Prediction of Protein Structure from Amino Acid Sequence View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

1987

AUTHORS

Michael J. E. Sternberg

ABSTRACT

Renaturation experiments show that a folded active protein can be unfolded and inactivated and then this process can be reversed to yield the active folded molecule. Thus it is considered that the amino acid sequence and the protein environment determine the three-dimensional conformation of a protein. Accordingly workers are trying to predict theoretically the three-dimensional structure of a protein from its sequence. Prediction will be useful as protein crystallography is at best time-consuming (typically at least 10 man years) and sometimes impossible because of unsuitable or unavailable crystals. In contrast, amino acid sequence information, today often derived from the nucleic acid sequence, is becoming available for many proteins. Recently, the advent of protein engineering has increased the requirements to model the relationship between protein sequence and conformation (eg. Fersht et al, 1985). This paper reviews available methods of structure prediction and introduces developments using data bases and logic programming computer languages. More... »

PAGES

141-149

Book

TITLE

Crystallography in Molecular Biology

ISBN

978-1-4684-5274-7
978-1-4684-5272-3

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-4684-5272-3_12

DOI

http://dx.doi.org/10.1007/978-1-4684-5272-3_12

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1040267690


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/2008/0601", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biochemistry and Cell Biology", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biological Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Birkbeck, University of London", 
          "id": "https://www.grid.ac/institutes/grid.88379.3d", 
          "name": [
            "Department of Crystallography, Birkbeck College, Malet Street, London, WC1E 7HX, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sternberg", 
        "givenName": "Michael J. E.", 
        "id": "sg:person.0611736450.97", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0611736450.97"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/316170a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004191876", 
          "https://doi.org/10.1038/316170a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0141-8130(82)90042-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011195144"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0141-8130(82)90042-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011195144"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0022-2836(69)90487-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011839241"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0022-2836(79)90260-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015482753"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0065-3233(08)60520-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022969730"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0014-5793(84)80774-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024818202"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0022-2836(78)90297-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025687659"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/301540a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025735061", 
          "https://doi.org/10.1038/301540a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0022-2836(77)80200-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032593955"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0022-2836(85)90248-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035460094"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/310235a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036994669", 
          "https://doi.org/10.1038/310235a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/304273a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038177308", 
          "https://doi.org/10.1038/304273a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1042/bj1950031", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038554299"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1042/bj1950031", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038554299"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0097-8485(83)80011-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039519279"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0022-2836(74)90405-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039641042"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1107/s0021889878013308", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046403610"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/285378a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049444757", 
          "https://doi.org/10.1038/285378a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/302842a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052799882", 
          "https://doi.org/10.1038/302842a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0014-5793(82)80597-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053172058"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/314235a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053524488", 
          "https://doi.org/10.1038/314235a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/bi00699a001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055185696"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ja00315a051", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055722739"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "1987", 
    "datePublishedReg": "1987-01-01", 
    "description": "Renaturation experiments show that a folded active protein can be unfolded and inactivated and then this process can be reversed to yield the active folded molecule. Thus it is considered that the amino acid sequence and the protein environment determine the three-dimensional conformation of a protein. Accordingly workers are trying to predict theoretically the three-dimensional structure of a protein from its sequence. Prediction will be useful as protein crystallography is at best time-consuming (typically at least 10 man years) and sometimes impossible because of unsuitable or unavailable crystals. In contrast, amino acid sequence information, today often derived from the nucleic acid sequence, is becoming available for many proteins. Recently, the advent of protein engineering has increased the requirements to model the relationship between protein sequence and conformation (eg. Fersht et al, 1985). This paper reviews available methods of structure prediction and introduces developments using data bases and logic programming computer languages.", 
    "editor": [
      {
        "familyName": "Moras", 
        "givenName": "Dino", 
        "type": "Person"
      }, 
      {
        "familyName": "Drenth", 
        "givenName": "Jan", 
        "type": "Person"
      }, 
      {
        "familyName": "Strandberg", 
        "givenName": "Bror", 
        "type": "Person"
      }, 
      {
        "familyName": "Suck", 
        "givenName": "Dietrich", 
        "type": "Person"
      }, 
      {
        "familyName": "Wilson", 
        "givenName": "Keith", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-1-4684-5272-3_12", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-1-4684-5274-7", 
        "978-1-4684-5272-3"
      ], 
      "name": "Crystallography in Molecular Biology", 
      "type": "Book"
    }, 
    "name": "Prediction of Protein Structure from Amino Acid Sequence", 
    "pagination": "141-149", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-1-4684-5272-3_12"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "bfd1b35e054af82ab5f43b69f5bc0ee39ed3423eea3b6b9e70c7a868150ad459"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1040267690"
        ]
      }
    ], 
    "publisher": {
      "location": "Boston, MA", 
      "name": "Springer US", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-1-4684-5272-3_12", 
      "https://app.dimensions.ai/details/publication/pub.1040267690"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-15T23:54", 
    "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_8697_00000268.jsonl", 
    "type": "Chapter", 
    "url": "http://link.springer.com/10.1007/978-1-4684-5272-3_12"
  }
]
 

