Accelerating molecular discovery through data and physical sciences: Applications to peptide-membrane interactions
Simulation and data analysis have evolved into powerful methods for discovering and understanding molecular modes of action and designing new compounds to exploit these modes. The combination provides a strong impetus to create and exploit new tools and techniques at the interfaces between physics,...
Gespeichert in:
Veröffentlicht in: | The Journal of chemical physics 2018-06, Vol.148 (24), p.241744-241744 |
---|---|
Hauptverfasser: | , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 241744 |
---|---|
container_issue | 24 |
container_start_page | 241744 |
container_title | The Journal of chemical physics |
container_volume | 148 |
creator | Cipcigan, Flaviu Carrieri, Anna Paola Pyzer-Knapp, Edward O. Krishna, Ritesh Hsiao, Ya-Wen Winn, Martyn Ryadnov, Maxim G. Edge, Colin Martyna, Glenn Crain, Jason |
description | Simulation and data analysis have evolved into powerful methods for discovering and understanding molecular modes of action and designing new compounds to exploit these modes. The combination provides a strong impetus to create and exploit new tools and techniques at the interfaces between physics, biology, and data science as a pathway to new scientific insight and accelerated discovery. In this context, we explore the rational design of novel antimicrobial peptides (short protein sequences exhibiting broad activity against multiple species of bacteria). We show how datasets can be harvested to reveal features which inform new design concepts. We introduce new analysis and visualization tools: a graphical representation of the k-mer spectrum as a fundamental property encoded in antimicrobial peptide databases and a data-driven representation to illustrate membrane binding and permeation of helical peptides. |
doi_str_mv | 10.1063/1.5027261 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1063_1_5027261</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2088311087</sourcerecordid><originalsourceid>FETCH-LOGICAL-c383t-a4c719f6301d03866eb15aa9c0c90cda9aed347af71a5bffda73aa9bc4ba8ffa3</originalsourceid><addsrcrecordid>eNp90U1LxDAQBuAgirt-HPwDEvCiQjVpdtPW2yJ-geBFz2WaTNwubVOTdGH_vdFdFQQ9BSYPk8k7hBxxdsGZFJf8YsrSLJV8i4w5y4skkwXbJmPGUp4UkskR2fN-wRjjWTrZJaO0iFWR5mPiZkphgw5C3b3S1jaohgYc1bVXdoluRcPc2eF1TjUEoNBp2s9XvlbQUK9q7BT6Kzrr-yaWQm07T4OlPfah1pi02FYOOqR1F-Ib6hMckB0DjcfDzblPXm5vnq_vk8enu4fr2WOiRC5CAhOV8cJIwbhmIpcSKz4FKBRTBVMaCkAtJhmYjMO0MkZDJuJ1pSYV5MaA2Cen6769s28D-lC28VPYNHEgO_gyjdHF0NKpjPTkF13YwXVxuqjyXPCYahbV2VopZ713aMre1S24VclZ-bGIkpebRUR7vOk4VC3qb_mVfATnaxBTDJ_J_dvtT7y07geWvTbiHY60oYg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2088311087</pqid></control><display><type>article</type><title>Accelerating molecular discovery through data and physical sciences: Applications to peptide-membrane interactions</title><source>AIP Journals Complete</source><source>Alma/SFX Local Collection</source><creator>Cipcigan, Flaviu ; Carrieri, Anna Paola ; Pyzer-Knapp, Edward O. ; Krishna, Ritesh ; Hsiao, Ya-Wen ; Winn, Martyn ; Ryadnov, Maxim G. ; Edge, Colin ; Martyna, Glenn ; Crain, Jason</creator><creatorcontrib>Cipcigan, Flaviu ; Carrieri, Anna Paola ; Pyzer-Knapp, Edward O. ; Krishna, Ritesh ; Hsiao, Ya-Wen ; Winn, Martyn ; Ryadnov, Maxim G. ; Edge, Colin ; Martyna, Glenn ; Crain, Jason</creatorcontrib><description>Simulation and data analysis have evolved into powerful methods for discovering and understanding molecular modes of action and designing new compounds to exploit these modes. The combination provides a strong impetus to create and exploit new tools and techniques at the interfaces between physics, biology, and data science as a pathway to new scientific insight and accelerated discovery. In this context, we explore the rational design of novel antimicrobial peptides (short protein sequences exhibiting broad activity against multiple species of bacteria). We show how datasets can be harvested to reveal features which inform new design concepts. We introduce new analysis and visualization tools: a graphical representation of the k-mer spectrum as a fundamental property encoded in antimicrobial peptide databases and a data-driven representation to illustrate membrane binding and permeation of helical peptides.