19.
Auteurs : Claudia Cava [Italie] ; Gloria Bertoli [Italie] ; Isabella Castiglioni [Italie]Source :
- Viruses [ 1999-4915 ] ; 2020.
Descripteurs français
- KwdFr :
- Analyse de profil d'expression de gènes, Anti-inflammatoires (pharmacologie), Anti-inflammatoires (usage thérapeutique), Antiviraux (pharmacologie), Antiviraux (usage thérapeutique), Bases de données génétiques, Biologie informatique, Cartographie d'interactions entre protéines, Découverte de médicament, Humains, Infections à coronavirus (traitement médicamenteux), Infections à coronavirus (virologie), Pandémies, Peptidyl-Dipeptidase A (génétique), Peptidyl-Dipeptidase A (métabolisme), Pneumopathie virale (traitement médicamenteux), Pneumopathie virale (virologie), Poumon (enzymologie), Récepteurs viraux (génétique), Récepteurs viraux (métabolisme), Réseaux de régulation génique, Simulation numérique.
- MESH :
- enzymologie : Poumon.
- génétique : Peptidyl-Dipeptidase A, Récepteurs viraux.
- métabolisme : Peptidyl-Dipeptidase A, Récepteurs viraux.
- pharmacologie : Anti-inflammatoires, Antiviraux.
- traitement médicamenteux : Infections à coronavirus, Pneumopathie virale.
- usage thérapeutique : Anti-inflammatoires, Antiviraux.
- virologie : Infections à coronavirus, Pneumopathie virale.
- Analyse de profil d'expression de gènes, Bases de données génétiques, Biologie informatique, Cartographie d'interactions entre protéines, Découverte de médicament, Humains, Pandémies, Réseaux de régulation génique, Simulation numérique.
English descriptors
- KwdEn :
- Anti-Inflammatory Agents (pharmacology), Anti-Inflammatory Agents (therapeutic use), Antiviral Agents (pharmacology), Antiviral Agents (therapeutic use), Betacoronavirus (drug effects), Computational Biology, Computer Simulation, Coronavirus Infections (drug therapy), Coronavirus Infections (virology), Databases, Genetic, Drug Discovery, Gene Expression Profiling, Gene Regulatory Networks, Humans, Lung (enzymology), Pandemics, Peptidyl-Dipeptidase A (genetics), Peptidyl-Dipeptidase A (metabolism), Pneumonia, Viral (drug therapy), Pneumonia, Viral (virology), Protein Interaction Mapping, Receptors, Virus (genetics), Receptors, Virus (metabolism).
- MESH :
- chemical , genetics : Peptidyl-Dipeptidase A, Receptors, Virus.
- chemical , metabolism : Peptidyl-Dipeptidase A, Receptors, Virus.
- chemical , pharmacology : Anti-Inflammatory Agents, Antiviral Agents.
- chemical , therapeutic use : Anti-Inflammatory Agents, Antiviral Agents.
- drug effects : Betacoronavirus.
- drug therapy : Coronavirus Infections, Pneumonia, Viral.
- enzymology : Lung.
- virology : Coronavirus Infections, Pneumonia, Viral.
- Computational Biology, Computer Simulation, Databases, Genetic, Drug Discovery, Gene Expression Profiling, Gene Regulatory Networks, Humans, Pandemics, Protein Interaction Mapping.
Abstract
Previous studies reported that Angiotensin converting enzyme 2 (ACE2) is the main cell receptor of SARS-CoV and SARS-CoV-2. It plays a key role in the access of the virus into the cell to produce the final infection. In the present study we investigated in silico the basic mechanism of ACE2 in the lung and provided evidences for new potentially effective drugs for Covid-19. Specifically, we used the gene expression profiles from public datasets including The Cancer Genome Atlas, Gene Expression Omnibus and Genotype-Tissue Expression, Gene Ontology and pathway enrichment analysis to investigate the main functions of ACE2-correlated genes. We constructed a protein-protein interaction network containing the genes co-expressed with ACE2. Finally, we focused on the genes in the network that are already associated with known drugs and evaluated their role for a potential treatment of Covid-19. Our results demonstrate that the genes correlated with ACE2 are mainly enriched in the sterol biosynthetic process, Aryldialkylphosphatase activity, adenosylhomocysteinase activity, trialkylsulfonium hydrolase activity, acetate-CoA and CoA ligase activity. We identified a network of 193 genes, 222 interactions and 36 potential drugs that could have a crucial role. Among possible interesting drugs for Covid-19 treatment, we found Nimesulide, Fluticasone Propionate, Thiabendazole, Photofrin, Didanosine and Flutamide.
