In Silico Generation of Peptides by Replica Exchange Monte Carlo: Docking-Based Optimization of Maltose-Binding-Protein Ligands
Short peptides can be designed in silico and synthesized through automated techniques, making them advantageous and versatile protein binders. A number of docking-based algorithms allow for a computational screening of peptides as binders. Here we developed ex-novo peptides targeting the maltose sit...
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| Veröffentlicht in: | PloS one 2015-08, Vol.10 (8), p.e0133571-e0133571 |
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| creator | Russo, Anna Scognamiglio, Pasqualina Liana Hong Enriquez, Rolando Pablo Santambrogio, Carlo Grandori, Rita Marasco, Daniela Giordano, Antonio Scoles, Giacinto Fortuna, Sara |
| description | Short peptides can be designed in silico and synthesized through automated techniques, making them advantageous and versatile protein binders. A number of docking-based algorithms allow for a computational screening of peptides as binders. Here we developed ex-novo peptides targeting the maltose site of the Maltose Binding Protein, the prototypical system for the study of protein ligand recognition. We used a Monte Carlo based protocol, to computationally evolve a set of octapeptides starting from a polialanine sequence. We screened in silico the candidate peptides and characterized their binding abilities by surface plasmon resonance, fluorescence and electrospray ionization mass spectrometry assays. These experiments showed the designed binders to recognize their target with micromolar affinity. We finally discuss the obtained results in the light of further improvement in the ex-novo optimization of peptide based binders. |
| doi_str_mv | 10.1371/journal.pone.0133571 |
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A number of docking-based algorithms allow for a computational screening of peptides as binders. Here we developed ex-novo peptides targeting the maltose site of the Maltose Binding Protein, the prototypical system for the study of protein ligand recognition. We used a Monte Carlo based protocol, to computationally evolve a set of octapeptides starting from a polialanine sequence. We screened in silico the candidate peptides and characterized their binding abilities by surface plasmon resonance, fluorescence and electrospray ionization mass spectrometry assays. These experiments showed the designed binders to recognize their target with micromolar affinity. We finally discuss the obtained results in the light of further improvement in the ex-novo optimization of peptide based binders.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0133571</identifier><identifier>PMID: 26252476</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Amino Acid Sequence ; Binders ; Biotechnology ; Computer applications ; Docking ; Fluorescence ; Genetic algorithms ; Immobilized Proteins - metabolism ; Ionization ; Kinetics ; Ligands ; Maltose ; Maltose-binding protein ; Maltose-Binding Proteins - chemistry ; Maltose-Binding Proteins - metabolism ; Mass spectrometry ; Mass spectroscopy ; Medical research ; Molecular biology ; Molecular Docking Simulation ; Molecular Sequence Data ; Monte Carlo Method ; Octapeptides ; Optimization ; Peptides ; Peptides - chemistry ; Peptides - metabolism ; Pharmacy ; Protein Binding ; Proteins ; Spectrometry, Mass, Electrospray Ionization ; Surface Plasmon Resonance ; Target recognition ; Thermodynamics ; Tryptophan - metabolism</subject><ispartof>PloS one, 2015-08, Vol.10 (8), p.e0133571-e0133571</ispartof><rights>2015 Russo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2015 Russo et al 2015 Russo et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c526t-b709d333aa20d74ba2c7d21aaf4d3504bfc3421a619b3fa6494926b9178fe1113</citedby><cites>FETCH-LOGICAL-c526t-b709d333aa20d74ba2c7d21aaf4d3504bfc3421a619b3fa6494926b9178fe1113</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4529233/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4529233/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26252476$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Zhang, Yang</contributor><creatorcontrib>Russo, Anna</creatorcontrib><creatorcontrib>Scognamiglio, Pasqualina Liana</creatorcontrib><creatorcontrib>Hong Enriquez, Rolando Pablo</creatorcontrib><creatorcontrib>Santambrogio, Carlo</creatorcontrib><creatorcontrib>Grandori, Rita</creatorcontrib><creatorcontrib>Marasco, Daniela</creatorcontrib><creatorcontrib>Giordano, Antonio</creatorcontrib><creatorcontrib>Scoles, Giacinto</creatorcontrib><creatorcontrib>Fortuna, Sara</creatorcontrib><title>In Silico Generation of Peptides by Replica Exchange Monte Carlo: Docking-Based Optimization of Maltose-Binding-Protein Ligands</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Short peptides can be designed in silico and synthesized through automated techniques, making them advantageous and versatile protein binders. A number of