A method for the calculation of protein α-CH chemical shifts View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1992-01

AUTHORS

Michael P. Williamson, Tetsuo Asakura, Eiji Nakamura, Makoto Demura

ABSTRACT

The chemical shifts of CαH protons have been calculated for 9 proteins, based on coordinates taken from high-resolution crystal structures. Chemical shifts were calculated using ring-current shifts, shifts arising from magnetic anisotropies of bonds, and shifts arising from the polarizing effect of polar atoms on the Cα-H bond. The parameters used were refined iteratively to give the best fit to (experimental — random coil) shifts over the set of 9 proteins. A further small correction was made to the averaged Gly CαH shift. The calculated shifts match observed shifts with correlation coefficients varying between 0.45 and 0.86, with a standard deviation of about 0.3 ppm. The differences between calculated and observed shifts have been studied in detail, including an analysis of different crystal structures of the same protein, and indicate that most of the differences can be accounted for by small differences between the structure in solution and in the crystal. Calculations using NMR-derived structures give a poor fit. The calculations reproduce the experimentally observed differences between chemical shifts for CαH in α-helix and β-sheet. Most of the differentiation in secondary structure-dependent shifts arises from electric field effects, although magnetic anisotropy also makes a large contribution to the net shift. Applications of the calculations to assignment (including stereospecific assignment) and structure determination are discussed. More... »

