Development of a tactical screening method to investigate the characteristics of functional peptides View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2016-01

AUTHORS

Akiko Kume, Mina Okochi, Kazunori Shimizu, Yasuko Yoshida, Hiroyuki Honda

ABSTRACT

Using spot-synthesized peptide arrays, a functional peptide can be screened as a high-binding peptide for a target molecule. We have developed a rational screening method for functional peptides by analyzing the physicochemical rules of high-binding peptide sequences. To screen the peptides simply and strategically, we prepared an exhaustive 4-mer peptide library consisting of 256 peptides (44 = 256) characterized by four physicochemical groups of 20 amino acids: Group 1, non-charged hydrophobic amino acids; Group 2, non-charged hydrophilic amino acids; Group 3, positive-charged hydrophilic amino acids; Group 4, negative-charged hydrophilic amino acids. First, our previous screening data from cell adhesion, bile acid-binding, and nanoparticle-binding peptides were applied to the four-category analysis, and target-specific physicochemical characteristics were obtained. We then prepared an exhaustive 4-mer peptide library using these four physicochemical groups, and screened for high-binding peptides that bind model proteins interleukin-2 and IgG. We obtained individual physicochemical rules for high-binding peptides: group 1 or 4 amino acids in position (P) 1, group 1 in P2 and P4 for IL-2, and group 2 and 3 amino acids at all position for IgG. Therefore, this system, which employs the use of a simple and strategic peptide library, will be useful in the development of functional peptides. More... »

PAGES

119-127

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12257-015-0523-0

DOI

http://dx.doi.org/10.1007/s12257-015-0523-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1011914758


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0303", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Macromolecular and Materials Chemistry", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/03", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Chemical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Nagoya University", 
          "id": "https://www.grid.ac/institutes/grid.27476.30", 
          "name": [
            "Department of Biotechnology, Graduate School of Engineering, Nagoya University, 464-8603, Nagoya, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kume", 
        "givenName": "Akiko", 
        "id": "sg:person.014374604335.14", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014374604335.14"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tokyo Institute of Technology", 
          "id": "https://www.grid.ac/institutes/grid.32197.3e", 
          "name": [
            "Department of Chemical Engineering, Graduate School of Science and Engineering, Tokyo Institute of Technology, 152-8552, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Okochi", 
        "givenName": "Mina", 
        "id": "sg:person.0740275451.42", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0740275451.42"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Nagoya University", 
          "id": "https://www.grid.ac/institutes/grid.27476.30", 
          "name": [
            "Department of Biotechnology, Graduate School of Engineering, Nagoya University, 464-8603, Nagoya, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shimizu", 
        "givenName": "Kazunori", 
        "id": "sg:person.016146465161.11", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016146465161.11"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Nagoya University", 
          "id": "https://www.grid.ac/institutes/grid.27476.30", 
          "name": [
            "Innovative Research Center for Preventative Medical Engineering, Nagoya University, 464-8603, Nagoya, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yoshida", 
        "givenName": "Yasuko", 
        "id": "sg:person.07426074352.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07426074352.27"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Nagoya University", 
          "id": "https://www.grid.ac/institutes/grid.27476.30", 
          "name": [
            "Department of Biotechnology, Graduate School of Engineering, Nagoya University, 464-8603, Nagoya, Japan", 
            "Innovative Research Center for Preventative Medical Engineering, Nagoya University, 464-8603, Nagoya, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Honda", 
        "givenName": "Hiroyuki", 
        "id": "sg:person.016617716011.29", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016617716011.29"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1002/jmr.2477", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007944332"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0040-4020(01)85612-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008923343"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.biologicals.2005.06.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009818724"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.febslet.2006.01.010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011219066"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.actbio.2009.12.025", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011459780"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1074/jbc.m115.643700", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021449568"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/bjc.2015.189", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027356767", 
          "https://doi.org/10.1038/bjc.2015.189"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jbiosc.2011.03.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041049669"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1271/bbb.110963", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043059328"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.bbrc.2004.01.016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047681256"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.bbrc.2007.08.110", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052506625"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2144/000112693", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069095711"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2016-01", 
    "datePublishedReg": "2016-01-01", 
    "description": "Using spot-synthesized peptide arrays, a functional peptide can be screened as a high-binding peptide for a target molecule. We have developed a rational screening method for functional peptides by analyzing the physicochemical rules of high-binding peptide sequences. To screen the peptides simply and strategically, we prepared an exhaustive 4-mer peptide library consisting of 256 peptides (44 = 256) characterized by four physicochemical groups of 20 amino acids: Group 1, non-charged hydrophobic amino acids; Group 2, non-charged hydrophilic amino acids; Group 3, positive-charged hydrophilic amino acids; Group 4, negative-charged hydrophilic amino acids. First, our previous screening data from cell adhesion, bile acid-binding, and nanoparticle-binding peptides were applied to the four-category analysis, and target-specific physicochemical characteristics were obtained. We then prepared an exhaustive 4-mer peptide library using these four physicochemical groups, and screened for high-binding peptides that bind model proteins interleukin-2 and IgG. We obtained individual physicochemical rules for high-binding peptides: group 1 or 4 amino acids in position (P) 1, group 1 in P2 and P4 for IL-2, and group 2 and 3 amino acids at all position for IgG. Therefore, this system, which employs the use of a simple and strategic peptide library, will be useful in the development of functional peptides.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s12257-015-0523-0", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.6110990", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1036335", 
        "issn": [
          "1226-8372", 
          "1976-3816"
        ], 
        "name": "Biotechnology and Bioprocess Engineering", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "21"
      }
    ], 
    "name": "Development of a tactical screening method to investigate the characteristics of functional peptides", 
    "pagination": "119-127", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "38c49aa4f54d58dd6bb75eb561c5454f93a35a5ae3ca10571eb1c339dd6a501a"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s12257-015-0523-0"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1011914758"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s12257-015-0523-0", 
      "https://app.dimensions.ai/details/publication/pub.1011914758"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T21:38", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8687_00000520.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs12257-015-0523-0"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s12257-015-0523-0'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s12257-015-0523-0'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12257-015-0523-0'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12257-015-0523-0'


