Computational Design of Highly Selective Antimicrobial Peptides
We have created a structure-selectivity database (AMPad) of frog-derived, helical antimicrobial peptides (AMPs), in which the selectivity was determined as a therapeutic index (TI), and then used the novel concept of sequence moments to study the lengthwise asymmetry of physicochemical peptide prope...
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| Veröffentlicht in: | Journal of chemical information and modeling 2009-12, Vol.49 (12), p.2873-2882 |
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| container_title | Journal of chemical information and modeling |
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| creator | Juretić, Davor Vukičević, Damir Ilić, Nada Antcheva, Nikolinka Tossi, Alessandro |
| description | We have created a structure-selectivity database (AMPad) of frog-derived, helical antimicrobial peptides (AMPs), in which the selectivity was determined as a therapeutic index (TI), and then used the novel concept of sequence moments to study the lengthwise asymmetry of physicochemical peptide properties. We found that the cosine of the angle between two sequence moments obtained with different hydrophobicity scales, defined as the D-descriptor, identifies highly selective peptide antibiotics. We could then use this descriptor to predict TI changes after point mutations in known AMPs, and to aid the prediction of TI for de novo designed AMPs. In combination with an amino acid selectivity index, a motif regularity index and other statistical rules extracted from AMPad, the D-descriptor enabled construction of the AMP-Designer algorithm. A 23 residue, glycine-rich, peptide suggested by the algorithm was synthesized and the activity and selectivity tested. This peptide, adepantin 1, is less than 50% identical to any other AMP, has a potent antibacterial activity against the reference organism, E. coli, and has a significantly greater selectivity (TI > 200) than the best AMP present in the AMPad database (TI = 125). |
| doi_str_mv | 10.1021/ci900327a |
| format | Article |
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We found that the cosine of the angle between two sequence moments obtained with different hydrophobicity scales, defined as the D-descriptor, identifies highly selective peptide antibiotics. We could then use this descriptor to predict TI changes after point mutations in known AMPs, and to aid the prediction of TI for de novo designed AMPs. In combination with an amino acid selectivity index, a motif regularity index and other statistical rules extracted from AMPad, the D-descriptor enabled construction of the AMP-Designer algorithm. A 23 residue, glycine-rich, peptide suggested by the algorithm was synthesized and the activity and selectivity tested. This peptide, adepantin 1, is less than 50% identical to any other AMP, has a potent antibacterial activity against the reference organism, E. coli, and has a significantly greater selectivity (TI > 200) than the best AMP present in the AMPad database (TI = 125).</description><identifier>ISSN: 1549-9596</identifier><identifier>EISSN: 1549-960X</identifier><identifier>DOI: 10.1021/ci900327a</identifier><identifier>PMID: 19947578</identifier><language>eng</language><publisher>United States: American Chemical Society</publisher><subject>Algorithms ; Amino Acid Motifs ; Amino Acid Sequence ; Amino acids ; Animals ; Antibiotics ; Antimicrobial Cationic Peptides - chemical synthesis ; Antimicrobial Cationic Peptides - chemistry ; Antimicrobial Cationic Peptides - pharmacology ; Antimicrobial Cationic Peptides - toxicity ; Bioinformatics ; Computer Simulation ; Data Mining ; Databases, Protein ; Drug Design ; Erythrocytes - drug effects ; Escherichia coli - drug effects ; Hemolysis - drug effects ; Humans ; Microbial Sensitivity Tests ; Models, Molecular ; Molecular Sequence Data ; Mutation ; Peptides ; Protein Structure, Secondary ; Reproducibility of Results ; Structure-Activity Relationship ; Substrate Specificity</subject><ispartof>Journal of chemical information and modeling, 2009-12, Vol.49 (12), p.2873-2882</ispartof><rights>Copyright © 2009 American Chemical Society</rights><rights>Copyright American Chemical Society Dec 28, 2009</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a442t-1b408bf8095431f8d5a80294d3aaa449689d4e694a840a4883c485257654a4853</citedby><cites>FETCH-LOGICAL-a442t-1b408bf8095431f8d5a80294d3aaa449689d4e694a840a4883c485257654a4853</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://pubs.acs.org/doi/pdf/10.1021/ci900327a$$EPDF$$P50$$Gacs$$H</linktopdf><linktohtml>$$Uhttps://pubs.acs.org/doi/10.1021/ci900327a$$EHTML$$P50$$Gacs$$H</linktohtml><link.rule.ids>314,776,780,2752,27053,27901,27902,56713,56763</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/19947578$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Juretić, Davor</creatorcontrib><creatorcontrib>Vukičević, Damir</creatorcontrib><creatorcontrib>Ilić, Nada</creatorcontrib><creatorcontrib>Antcheva, Nikolinka</creatorcontrib><creatorcontrib>Tossi, Alessandro</creatorcontrib><title>Computational Design of Highly Selective Antimicrobial Peptides</title><title>Journal of chemical information and modeling</title><addtitle>J. Chem. Inf. Model</addtitle><description>We have created a structure-selectivity database (AMPad) of frog-derived, helical antimicrobial peptides (AMPs), in which the selectivity was determined as a therapeutic index (TI), and then used the novel concept of sequence moments to study the lengthwise asymmetry of physicochemical peptide properties. We found that the cosine of the angle between two sequence moments obtained with different hydrophobicity scales, defined as the D-descriptor, identifies highly selective peptide antibiotics. We could then use this descriptor to predict TI changes after point mutations in known AMPs, and to aid the prediction of TI for de novo designed AMPs. In combination with an amino acid selectivity index, a motif regularity index and other statistical rules extracted from AMPad, the D-descriptor enabled construction of the AMP-Designer algorithm. A 23 residue, glycine-rich, peptide suggested by the algorithm was synthesized and the activity and selectivity tested. This peptide, adepantin 1, is less than 50% identical to any other AMP, has a potent antibacterial activity against the reference organism, E. coli, and has a significantly greater selectivity (TI > 200) than the best AMP present in the AMPad database (TI = 125).</description><subject>Algorithms</subject><subject>Amino Acid Motifs</subject><subject>Amino Acid Sequence</subject><subject>Amino acids</subject><subject>Animals</subject><subject>Antibiotics</subject><subject>Antimicrobial Cationic Peptides - chemical synthesis</subject><subject>Antimicrobial Cationic Peptides - chemistry</subject><subject>Antimicrobial Cationic Peptides - pharmacology</subject><subject>Antimicrobial Cationic Peptides - toxicity</subject><subject>Bioinformatics</subject><subject>Computer Simulation</subject><subject>Data Mining</subject><subject>Databases, Protein</subject><subject>Drug Design</subject><subject>Erythrocytes - drug effects</subject><subject>Escherichia coli - drug effects</subject><subject>Hemolysis - drug effects</subject><subject>Humans</subject><subject>Microbial Sensitivity Tests</subject><subject>Models, Molecular</subject><subject>Molecular Sequence Data</subject><subject>Mutation</subject><subject>Peptides</subject><subject>Protein Structure, Secondary</subject><subject>Reproducibility of Results</subject><subject>Structure-Activity Relationship</subject><subject>Substrate Specificity</subject><issn>1549-9596</issn><issn>1549-960X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpl0F1LwzAYBeAgipvTC_-AFEHEi2qSvkmTKxn1Y8JAQQXvQtqmM6NfNq2wf29k04FeJYGHE85B6JjgS4IpucqsxDiisd5BY8JAhpLjt92fO5N8hA6cW3oTSU730YhICTGLxRhdJ03VDr3ubVPrMrgxzi7qoCmCmV28l6vg2ZQm6-2nCaZ1byubdU1qPXwybW9z4w7RXqFLZ4425wS93t2-JLNw_nj_kEznoQagfUhSwCItBJYMIlKInGmBqYQ80toLyYXMwXAJWgDWIESUgWCUxZyBf7Jogs7XuW3XfAzG9aqyLjNlqWvTDE7FEVACvq-Xp3_kshk6X84pSjgFL8GjizXyfZzrTKHazla6WymC1fem6ndTb082gUNamXwrNyN6cLYGOnPbz_4HfQHGEHq-</recordid><startdate>20091228</startdate><enddate>20091228</enddate><creator>Juretić, Davor</creator><creator>Vukičević, Damir</creator><creator>Ilić, Nada</creator><creator>Antcheva, Nikolinka</creator><creator>Tossi, Alessandro</creator><general>American