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.10.1007/978-1-4684-5272-3_12'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-1-4684-5272-3_12'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-1-4684-5272-3_12'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-1-4684-5272-3_12'


 

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

158 TRIPLES      23 PREDICATES      49 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-1-4684-5272-3_12 schema:about anzsrc-for:06
2 anzsrc-for:0601
3 schema:author N01d682123ed64d3d9e26219ac566f38a
4 schema:citation sg:pub.10.1038/285378a0
5 sg:pub.10.1038/301540a0
6 sg:pub.10.1038/302842a0
7 sg:pub.10.1038/304273a0
8 sg:pub.10.1038/310235a0
9 sg:pub.10.1038/314235a0
10 sg:pub.10.1038/316170a0
11 https://doi.org/10.1016/0014-5793(82)80597-8
12 https://doi.org/10.1016/0014-5793(84)80774-7
13 https://doi.org/10.1016/0022-2836(69)90487-2
14 https://doi.org/10.1016/0022-2836(74)90405-7
15 https://doi.org/10.1016/0022-2836(78)90297-8
16 https://doi.org/10.1016/0022-2836(79)90260-2
17 https://doi.org/10.1016/0022-2836(85)90248-7
18 https://doi.org/10.1016/0097-8485(83)80011-4
19 https://doi.org/10.1016/0141-8130(82)90042-3
20 https://doi.org/10.1016/s0022-2836(77)80200-3
21 https://doi.org/10.1016/s0065-3233(08)60520-3
22 https://doi.org/10.1021/bi00699a001
23 https://doi.org/10.1021/ja00315a051
24 https://doi.org/10.1042/bj1950031
25 https://doi.org/10.1107/s0021889878013308
26 schema:datePublished 1987
27 schema:datePublishedReg 1987-01-01
28 schema:description Renaturation experiments show that a folded active protein can be unfolded and inactivated and then this process can be reversed to yield the active folded molecule. Thus it is considered that the amino acid sequence and the protein environment determine the three-dimensional conformation of a protein. Accordingly workers are trying to predict theoretically the three-dimensional structure of a protein from its sequence. Prediction will be useful as protein crystallography is at best time-consuming (typically at least 10 man years) and sometimes impossible because of unsuitable or unavailable crystals. In contrast, amino acid sequence information, today often derived from the nucleic acid sequence, is becoming available for many proteins. Recently, the advent of protein engineering has increased the requirements to model the relationship between protein sequence and conformation (eg. Fersht et al, 1985). This paper reviews available methods of structure prediction and introduces developments using data bases and logic programming computer languages.
29 schema:editor N3bd20afcf88745348fd36521857f3eb5
30 schema:genre chapter
31 schema:inLanguage en
32 schema:isAccessibleForFree false
33 schema:isPartOf N74ef069663b440d89fa71227f6934fcc
34 schema:name Prediction of Protein Structure from Amino Acid Sequence
35 schema:pagination 141-149
36 schema:productId N383f40c4443347ef9fa11fea70b9258a
37 N9f07c47d06c849ab8107b764cc0596fd
38 Ncde83d738639400f8463906d7bdddecf
39 schema:publisher N84d0fe3a24064f9fae591a1805631f7c
40 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040267690
41 https://doi.org/10.1007/978-1-4684-5272-3_12
42 schema:sdDatePublished 2019-04-15T23:54
43 schema:sdLicense https://scigraph.springernature.com/explorer/license/
44 schema:sdPublisher N547a0e8069874f919c99b39adc86c17a
45 schema:url http://link.springer.com/10.1007/978-1-4684-5272-3_12
46 sgo:license sg:explorer/license/
47 sgo:sdDataset chapters
48 rdf:type schema:Chapter
49 N01d682123ed64d3d9e26219ac566f38a rdf:first sg:person.0611736450.97
50 rdf:rest rdf:nil
51 N0e01a3c9f4b2412c88d85eac78625081 schema:familyName Wilson
52 schema:givenName Keith
53 rdf:type schema:Person
54 N2f5cbd4ef0234db9851b053462541a88 schema:familyName Suck
55 schema:givenName Dietrich
56 rdf:type schema:Person
57 N383f40c4443347ef9fa11fea70b9258a schema:name readcube_id
58 schema:value bfd1b35e054af82ab5f43b69f5bc0ee39ed3423eea3b6b9e70c7a868150ad459
59 rdf:type schema:PropertyValue
60 N3bd20afcf88745348fd36521857f3eb5 rdf:first Nf7590eeec31d4a408e0b5702410ececa
61 rdf:rest N8eb5b2bd483c4828b32b124e55bd217b
62 N4042b59d94304db284e4305555cb143a rdf:first N0e01a3c9f4b2412c88d85eac78625081
63 rdf:rest rdf:nil
64 N547a0e8069874f919c99b39adc86c17a schema:name Springer Nature - SN SciGraph project
65 rdf:type schema:Organization
66 N74ef069663b440d89fa71227f6934fcc schema:isbn 978-1-4684-5272-3
67 978-1-4684-5274-7
68 schema:name Crystallography in Molecular Biology
69 rdf:type schema:Book
70 N7b6603edd5104473beb98b475420038b rdf:first N7d8f418a0017477ab487327c62f3d856
71 rdf:rest Nf0eca9b512e543b09c6e9b2e6a4bd9e3
72 N7d8f418a0017477ab487327c62f3d856 schema:familyName Strandberg
73 schema:givenName Bror
74 rdf:type schema:Person
75 N84d0fe3a24064f9fae591a1805631f7c schema:location Boston, MA