PAGES

83-98

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/bf02192802

DOI

http://dx.doi.org/10.1007/bf02192802

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1036412028

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/1330129


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/2008/03", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Chemical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0306", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Physical Chemistry (incl. Structural)", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Carbon", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Hydrogen", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Magnetic Resonance Spectroscopy", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Mathematics", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Molecular", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Protein Conformation", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Proteins", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Ubiquitins", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Krebs Institute, Department of Molecular Biology and Biotechnology, University of Sheffield, S10 2UH, Sheffield, UK", 
          "id": "http://www.grid.ac/institutes/grid.11835.3e", 
          "name": [
            "Krebs Institute, Department of Molecular Biology and Biotechnology, University of Sheffield, S10 2UH, Sheffield, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Williamson", 
        "givenName": "Michael P.", 
        "id": "sg:person.0713375150.21", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0713375150.21"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Biotechnology, Tokyo University of Agriculture and Technology, Koganei, 184, Tokyo, Japan", 
          "id": "http://www.grid.ac/institutes/grid.136594.c", 
          "name": [
            "Department of Biotechnology, Tokyo University of Agriculture and Technology, Koganei, 184, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Asakura", 
        "givenName": "Tetsuo", 
        "id": "sg:person.01042742210.83", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01042742210.83"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Biotechnology, Tokyo University of Agriculture and Technology, Koganei, 184, Tokyo, Japan", 
          "id": "http://www.grid.ac/institutes/grid.136594.c", 
          "name": [
            "Department of Biotechnology, Tokyo University of Agriculture and Technology, Koganei, 184, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nakamura", 
        "givenName": "Eiji", 
        "id": "sg:person.01033345104.15", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01033345104.15"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Biotechnology, Tokyo University of Agriculture and Technology, Koganei, 184, Tokyo, Japan", 
          "id": "http://www.grid.ac/institutes/grid.136594.c", 
          "name": [
            "Department of Biotechnology, Tokyo University of Agriculture and Technology, Koganei, 184, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Demura", 
        "givenName": "Makoto", 
        "id": "sg:person.01172346356.29", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01172346356.29"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "1992-01", 
    "datePublishedReg": "1992-01-01", 
    "description": "The chemical shifts of C\u03b1H protons have been calculated for 9 proteins, based on coordinates taken from high-resolution crystal structures. Chemical shifts were calculated using ring-current shifts, shifts arising from magnetic anisotropies of bonds, and shifts arising from the polarizing effect of polar atoms on the C\u03b1-H bond. The parameters used were refined iteratively to give the best fit to (experimental \u2014 random coil) shifts over the set of 9 proteins. A further small correction was made to the averaged Gly C\u03b1H shift. The calculated shifts match observed shifts with correlation coefficients varying between 0.45 and 0.86, with a standard deviation of about 0.3 ppm. The differences between calculated and observed shifts have been studied in detail, including an analysis of different crystal structures of the same protein, and indicate that most of the differences can be accounted for by small differences between the structure in solution and in the crystal. Calculations using NMR-derived structures give a poor fit. The calculations reproduce the experimentally observed differences between chemical shifts for C\u03b1H in \u03b1-helix and \u03b2-sheet. Most of the differentiation in secondary structure-dependent shifts arises from electric field effects, although magnetic anisotropy also makes a large contribution to the net shift. Applications of the calculations to assignment (including stereospecific assignment) and structure determination are discussed.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/bf02192802", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1101518", 
        "issn": [
          "0925-2738", 
          "1573-5001"
        ], 
        "name": "Journal of Biomolecular NMR", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "2"
      }
    ], 
    "keywords": [
      "chemical shifts", 
      "crystal structure", 
      "CH chemical shifts", 
      "different crystal structures", 
      "structure determination", 
      "ring-current shifts", 
      "high-resolution crystal structures", 
      "polar atoms", 
      "bonds", 
      "electric field effects", 
      "magnetic anisotropy", 
      "observed shifts", 
      "field effects", 
      "polarizing effect", 
      "C\u03b1H", 
      "calculations", 
      "structure", 
      "NMR", 
      "standard deviation", 
      "atoms", 
      "shift", 
      "protons", 
      "crystals", 
      "C\u03b1", 
      "determination", 
      "ppm", 
      "large contribution", 
      "solution", 
      "small differences", 
      "best fit", 
      "helix", 
      "net shift", 
      "anisotropy", 
      "observed differences", 
      "correlation coefficient", 
      "assignment", 
      "same protein", 
      "sheets", 
      "applications", 
      "effect", 
      "coefficient", 
      "deviation", 
      "method", 
      "protein \u03b1", 
      "protein", 
      "detail", 
      "parameters", 
      "fit", 
      "analysis", 
      "contribution", 
      "coordinates", 
      "small corrections", 
      "differences", 
      "poor fit", 
      "set", 
      "correction", 
      "differentiation", 
      "C\u03b1H protons", 
      "further small correction", 
      "Gly C\u03b1H shift", 
      "C\u03b1H shift", 
      "secondary structure-dependent shifts", 
      "structure-dependent shifts"
    ], 
    "name": "A method for the calculation of protein \u03b1-CH chemical shifts", 
    "pagination": "83-98", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1036412028"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/bf02192802"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "1330129"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/bf02192802", 
      "https://app.dimensions.ai/details/publication/pub.1036412028"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2021-12-01T19:07", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20211201/entities/gbq_results/article/article_225.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/bf02192802"
  }
]
 

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/bf02192802'

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/bf02192802'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/bf02192802'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/bf02192802'


 