 

This table displays all metadata directly associated to this object as RDF triples.

132 TRIPLES      21 PREDICATES      39 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s12257-015-0523-0 schema:about anzsrc-for:03
2 anzsrc-for:0303
3 schema:author N28774ec1628946bab759bd05f0fd285e
4 schema:citation sg:pub.10.1038/bjc.2015.189
5 https://doi.org/10.1002/jmr.2477
6 https://doi.org/10.1016/j.actbio.2009.12.025
7 https://doi.org/10.1016/j.bbrc.2004.01.016
8 https://doi.org/10.1016/j.bbrc.2007.08.110
9 https://doi.org/10.1016/j.biologicals.2005.06.007
10 https://doi.org/10.1016/j.febslet.2006.01.010
11 https://doi.org/10.1016/j.jbiosc.2011.03.002
12 https://doi.org/10.1016/s0040-4020(01)85612-x
13 https://doi.org/10.1074/jbc.m115.643700
14 https://doi.org/10.1271/bbb.110963
15 https://doi.org/10.2144/000112693
16 schema:datePublished 2016-01
17 schema:datePublishedReg 2016-01-01
18 schema:description Using spot-synthesized peptide arrays, a functional peptide can be screened as a high-binding peptide for a target molecule. We have developed a rational screening method for functional peptides by analyzing the physicochemical rules of high-binding peptide sequences. To screen the peptides simply and strategically, we prepared an exhaustive 4-mer peptide library consisting of 256 peptides (44 = 256) characterized by four physicochemical groups of 20 amino acids: Group 1, non-charged hydrophobic amino acids; Group 2, non-charged hydrophilic amino acids; Group 3, positive-charged hydrophilic amino acids; Group 4, negative-charged hydrophilic amino acids. First, our previous screening data from cell adhesion, bile acid-binding, and nanoparticle-binding peptides were applied to the four-category analysis, and target-specific physicochemical characteristics were obtained. We then prepared an exhaustive 4-mer peptide library using these four physicochemical groups, and screened for high-binding peptides that bind model proteins interleukin-2 and IgG. We obtained individual physicochemical rules for high-binding peptides: group 1 or 4 amino acids in position (P) 1, group 1 in P2 and P4 for IL-2, and group 2 and 3 amino acids at all position for IgG. Therefore, this system, which employs the use of a simple and strategic peptide library, will be useful in the development of functional peptides.
19 schema:genre research_article
20 schema:inLanguage en
21 schema:isAccessibleForFree false
22 schema:isPartOf N7f48c6a456564bd185bd9fa64a4634ac
23 Nd70a6cb0e8d04d719b3a7d9bb003bfc3
24 sg:journal.1036335
25 schema:name Development of a tactical screening method to investigate the characteristics of functional peptides
26 schema:pagination 119-127
27 schema:productId N381fb1fd52564a77abc4247ea65d8f48
28 Na35430fa7469406aa180ac1789d0eef8
29 Nd66c081fb3394489964fdfb3a3f1b6ad
30 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011914758
31 https://doi.org/10.1007/s12257-015-0523-0
32 schema:sdDatePublished 2019-04-10T21:38
33 schema:sdLicense https://scigraph.springernature.com/explorer/license/
34 schema:sdPublisher Nf7b3a31c8ff745e9a76c92bd97f5aefd
35 schema:url http://link.springer.com/10.1007%2Fs12257-015-0523-0
36 sgo:license sg:explorer/license/
37 sgo:sdDataset articles
38 rdf:type schema:ScholarlyArticle
39 N0872daec603c47c8a56129939ba5e941 rdf:first sg:person.07426074352.27
40 rdf:rest Neeb7bd0227ca4b84a4238795586149ef
41 N28774ec1628946bab759bd05f0fd285e rdf:first sg:person.014374604335.14
42 rdf:rest N997e7dfa3dbe47e58eddc028980709fa
43 N381fb1fd52564a77abc4247ea65d8f48 schema:name readcube_id
44 schema:value 38c49aa4f54d58dd6bb75eb561c5454f93a35a5ae3ca10571eb1c339dd6a501a
45 rdf:type schema:PropertyValue
46 N6cea82b5e395445cafb399b67c5b59a2 rdf:first sg:person.016146465161.11
47 rdf:rest N0872daec603c47c8a56129939ba5e941
48 N7f48c6a456564bd185bd9fa64a4634ac schema:issueNumber 1
49 rdf:type schema:PublicationIssue
50 N997e7dfa3dbe47e58eddc028980709fa rdf:first sg:person.0740275451.42
51 rdf:rest N6cea82b5e395445cafb399b67c5b59a2
52 Na35430fa7469406aa180ac1789d0eef8 schema:name doi
53 schema:value 10.1007/s12257-015-0523-0
54 rdf:type schema:PropertyValue
55 Nd66c081fb3394489964fdfb3a3f1b6ad schema:name dimensions_id
56 schema:value pub.1011914758
57 rdf:type schema:PropertyValue
58 Nd70a6cb0e8d04d719b3a7d9bb003bfc3 schema:volumeNumber 21
59 rdf:type schema:PublicationVolume