76 schema:name Springer US
77 rdf:type schema:Organisation
78 N8eac1202b3184f8ab382bef31913f769 schema:familyName Drenth
79 schema:givenName Jan
80 rdf:type schema:Person
81 N8eb5b2bd483c4828b32b124e55bd217b rdf:first N8eac1202b3184f8ab382bef31913f769
82 rdf:rest N7b6603edd5104473beb98b475420038b
83 N9f07c47d06c849ab8107b764cc0596fd schema:name dimensions_id
84 schema:value pub.1040267690
85 rdf:type schema:PropertyValue
86 Ncde83d738639400f8463906d7bdddecf schema:name doi
87 schema:value 10.1007/978-1-4684-5272-3_12
88 rdf:type schema:PropertyValue
89 Nf0eca9b512e543b09c6e9b2e6a4bd9e3 rdf:first N2f5cbd4ef0234db9851b053462541a88
90 rdf:rest N4042b59d94304db284e4305555cb143a
91 Nf7590eeec31d4a408e0b5702410ececa schema:familyName Moras
92 schema:givenName Dino
93 rdf:type schema:Person
94 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
95 schema:name Biological Sciences
96 rdf:type schema:DefinedTerm
97 anzsrc-for:0601 schema:inDefinedTermSet anzsrc-for:
98 schema:name Biochemistry and Cell Biology
99 rdf:type schema:DefinedTerm
100 sg:person.0611736450.97 schema:affiliation https://www.grid.ac/institutes/grid.88379.3d
101 schema:familyName Sternberg
102 schema:givenName Michael J. E.
103 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0611736450.97
104 rdf:type schema:Person
105 sg:pub.10.1038/285378a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049444757
106 https://doi.org/10.1038/285378a0
107 rdf:type schema:CreativeWork
108 sg:pub.10.1038/301540a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025735061
109 https://doi.org/10.1038/301540a0
110 rdf:type schema:CreativeWork
111 sg:pub.10.1038/302842a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052799882
112 https://doi.org/10.1038/302842a0
113 rdf:type schema:CreativeWork
114 sg:pub.10.1038/304273a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038177308
115 https://doi.org/10.1038/304273a0
116 rdf:type schema:CreativeWork
117 sg:pub.10.1038/310235a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036994669
118 https://doi.org/10.1038/310235a0
119 rdf:type schema:CreativeWork
120 sg:pub.10.1038/314235a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053524488
121 https://doi.org/10.1038/314235a0
122 rdf:type schema:CreativeWork
123 sg:pub.10.1038/316170a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004191876
124 https://doi.org/10.1038/316170a0
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1016/0014-5793(82)80597-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053172058
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1016/0014-5793(84)80774-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024818202
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1016/0022-2836(69)90487-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011839241
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1016/0022-2836(74)90405-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039641042
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1016/0022-2836(78)90297-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025687659
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1016/0022-2836(79)90260-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015482753
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1016/0022-2836(85)90248-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035460094
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1016/0097-8485(83)80011-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039519279
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1016/0141-8130(82)90042-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011195144
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1016/s0022-2836(77)80200-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032593955
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1016/s0065-3233(08)60520-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022969730
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1021/bi00699a001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055185696
149 rdf:type schema:CreativeWork
150 https://doi.org/10.1021/ja00315a051 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055722739
151 rdf:type schema:CreativeWork
152 https://doi.org/10.1042/bj1950031 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038554299
153 rdf:type schema:CreativeWork
154 https://doi.org/10.1107/s0021889878013308 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046403610
155 rdf:type schema:CreativeWork
156 https://www.grid.ac/institutes/grid.88379.3d schema:alternateName Birkbeck, University of London
157 schema:name Department of Crystallography, Birkbeck College, Malet Street, London, WC1E 7HX, UK
158 rdf:type schema:Organization
 




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


...