docking-based algorithms allow for a computational screening of peptides as binders. Here we developed ex-novo peptides targeting the maltose site of the Maltose Binding Protein, the prototypical system for the study of protein ligand recognition. We used a Monte Carlo based protocol, to computationally evolve a set of octapeptides starting from a polialanine sequence. We screened in silico the candidate peptides and characterized their binding abilities by surface plasmon resonance, fluorescence and electrospray ionization mass spectrometry assays. These experiments showed the designed binders to recognize their target with micromolar affinity. We finally discuss the obtained results in the light of further improvement in the ex-novo optimization of peptide based binders.</description><subject>Algorithms</subject><subject>Amino Acid Sequence</subject><subject>Binders</subject><subject>Biotechnology</subject><subject>Computer applications</subject><subject>Docking</subject><subject>Fluorescence</subject><subject>Genetic algorithms</subject><subject>Immobilized Proteins - metabolism</subject><subject>Ionization</subject><subject>Kinetics</subject><subject>Ligands</subject><subject>Maltose</subject><subject>Maltose-binding protein</subject><subject>Maltose-Binding Proteins - chemistry</subject><subject>Maltose-Binding Proteins - metabolism</subject><subject>Mass spectrometry</subject><subject>Mass spectroscopy</subject><subject>Medical research</subject><subject>Molecular biology</subject><subject>Molecular Docking Simulation</subject><subject>Molecular Sequence Data</subject><subject>Monte Carlo Method</subject><subject>Octapeptides</subject><subject>Optimization</subject><subject>Peptides</subject><subject>Peptides - chemistry</subject><subject>Peptides - metabolism</subject><subject>Pharmacy</subject><subject>Protein Binding</subject><subject>Proteins</subject><subject>Spectrometry, Mass, Electrospray Ionization</subject><subject>Surface Plasmon Resonance</subject><subject>Target recognition</subject><subject>Thermodynamics</subject><subject>Tryptophan - metabolism</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNptkktvEzEUhUcIREvhHyCwxIbNBL_GzrBAoqGUSKla8Vhbd2xP6jCxB3tStWz46zjNNGoRkiW_zvl8r3WK4iXBE8IkebcKm-ihm_TB2wkmjFWSPCoOSc1oKShmj--tD4pnKa0wrthUiKfFARW0olyKw-LP3KNvrnM6oFPrbYTBBY9Ciy5sPzhjE2pu0FfbZwWgk2t9CX5p0Vnwg0UziF14jz4F_dP5ZXkMyRp0nm1r93vPOYNuCMmWx86breoihsE6jxZuCd6k58WTFrpkX4zzUfHj88n32ZdycX46n31clLqiYigbiWvDGAOg2EjeANXSUALQcsMqzJtWM573gtQNa0HwmtdUNDWR09YSQthR8XrH7buQ1Ph3SRGJKSWMcp4V853CBFipPro1xBsVwKnbgxCXCuLgdGcVZUxWrRCGToHblkwpCFlLzQHn0eLM-jC-tmnW1mjrhwjdA-jDG-8u1TJcKV7ROtMz4O0IiOHXxqZBrV3StuvA27C5rTsXXXFKs_TNP9L_d8d3Kh1DStG2-2IIVts83bnUNk9qzFO2vbrfyN50FyD2F9rjyNA</recordid><startdate>20150807</startdate><enddate>20150807</enddate><creator>Russo, Anna</creator><creator>Scognamiglio, Pasqualina Liana</creator><creator>Hong Enriquez, Rolando Pablo</creator><creator>Santambrogio, Carlo</creator><creator>Grandori, Rita</creator><creator>Marasco, Daniela</creator><creator>Giordano, Antonio</creator><creator>Scoles, Giacinto</creator><creator>Fortuna, Sara</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</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>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20150807</creationdate><title>In Silico Generation of Peptides by Replica Exchange Monte Carlo: Docking-Based Optimization of Maltose-Binding-Protein Ligands</title><author>Russo, Anna ; Scognamiglio, Pasqualina Liana ; Hong Enriquez, Rolando Pablo ; Santambrogio, Carlo ; Grandori, Rita ; Marasco, Daniela ; Giordano, Antonio ; Scoles, Giacinto ; Fortuna, Sara</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c526t-b709d333aa20d74ba2c7d21aaf4d3504bfc3421a619b3fa6494926b9178fe1113</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Algorithms</topic><topic>Amino Acid Sequence</topic><topic>Binders</topic><topic>Biotechnology</topic><topic>Computer applications</topic><topic>Docking</topic><topic>Fluorescence</topic><topic>Genetic algorithms</topic><topic>Immobilized Proteins - 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| subjects | Algorithms Amino Acid Sequence Binders Biotechnology Computer applications Docking Fluorescence Genetic algorithms Immobilized Proteins - metabolism Ionization Kinetics Ligands Maltose Maltose-binding protein Maltose-Binding Proteins - chemistry Maltose-Binding Proteins - metabolism Mass spectrometry Mass spectroscopy Medical research Molecular biology Molecular Docking Simulation Molecular Sequence Data Monte Carlo Method Octapeptides Optimization Peptides Peptides - chemistry Peptides - metabolism Pharmacy Protein Binding Proteins Spectrometry, Mass, Electrospray Ionization Surface Plasmon Resonance Target recognition Thermodynamics Tryptophan - metabolism |
| title | In Silico Generation of Peptides by Replica Exchange Monte Carlo: Docking-Based Optimization of Maltose-Binding-Protein Ligands |
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