</description><identifier>ISSN: 0021-9606</identifier><identifier>EISSN: 1089-7690</identifier><identifier>DOI: 10.1063/1.5027261</identifier><identifier>PMID: 29960328</identifier><identifier>CODEN: JCPSA6</identifier><language>eng</language><publisher>United States: American Institute of Physics</publisher><subject>Antiinfectives and antibacterials ; Coding ; Data analysis ; Graphical representations ; Peptides ; Physical sciences ; Proteins</subject><ispartof>The Journal of chemical physics, 2018-06, Vol.148 (24), p.241744-241744</ispartof><rights>Author(s)</rights><rights>2018 Author(s). Published by AIP Publishing.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c383t-a4c719f6301d03866eb15aa9c0c90cda9aed347af71a5bffda73aa9bc4ba8ffa3</citedby><cites>FETCH-LOGICAL-c383t-a4c719f6301d03866eb15aa9c0c90cda9aed347af71a5bffda73aa9bc4ba8ffa3</cites><orcidid>0000-0002-5015-1443 ; 0000-0002-4964-7759 ; 0000000250151443 ; 0000000249647759</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://pubs.aip.org/jcp/article-lookup/doi/10.1063/1.5027261$$EHTML$$P50$$Gscitation$$H</linktohtml><link.rule.ids>314,776,780,790,4498,27901,27902,76126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29960328$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Cipcigan, Flaviu</creatorcontrib><creatorcontrib>Carrieri, Anna Paola</creatorcontrib><creatorcontrib>Pyzer-Knapp, Edward O.</creatorcontrib><creatorcontrib>Krishna, Ritesh</creatorcontrib><creatorcontrib>Hsiao, Ya-Wen</creatorcontrib><creatorcontrib>Winn, Martyn</creatorcontrib><creatorcontrib>Ryadnov, Maxim G.</creatorcontrib><creatorcontrib>Edge, Colin</creatorcontrib><creatorcontrib>Martyna, Glenn</creatorcontrib><creatorcontrib>Crain, Jason</creatorcontrib><title>Accelerating molecular discovery through data and physical sciences: Applications to peptide-membrane interactions</title><title>The Journal of chemical physics</title><addtitle>J Chem Phys</addtitle><description>Simulation and data analysis have evolved into powerful methods for discovering and understanding molecular modes of action and designing new compounds to exploit these modes. The combination provides a strong impetus to create and exploit new tools and techniques at the interfaces between physics, biology, and data science as a pathway to new scientific insight and accelerated discovery. In this context, we explore the rational design of novel antimicrobial peptides (short protein sequences exhibiting broad activity against multiple species of bacteria). We show how datasets can be harvested to reveal features which inform new design concepts. We introduce new analysis and visualization tools: a graphical representation of the k-mer spectrum as a fundamental property encoded in antimicrobial peptide databases and a data-driven representation to illustrate membrane binding and permeation of helical peptides.</description><subject>Antiinfectives and antibacterials</subject><subject>Coding</subject><subject>Data analysis</subject><subject>Graphical representations</subject><subject>Peptides</subject><subject>Physical sciences</subject><subject>Proteins</subject><issn>0021-9606</issn><issn>1089-7690</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp90U1LxDAQBuAgirt-HPwDEvCiQjVpdtPW2yJ-geBFz2WaTNwubVOTdGH_vdFdFQQ9BSYPk8k7hBxxdsGZFJf8YsrSLJV8i4w5y4skkwXbJmPGUp4UkskR2fN-wRjjWTrZJaO0iFWR5mPiZkphgw5C3b3S1jaohgYc1bVXdoluRcPc2eF1TjUEoNBp2s9XvlbQUK9q7BT6Kzrr-yaWQm07T4OlPfah1pi02FYOOqR1F-Ib6hMckB0DjcfDzblPXm5vnq_vk8enu4fr2WOiRC5CAhOV8cJIwbhmIpcSKz4FKBRTBVMaCkAtJhmYjMO0MkZDJuJ1pSYV5MaA2Cen6769s28D-lC28VPYNHEgO_gyjdHF0NKpjPTkF13YwXVxuqjyXPCYahbV2VopZ713aMre1S24VclZ-bGIkpebRUR7vOk4VC3qb_mVfATnaxBTDJ_J_dvtT7y07geWvTbiHY60oYg</recordid><startdate>20180628</startdate><enddate>20180628</enddate><creator>Cipcigan, Flaviu</creator><creator>Carrieri, Anna Paola</creator><creator>Pyzer-Knapp, Edward O.</creator><creator>Krishna, Ritesh</creator><creator>Hsiao, Ya-Wen</creator><creator>Winn, Martyn</creator><creator>Ryadnov, Maxim G.