60 Neeb7bd0227ca4b84a4238795586149ef rdf:first sg:person.016617716011.29
61 rdf:rest rdf:nil
62 Nf7b3a31c8ff745e9a76c92bd97f5aefd schema:name Springer Nature - SN SciGraph project
63 rdf:type schema:Organization
64 anzsrc-for:03 schema:inDefinedTermSet anzsrc-for:
65 schema:name Chemical Sciences
66 rdf:type schema:DefinedTerm
67 anzsrc-for:0303 schema:inDefinedTermSet anzsrc-for:
68 schema:name Macromolecular and Materials Chemistry
69 rdf:type schema:DefinedTerm
70 sg:grant.6110990 http://pending.schema.org/fundedItem sg:pub.10.1007/s12257-015-0523-0
71 rdf:type schema:MonetaryGrant
72 sg:journal.1036335 schema:issn 1226-8372
73 1976-3816
74 schema:name Biotechnology and Bioprocess Engineering
75 rdf:type schema:Periodical
76 sg:person.014374604335.14 schema:affiliation https://www.grid.ac/institutes/grid.27476.30
77 schema:familyName Kume
78 schema:givenName Akiko
79 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014374604335.14
80 rdf:type schema:Person
81 sg:person.016146465161.11 schema:affiliation https://www.grid.ac/institutes/grid.27476.30
82 schema:familyName Shimizu
83 schema:givenName Kazunori
84 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016146465161.11
85 rdf:type schema:Person
86 sg:person.016617716011.29 schema:affiliation https://www.grid.ac/institutes/grid.27476.30
87 schema:familyName Honda
88 schema:givenName Hiroyuki
89 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016617716011.29
90 rdf:type schema:Person
91 sg:person.0740275451.42 schema:affiliation https://www.grid.ac/institutes/grid.32197.3e
92 schema:familyName Okochi
93 schema:givenName Mina
94 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0740275451.42
95 rdf:type schema:Person
96 sg:person.07426074352.27 schema:affiliation https://www.grid.ac/institutes/grid.27476.30
97 schema:familyName Yoshida
98 schema:givenName Yasuko
99 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07426074352.27
100 rdf:type schema:Person
101 sg:pub.10.1038/bjc.2015.189 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027356767
102 https://doi.org/10.1038/bjc.2015.189
103 rdf:type schema:CreativeWork
104 https://doi.org/10.1002/jmr.2477 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007944332
105 rdf:type schema:CreativeWork
106 https://doi.org/10.1016/j.actbio.2009.12.025 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011459780
107 rdf:type schema:CreativeWork
108 https://doi.org/10.1016/j.bbrc.2004.01.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047681256
109 rdf:type schema:CreativeWork
110 https://doi.org/10.1016/j.bbrc.2007.08.110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052506625
111 rdf:type schema:CreativeWork
112 https://doi.org/10.1016/j.biologicals.2005.06.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009818724
113 rdf:type schema:CreativeWork
114 https://doi.org/10.1016/j.febslet.2006.01.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011219066
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1016/j.jbiosc.2011.03.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041049669
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1016/s0040-4020(01)85612-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1008923343
119 rdf:type schema:CreativeWork
120 https://doi.org/10.1074/jbc.m115.643700 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021449568
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1271/bbb.110963 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043059328
123 rdf:type schema:CreativeWork
124 https://doi.org/10.2144/000112693 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069095711
125 rdf:type schema:CreativeWork
126 https://www.grid.ac/institutes/grid.27476.30 schema:alternateName Nagoya University
127 schema:name Department of Biotechnology, Graduate School of Engineering, Nagoya University, 464-8603, Nagoya, Japan
128 Innovative Research Center for Preventative Medical Engineering, Nagoya University, 464-8603, Nagoya, Japan
129 rdf:type schema:Organization
130 https://www.grid.ac/institutes/grid.32197.3e schema:alternateName Tokyo Institute of Technology
131 schema:name Department of Chemical Engineering, Graduate School of Science and Engineering, Tokyo Institute of Technology, 152-8552, Tokyo, Japan
132 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...