Chemical Society</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SR</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7X8</scope></search><sort><creationdate>20091228</creationdate><title>Computational Design of Highly Selective Antimicrobial Peptides</title><author>Juretić, Davor ; Vukičević, Damir ; Ilić, Nada ; Antcheva, Nikolinka ; Tossi, Alessandro</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a442t-1b408bf8095431f8d5a80294d3aaa449689d4e694a840a4883c485257654a4853</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Algorithms</topic><topic>Amino Acid Motifs</topic><topic>Amino Acid Sequence</topic><topic>Amino acids</topic><topic>Animals</topic><topic>Antibiotics</topic><topic>Antimicrobial Cationic Peptides - chemical synthesis</topic><topic>Antimicrobial Cationic Peptides - chemistry</topic><topic>Antimicrobial Cationic Peptides - pharmacology</topic><topic>Antimicrobial Cationic Peptides - toxicity</topic><topic>Bioinformatics</topic><topic>Computer Simulation</topic><topic>Data Mining</topic><topic>Databases, Protein</topic><topic>Drug Design</topic><topic>Erythrocytes - drug effects</topic><topic>Escherichia coli - drug effects</topic><topic>Hemolysis - drug effects</topic><topic>Humans</topic><topic>Microbial Sensitivity Tests</topic><topic>Models, Molecular</topic><topic>Molecular Sequence Data</topic><topic>Mutation</topic><topic>Peptides</topic><topic>Protein Structure, Secondary</topic><topic>Reproducibility of Results</topic><topic>Structure-Activity Relationship</topic><topic>Substrate Specificity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Juretić, Davor</creatorcontrib><creatorcontrib>Vukičević, Damir</creatorcontrib><creatorcontrib>Ilić, Nada</creatorcontrib><creatorcontrib>Antcheva, Nikolinka</creatorcontrib><creatorcontrib>Tossi, Alessandro</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of chemical information and modeling</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Juretić, Davor</au><au>Vukičević, Damir</au><au>Ilić, Nada</au><au>Antcheva, Nikolinka</au><au>Tossi, Alessandro</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Computational Design of Highly Selective Antimicrobial Peptides</atitle><jtitle>Journal of chemical information and modeling</jtitle><addtitle>J. Chem. Inf. Model</addtitle><date>2009-12-28</date><risdate>2009</risdate><volume>49</volume><issue>12</issue><spage>2873</spage><epage>2882</epage><pages>2873-2882</pages><issn>1549-9596</issn><eissn>1549-960X</eissn><abstract>We have created a structure-selectivity database (AMPad) of frog-derived, helical antimicrobial peptides (AMPs), in which the selectivity was determined as a therapeutic index (TI), and then used the novel concept of sequence moments to study the lengthwise asymmetry of physicochemical peptide properties. We found that the cosine of the angle between two sequence moments obtained with different hydrophobicity scales, defined as the D-descriptor, identifies highly selective peptide antibiotics. We could then use this descriptor to predict TI changes after point mutations in known AMPs, and to aid the prediction of TI for de novo designed AMPs. 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| subjects | Algorithms Amino Acid Motifs Amino Acid Sequence Amino acids Animals Antibiotics Antimicrobial Cationic Peptides - chemical synthesis Antimicrobial Cationic Peptides - chemistry Antimicrobial Cationic Peptides - pharmacology Antimicrobial Cationic Peptides - toxicity Bioinformatics Computer Simulation Data Mining Databases, Protein Drug Design Erythrocytes - drug effects Escherichia coli - drug effects Hemolysis - drug effects Humans Microbial Sensitivity Tests Models, Molecular Molecular Sequence Data Mutation Peptides Protein Structure, Secondary Reproducibility of Results Structure-Activity Relationship Substrate Specificity |
| title | Computational Design of Highly Selective Antimicrobial Peptides |
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