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

181 TRIPLES      21 PREDICATES      98 URIs      90 LITERALS      15 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/bf02192802 schema:about N42e97ddf6eb44d6496ed080ff81f34c9
2 N5debe0a4f5824ed3acace42b03649713
3 N5e5fb5ee2e7244c8969ea6d5e5799210
4 N6af92e04bfaa4eeb82ab72247d67f418
5 N99f7ca784bbc478f9217d9d9518f2057
6 N9bce12f5bc4b43eba4446e115c1c4a29
7 N9ee57a5934d1425da3a6d13c5d5439d3
8 Nd79334cfa93d4bfd963ead018decb77f
9 anzsrc-for:03
10 anzsrc-for:0306
11 schema:author Nfec8b6b6181c49f68fa58dc5ed32ae6d
12 schema:datePublished 1992-01
13 schema:datePublishedReg 1992-01-01
14 schema:description The chemical shifts of CαH protons have been calculated for 9 proteins, based on coordinates taken from high-resolution crystal structures. Chemical shifts were calculated using ring-current shifts, shifts arising from magnetic anisotropies of bonds, and shifts arising from the polarizing effect of polar atoms on the Cα-H bond. The parameters used were refined iteratively to give the best fit to (experimental — random coil) shifts over the set of 9 proteins. A further small correction was made to the averaged Gly CαH shift. The calculated shifts match observed shifts with correlation coefficients varying between 0.45 and 0.86, with a standard deviation of about 0.3 ppm. The differences between calculated and observed shifts have been studied in detail, including an analysis of different crystal structures of the same protein, and indicate that most of the differences can be accounted for by small differences between the structure in solution and in the crystal. Calculations using NMR-derived structures give a poor fit. The calculations reproduce the experimentally observed differences between chemical shifts for CαH in α-helix and β-sheet. Most of the differentiation in secondary structure-dependent shifts arises from electric field effects, although magnetic anisotropy also makes a large contribution to the net shift. Applications of the calculations to assignment (including stereospecific assignment) and structure determination are discussed.
15 schema:genre article
16 schema:inLanguage en
17 schema:isAccessibleForFree false
18 schema:isPartOf N8c6d2e92bf3045aca6b737c45a6790bf
19 Na43d8f6acfdd45abb1b2b3a6b2941e90
20 sg:journal.1101518
21 schema:keywords CH chemical shifts
22
23 CαH
24 CαH protons
25 CαH shift
26 Gly CαH shift
27 NMR
28 analysis
29 anisotropy
30 applications
31 assignment
32 atoms
33 best fit
34 bonds
35 calculations
36 chemical shifts
37 coefficient
38 contribution
39 coordinates
40 correction
41 correlation coefficient
42 crystal structure
43 crystals
44 detail
45 determination
46 deviation
47 differences
48 different crystal structures
49 differentiation
50 effect
51 electric field effects
52 field effects
53 fit
54 further small correction
55 helix
56 high-resolution crystal structures
57 large contribution
58 magnetic anisotropy
59 method
60 net shift
61 observed differences
62 observed shifts
63 parameters
64 polar atoms
65 polarizing effect
66 poor fit
67 ppm
68 protein
69 protein α
70 protons
71 ring-current shifts
72 same protein
73 secondary structure-dependent shifts
74 set
75 sheets
76 shift
77 small corrections
78 small differences
79 solution
80 standard deviation
81 structure
82 structure determination
83 structure-dependent shifts
84 schema:name A method for the calculation of protein α-CH chemical shifts
85 schema:pagination 83-98
86 schema:productId N02772099553a44ca8214b92c43cffb2c
87 N6c6ec6cfd9094849ab3db00e82972b50
88 Nd864fb43d15c48f6a766f8c884a84155
89 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036412028
90 https://doi.org/10.1007/bf02192802
91 schema:sdDatePublished 2021-12-01T19:07
92 schema:sdLicense https://scigraph.springernature.com/explorer/license/
93 schema:sdPublisher Ne1bc04d37764488196ce9896df8be32e
94 schema:url https://doi.org/10.1007/bf02192802
95 sgo:license sg:explorer/license/
96 sgo:sdDataset articles