DOI: 10.3390/v12040404
PubMed: 32268515
Affiliations:
Links toward previous steps (curation, corpus...)
- to stream PubMed, to step Corpus: 000280
- to stream PubMed, to step Curation: 000280
- to stream PubMed, to step Checkpoint: 000447
- to stream Ncbi, to step Merge: 003827
- to stream Ncbi, to step Curation: 003827
- to stream Ncbi, to step Checkpoint: 003827
- to stream Main, to step Merge: 000560
- to stream Main, to step Curation: 000560
- to stream Main, to step Exploration: 000560
- to stream 2020, to step Extraction: 000560
Links to Exploration step
pubmed:32268515Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">In Silico Discovery of Candidate Drugs against Covid-19.</title><author><name sortKey="Cava, Claudia" sort="Cava, Claudia" uniqKey="Cava C" first="Claudia" last="Cava">Claudia Cava</name><affiliation wicri:level="3"><nlm:affiliation>Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090 Segrate-Milan, Milan, Italy.</nlm:affiliation><country xml:lang="fr">Italie</country><wicri:regionArea>Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090 Segrate-Milan, Milan</wicri:regionArea><placeName><settlement type="city">Milan</settlement><region nuts="2">Lombardie</region></placeName></affiliation></author><author><name sortKey="Bertoli, Gloria" sort="Bertoli, Gloria" uniqKey="Bertoli G" first="Gloria" last="Bertoli">Gloria Bertoli</name><affiliation wicri:level="3"><nlm:affiliation>Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090 Segrate-Milan, Milan, Italy.</nlm:affiliation><country xml:lang="fr">Italie</country><wicri:regionArea>Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090 Segrate-Milan, Milan</wicri:regionArea><placeName><settlement type="city">Milan</settlement><region nuts="2">Lombardie</region></placeName></affiliation></author><author><name sortKey="Castiglioni, Isabella" sort="Castiglioni, Isabella" uniqKey="Castiglioni I" first="Isabella" last="Castiglioni">Isabella Castiglioni</name><affiliation wicri:level="3"><nlm:affiliation>Department of Physics "Giuseppe Occhialini", University of Milan-Bicocca Piazza dell'Ateneo Nuovo, 1 - 20126, Milan, Italy.</nlm:affiliation><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Physics "Giuseppe Occhialini", University of Milan-Bicocca Piazza dell'Ateneo Nuovo, 1 - 20126, Milan</wicri:regionArea><placeName><settlement type="city">Milan</settlement><region nuts="2">Lombardie</region></placeName></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2020">2020</date><idno type="RBID">pubmed:32268515</idno><idno type="pmid">32268515</idno><idno type="doi">10.3390/v12040404</idno><idno type="wicri:Area/PubMed/Corpus">000280</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000280</idno><idno type="wicri:Area/PubMed/Curation">000280</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">000280</idno><idno type="wicri:Area/PubMed/Checkpoint">000447</idno><idno type="wicri:explorRef" wicri:stream="Checkpoint" wicri:step="PubMed">000447</idno><idno type="wicri:Area/Ncbi/Merge">003827</idno><idno type="wicri:Area/Ncbi/Curation">003827</idno><idno type="wicri:Area/Ncbi/Checkpoint">003827</idno><idno type="wicri:Area/Main/Merge">000560</idno><idno type="wicri:Area/Main/Curation">000560</idno><idno type="wicri:Area/Main/Exploration">000560</idno><idno type="wicri:Area/2020/Extraction">000560</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">In Silico Discovery of Candidate Drugs against Covid-19.</title><author><name sortKey="Cava, Claudia" sort="Cava, Claudia" uniqKey="Cava C" first="Claudia" last="Cava">Claudia Cava</name><affiliation wicri:level="3"><nlm:affiliation>Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090 Segrate-Milan, Milan, Italy.</nlm:affiliation><country xml:lang="fr">Italie</country><wicri:regionArea>Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090 Segrate-Milan, Milan</wicri:regionArea><placeName><settlement type="city">Milan</settlement><region nuts="2">Lombardie</region></placeName></affiliation></author><author><name sortKey="Bertoli, Gloria" sort="Bertoli, Gloria" uniqKey="Bertoli G" first="Gloria" last="Bertoli">Gloria Bertoli</name><affiliation wicri:level="3"><nlm:affiliation>Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090 Segrate-Milan, Milan, Italy.