Peptide-Protein Interaction Studies of Antimicrobial Peptides Targeting Middle East Respiratory Syndrome Coronavirus Spike Protein: An In Silico Approach.
Identifieur interne : 000469 ( PubMed/Curation ); précédent : 000468; suivant : 000470Peptide-Protein Interaction Studies of Antimicrobial Peptides Targeting Middle East Respiratory Syndrome Coronavirus Spike Protein: An In Silico Approach.
Auteurs : Sabeena Mustafa [Arabie saoudite] ; Hanan Balkhy [Arabie saoudite] ; Musa Gabere [Arabie saoudite]Source :
- Advances in bioinformatics [ 1687-8027 ] ; 2019.
Abstract
There is no effective therapeutic or vaccine for Middle East Respiratory Syndrome and this study attempts to find therapy using peptide by establishing a basis for the peptide-protein interactions through in silico docking studies for the spike protein of MERS-CoV. The antimicrobial peptides (AMPs) were retrieved from the antimicrobial peptide database (APD3) and shortlisted based on certain important physicochemical properties. The binding mode of the shortlisted peptides was measured based on the number of clusters which forms in a protein-peptide docking using Piper. As a result, we identified a list of putative AMPs which binds to the spike protein of MERS-CoV, which may be crucial in providing the inhibitory action. It is observed that seven putative peptides have good binding score based on cluster size cutoff of 208. We conclude that seven peptides, namely, AP00225, AP00180, AP00549, AP00744, AP00729, AP00764, and AP00223, could possibly have binding with the active site of the MERS-CoV spike protein. These seven AMPs could serve as a therapeutic option for MERS and enhance its treatment outcome.
DOI: 10.1155/2019/6815105
PubMed: 31354813
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Spike Protein: An In Silico Approach.</title><author><name sortKey="Mustafa, Sabeena" sort="Mustafa, Sabeena" uniqKey="Mustafa S" first="Sabeena" last="Mustafa">Sabeena Mustafa</name><affiliation wicri:level="1"><nlm:affiliation>Department of Biostatistics and Bioinformatics, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia.</nlm:affiliation><country xml:lang="fr">Arabie saoudite</country><wicri:regionArea>Department of Biostatistics and Bioinformatics, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Riyadh</wicri:regionArea></affiliation></author><author><name sortKey="Balkhy, Hanan" sort="Balkhy, Hanan" uniqKey="Balkhy H" first="Hanan" last="Balkhy">Hanan Balkhy</name><affiliation wicri:level="1"><nlm:affiliation>Infection Prevention and Control Department at the Ministry of National Guard, Department of Infectious Diseases, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia.</nlm:affiliation><country xml:lang="fr">Arabie saoudite</country><wicri:regionArea>Infection Prevention and Control Department at the Ministry of National Guard, Department of Infectious Diseases, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Riyadh</wicri:regionArea></affiliation></author><author><name sortKey="Gabere, Musa" sort="Gabere, Musa" uniqKey="Gabere M" first="Musa" last="Gabere">Musa Gabere</name><affiliation wicri:level="1"><nlm:affiliation>Department of Biostatistics and Bioinformatics, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia.</nlm:affiliation><country xml:lang="fr">Arabie saoudite</country><wicri:regionArea>Department of Biostatistics and Bioinformatics, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Riyadh</wicri:regionArea></affiliation></author></analytic><series><title level="j">Advances in bioinformatics</title><idno type="ISSN">1687-8027</idno><imprint><date when="2019" type="published">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">There is no effective therapeutic or vaccine for Middle East Respiratory Syndrome and this study attempts to find therapy using peptide by establishing a basis for the peptide-protein interactions through in silico docking studies for the spike protein of MERS-CoV. The antimicrobial peptides (AMPs) were retrieved from the antimicrobial peptide database (APD3) and shortlisted based on certain important physicochemical properties. The binding mode of the shortlisted peptides was measured based on the number of clusters which forms in a protein-peptide docking using Piper. As a result, we identified a list of putative AMPs which binds to the spike protein of MERS-CoV, which may be crucial in providing the inhibitory action. It is observed that seven putative peptides have good binding score based on cluster size cutoff of 208. We conclude that seven peptides, namely, AP00225, AP00180, AP00549, AP00744, AP00729, AP00764, and AP00223, could possibly have binding with the active site of the MERS-CoV spike protein. These seven AMPs could serve as a therapeutic option for MERS and enhance its treatment outcome.</div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">31354813</PMID><DateRevised><Year>2020</Year><Month>02</Month><Day>25</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Print">1687-8027</ISSN><JournalIssue CitedMedium="Print"><Volume>2019</Volume><PubDate><Year>2019</Year></PubDate></JournalIssue><Title>Advances in bioinformatics</Title><ISOAbbreviation>Adv Bioinformatics</ISOAbbreviation></Journal><ArticleTitle>Peptide-Protein Interaction Studies of Antimicrobial Peptides Targeting Middle East Respiratory Syndrome Coronavirus Spike Protein: An In Silico Approach.</ArticleTitle><Pagination><MedlinePgn>6815105</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1155/2019/6815105</ELocationID><Abstract><AbstractText>There is no effective therapeutic or vaccine for Middle East Respiratory Syndrome and this study attempts to find therapy using peptide by establishing a basis for the peptide-protein interactions through in silico docking studies for the spike protein of MERS-CoV. The antimicrobial peptides (AMPs) were retrieved from the antimicrobial peptide database (APD3) and shortlisted based on certain important physicochemical properties. The binding mode of the shortlisted peptides was measured based on the number of clusters which forms in a protein-peptide docking using Piper. As a result, we identified a list of putative AMPs which binds to the spike protein of MERS-CoV, which may be crucial in providing the inhibitory action. It is observed that seven putative peptides have good binding score based on cluster size cutoff of 208. We conclude that seven peptides, namely, AP00225, AP00180, AP00549, AP00744, AP00729, AP00764, and AP00223, could possibly have binding with the active site of the MERS-CoV spike protein. 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