</creator><creator>Edge, Colin</creator><creator>Martyna, Glenn</creator><creator>Crain, Jason</creator><general>American Institute of Physics</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-5015-1443</orcidid><orcidid>https://orcid.org/0000-0002-4964-7759</orcidid><orcidid>https://orcid.org/0000000250151443</orcidid><orcidid>https://orcid.org/0000000249647759</orcidid></search><sort><creationdate>20180628</creationdate><title>Accelerating molecular discovery through data and physical sciences: Applications to peptide-membrane interactions</title><author>Cipcigan, Flaviu ; Carrieri, Anna Paola ; Pyzer-Knapp, Edward O. ; Krishna, Ritesh ; Hsiao, Ya-Wen ; Winn, Martyn ; Ryadnov, Maxim G. ; Edge, Colin ; Martyna, Glenn ; Crain, Jason</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c383t-a4c719f6301d03866eb15aa9c0c90cda9aed347af71a5bffda73aa9bc4ba8ffa3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Antiinfectives and antibacterials</topic><topic>Coding</topic><topic>Data analysis</topic><topic>Graphical representations</topic><topic>Peptides</topic><topic>Physical sciences</topic><topic>Proteins</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cipcigan, Flaviu</creatorcontrib><creatorcontrib>Carrieri, Anna Paola</creatorcontrib><creatorcontrib>Pyzer-Knapp, Edward O.</creatorcontrib><creatorcontrib>Krishna, Ritesh</creatorcontrib><creatorcontrib>Hsiao, Ya-Wen</creatorcontrib><creatorcontrib>Winn, Martyn</creatorcontrib><creatorcontrib>Ryadnov, Maxim G.</creatorcontrib><creatorcontrib>Edge, Colin</creatorcontrib><creatorcontrib>Martyna, Glenn</creatorcontrib><creatorcontrib>Crain, Jason</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>MEDLINE - Academic</collection><jtitle>The Journal of chemical physics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cipcigan, Flaviu</au><au>Carrieri, Anna Paola</au><au>Pyzer-Knapp, Edward O.</au><au>Krishna, Ritesh</au><au>Hsiao, Ya-Wen</au><au>Winn, Martyn</au><au>Ryadnov, Maxim G.</au><au>Edge, Colin</au><au>Martyna, Glenn</au><au>Crain, Jason</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Accelerating molecular discovery through data and physical sciences: Applications to peptide-membrane interactions</atitle><jtitle>The Journal of chemical physics</jtitle><addtitle>J Chem Phys</addtitle><date>2018-06-28</date><risdate>2018</risdate><volume>148</volume><issue>24</issue><spage>241744</spage><epage>241744</epage><pages>241744-241744</pages><issn>0021-9606</issn><eissn>1089-7690</eissn><coden>JCPSA6</coden><abstract>Simulation and data analysis have evolved into powerful methods for discovering and understanding molecular modes of action and designing new compounds to exploit these modes. The combination provides a strong impetus to create and exploit new tools and techniques at the interfaces between physics, biology, and data science as a pathway to new scientific insight and accelerated discovery. In this context, we explore the rational design of novel antimicrobial peptides (short protein sequences exhibiting broad activity against multiple species of bacteria). We show how datasets can be harvested to reveal features which inform new design concepts. We introduce new analysis and visualization tools: a graphical representation of the k-mer spectrum as a fundamental property encoded in antimicrobial peptide databases and a data-driven representation to illustrate membrane binding and permeation of helical peptides.</abstract><cop>United States</cop><pub>American Institute of Physics</pub><pmid>29960328</pmid><doi>10.1063/1.5027261</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-5015-1443</orcidid><orcidid>https://orcid.org/0000-0002-4964-7759</orcidid><orcidid>https://orcid.org/0000000250151443</orcidid><orcidid>https://orcid.org/0000000249647759</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0021-9606 |
ispartof | The Journal of chemical physics, 2018-06, Vol.148 (24), p.241744-241744 |
issn | 0021-9606 1089-7690 |
language | eng |
recordid | cdi_crossref_primary_10_1063_1_5027261 |
source | AIP Journals Complete; Alma/SFX Local Collection |
subjects | Antiinfectives and antibacterials Coding Data analysis Graphical representations Peptides Physical sciences Proteins |
title | Accelerating molecular discovery through data and physical sciences: Applications to peptide-membrane interactions |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T03%3A22%3A07IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Accelerating%20molecular%20discovery%20through%20data%20and%20physical%20sciences:%20Applications%20to%20peptide-membrane%20interactions&rft.jtitle=The%20Journal%20of%20chemical%20physics&rft.au=Cipcigan,%20Flaviu&rft.date=2018-06-28&rft.volume=148&rft.issue=24&rft.spage=241744&rft.epage=241744&rft.pages=241744-241744&rft.issn=0021-9606&rft.eissn=1089-7690&rft.coden=JCPSA6&rft_id=info:doi/10.1063/1.5027261&rft_dat=%3Cproquest_cross%3E2088311087%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2088311087&rft_id=info:pmid/29960328&rfr_iscdi=true |