</nlm:affiliation><country xml:lang="fr">Italie</country><wicri:regionArea>Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090 Segrate-Milan, Milan</wicri:regionArea><placeName><settlement type="city">Milan</settlement><region nuts="2">Lombardie</region></placeName></affiliation></author><author><name sortKey="Castiglioni, Isabella" sort="Castiglioni, Isabella" uniqKey="Castiglioni I" first="Isabella" last="Castiglioni">Isabella Castiglioni</name><affiliation wicri:level="3"><nlm:affiliation>Department of Physics "Giuseppe Occhialini", University of Milan-Bicocca Piazza dell'Ateneo Nuovo, 1 - 20126, Milan, Italy.</nlm:affiliation><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Physics "Giuseppe Occhialini", University of Milan-Bicocca Piazza dell'Ateneo Nuovo, 1 - 20126, Milan</wicri:regionArea><placeName><settlement type="city">Milan</settlement><region nuts="2">Lombardie</region></placeName></affiliation></author></analytic><series><title level="j">Viruses</title><idno type="eISSN">1999-4915</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Anti-Inflammatory Agents (pharmacology)</term><term>Anti-Inflammatory Agents (therapeutic use)</term><term>Antiviral Agents (pharmacology)</term><term>Antiviral Agents (therapeutic use)</term><term>Betacoronavirus (drug effects)</term><term>Computational Biology</term><term>Computer Simulation</term><term>Coronavirus Infections (drug therapy)</term><term>Coronavirus Infections (virology)</term><term>Databases, Genetic</term><term>Drug Discovery</term><term>Gene Expression Profiling</term><term>Gene Regulatory Networks</term><term>Humans</term><term>Lung (enzymology)</term><term>Pandemics</term><term>Peptidyl-Dipeptidase A (genetics)</term><term>Peptidyl-Dipeptidase A (metabolism)</term><term>Pneumonia, Viral (drug therapy)</term><term>Pneumonia, Viral (virology)</term><term>Protein Interaction Mapping</term><term>Receptors, Virus (genetics)</term><term>Receptors, Virus (metabolism)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Analyse de profil d'expression de gènes</term><term>Anti-inflammatoires (pharmacologie)</term><term>Anti-inflammatoires (usage thérapeutique)</term><term>Antiviraux (pharmacologie)</term><term>Antiviraux (usage thérapeutique)</term><term>Bases de données génétiques</term><term>Biologie informatique</term><term>Cartographie d'interactions entre protéines</term><term>Découverte de médicament</term><term>Humains</term><term>Infections à coronavirus (traitement médicamenteux)</term><term>Infections à coronavirus (virologie)</term><term>Pandémies</term><term>Peptidyl-Dipeptidase A (génétique)</term><term>Peptidyl-Dipeptidase A (métabolisme)</term><term>Pneumopathie virale (traitement médicamenteux)</term><term>Pneumopathie virale (virologie)</term><term>Poumon (enzymologie)</term><term>Récepteurs viraux (génétique)</term><term>Récepteurs viraux (métabolisme)</term><term>Réseaux de régulation génique</term><term>Simulation numérique</term></keywords><keywords scheme="MESH" type="chemical" qualifier="genetics" xml:lang="en"><term>Peptidyl-Dipeptidase A</term><term>Receptors, Virus</term></keywords><keywords scheme="MESH" type="chemical" qualifier="metabolism" xml:lang="en"><term>Peptidyl-Dipeptidase A</term><term>Receptors, Virus</term></keywords><keywords scheme="MESH" type="chemical" qualifier="pharmacology" xml:lang="en"><term>Anti-Inflammatory Agents</term><term>Antiviral Agents</term></keywords><keywords scheme="MESH" type="chemical" qualifier="therapeutic use" xml:lang="en"><term>Anti-Inflammatory Agents</term><term>Antiviral Agents</term></keywords><keywords scheme="MESH" qualifier="drug effects" xml:lang="en"><term>Betacoronavirus</term></keywords><keywords scheme="MESH" qualifier="drug therapy" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="enzymologie" xml:lang="fr"><term>Poumon</term></keywords><keywords scheme="MESH" qualifier="enzymology" xml:lang="en"><term>Lung</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Peptidyl-Dipeptidase A</term><term>Récepteurs viraux</term></keywords><keywords scheme="MESH" qualifier="métabolisme" xml:lang="fr"><term>Peptidyl-Dipeptidase A</term><term>Récepteurs viraux</term></keywords><keywords scheme="MESH" qualifier="pharmacologie" xml:lang="fr"><term>Anti-inflammatoires</term><term>Antiviraux</term></keywords><keywords scheme="MESH" qualifier="traitement médicamenteux" xml:lang="fr"><term>Infections à coronavirus</term><term>Pneumopathie virale</term></keywords><keywords scheme="MESH" qualifier="usage thérapeutique" xml:lang="fr"><term>Anti-inflammatoires</term><term>Antiviraux</term></keywords><keywords scheme="MESH" qualifier="virologie" xml:lang="fr"><term>Infections à coronavirus</term><term>Pneumopathie virale</term></keywords><keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Computational Biology</term><term>Computer Simulation</term><term>Databases, Genetic</term><term>Drug Discovery</term><term>Gene Expression Profiling</term><term>Gene Regulatory Networks</term><term>Humans</term><term>Pandemics</term><term>Protein Interaction Mapping</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Analyse de profil d'expression de gènes</term><term>Bases de données génétiques</term><term>Biologie informatique</term><term>Cartographie d'interactions entre protéines</term><term>Découverte de médicament</term><term>Humains</term><term>Pandémies</term><term>Réseaux de régulation génique</term><term>Simulation numérique</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Previous studies reported that Angiotensin converting enzyme 2 (ACE2) is the main cell receptor of SARS-CoV and SARS-CoV-2. It plays a key role in the access of the virus into the cell to produce the final infection. In the present study we investigated in silico the basic mechanism of <i>ACE2</i> in the lung and provided evidences for new potentially effective drugs for Covid-19. Specifically, we used the gene expression profiles from public datasets including The Cancer Genome Atlas, Gene Expression Omnibus and Genotype-Tissue Expression, Gene Ontology and pathway enrichment analysis to investigate the main functions of <i>ACE2</i>-correlated genes. We constructed a protein-protein interaction network containing the genes co-expressed with <i>ACE2</i>. Finally, we focused on the genes in the network that are already associated with known drugs and evaluated their role for a potential treatment of Covid-19. Our results demonstrate that the genes correlated with <i>ACE2</i> are mainly enriched in the sterol biosynthetic process, Aryldialkylphosphatase activity, adenosylhomocysteinase activity, trialkylsulfonium hydrolase activity, acetate-CoA and CoA ligase activity. We identified a network of 193 genes, 222 interactions and 36 potential drugs that could have a crucial role. Among possible interesting drugs for Covid-19 treatment, we found Nimesulide, Fluticasone Propionate, Thiabendazole, Photofrin, Didanosine and Flutamide.</div></front></TEI><affiliations><list><country><li>Italie</li></country><region><li>Lombardie</li></region><settlement><li>Milan</li></settlement></list><tree><country name="Italie"><region name="Lombardie"><name sortKey="Cava, Claudia" sort="Cava, Claudia" uniqKey="Cava C" first="Claudia" last="Cava">Claudia Cava</name></region><name sortKey="Bertoli, Gloria" sort="Bertoli, Gloria" uniqKey="Bertoli G" first="Gloria" last="Bertoli">Gloria Bertoli</name><name sortKey="Castiglioni, Isabella" sort="Castiglioni, Isabella" uniqKey="Castiglioni I" first="Isabella" last="Castiglioni">Isabella Castiglioni</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Sante/explor/SrasV1/Data/2020/Analysis
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000560 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/2020/Analysis/biblio.hfd -nk 000560 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Sante
|area= SrasV1
|flux= 2020
|étape= Analysis
|type= RBID
|clé= pubmed:32268515
|texte= In Silico Discovery of Candidate Drugs against Covid-19.
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/2020/Analysis/RBID.i -Sk "pubmed:32268515" \
| HfdSelect -Kh $EXPLOR_AREA/Data/2020/Analysis/biblio.hfd \
| NlmPubMed2Wicri -a SrasV1
| This area was generated with Dilib version V0.6.33. |  |