97 rdf:type schema:ScholarlyArticle
98 N02772099553a44ca8214b92c43cffb2c schema:name dimensions_id
99 schema:value pub.1036412028
100 rdf:type schema:PropertyValue
101 N31a1675fab8542ca88804b86f5dd1278 rdf:first sg:person.01042742210.83
102 rdf:rest N45b26e760bab46bcb264cdf87cb78962
103 N42e97ddf6eb44d6496ed080ff81f34c9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
104 schema:name Protein Conformation
105 rdf:type schema:DefinedTerm
106 N45b26e760bab46bcb264cdf87cb78962 rdf:first sg:person.01033345104.15
107 rdf:rest Nd7fdcea263784837a3362bf1d9522a89
108 N5debe0a4f5824ed3acace42b03649713 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
109 schema:name Magnetic Resonance Spectroscopy
110 rdf:type schema:DefinedTerm
111 N5e5fb5ee2e7244c8969ea6d5e5799210 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
112 schema:name Proteins
113 rdf:type schema:DefinedTerm
114 N6af92e04bfaa4eeb82ab72247d67f418 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
115 schema:name Mathematics
116 rdf:type schema:DefinedTerm
117 N6c6ec6cfd9094849ab3db00e82972b50 schema:name doi
118 schema:value 10.1007/bf02192802
119 rdf:type schema:PropertyValue
120 N8c6d2e92bf3045aca6b737c45a6790bf schema:volumeNumber 2
121 rdf:type schema:PublicationVolume
122 N99f7ca784bbc478f9217d9d9518f2057 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
123 schema:name Carbon
124 rdf:type schema:DefinedTerm
125 N9bce12f5bc4b43eba4446e115c1c4a29 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
126 schema:name Hydrogen
127 rdf:type schema:DefinedTerm
128 N9ee57a5934d1425da3a6d13c5d5439d3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
129 schema:name Ubiquitins
130 rdf:type schema:DefinedTerm
131 Na43d8f6acfdd45abb1b2b3a6b2941e90 schema:issueNumber 1
132 rdf:type schema:PublicationIssue
133 Nd79334cfa93d4bfd963ead018decb77f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
134 schema:name Models, Molecular
135 rdf:type schema:DefinedTerm
136 Nd7fdcea263784837a3362bf1d9522a89 rdf:first sg:person.01172346356.29
137 rdf:rest rdf:nil
138 Nd864fb43d15c48f6a766f8c884a84155 schema:name pubmed_id
139 schema:value 1330129
140 rdf:type schema:PropertyValue
141 Ne1bc04d37764488196ce9896df8be32e schema:name Springer Nature - SN SciGraph project
142 rdf:type schema:Organization
143 Nfec8b6b6181c49f68fa58dc5ed32ae6d rdf:first sg:person.0713375150.21
144 rdf:rest N31a1675fab8542ca88804b86f5dd1278
145 anzsrc-for:03 schema:inDefinedTermSet anzsrc-for:
146 schema:name Chemical Sciences
147 rdf:type schema:DefinedTerm
148 anzsrc-for:0306 schema:inDefinedTermSet anzsrc-for:
149 schema:name Physical Chemistry (incl. Structural)
150 rdf:type schema:DefinedTerm
151 sg:journal.1101518 schema:issn 0925-2738
152 1573-5001
153 schema:name Journal of Biomolecular NMR
154 schema:publisher Springer Nature
155 rdf:type schema:Periodical
156 sg:person.01033345104.15 schema:affiliation grid-institutes:grid.136594.c
157 schema:familyName Nakamura
158 schema:givenName Eiji
159 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01033345104.15
160 rdf:type schema:Person
161 sg:person.01042742210.83 schema:affiliation grid-institutes:grid.136594.c
162 schema:familyName Asakura
163 schema:givenName Tetsuo
164 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01042742210.83
165 rdf:type schema:Person
166 sg:person.01172346356.29 schema:affiliation grid-institutes:grid.136594.c
167 schema:familyName Demura
168 schema:givenName Makoto
169 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01172346356.29
170 rdf:type schema:Person
171 sg:person.0713375150.21 schema:affiliation grid-institutes:grid.11835.3e
172 schema:familyName Williamson
173 schema:givenName Michael P.
174 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0713375150.21
175 rdf:type schema:Person
176 grid-institutes:grid.11835.3e schema:alternateName Krebs Institute, Department of Molecular Biology and Biotechnology, University of Sheffield, S10 2UH, Sheffield, UK
177 schema:name Krebs Institute, Department of Molecular Biology and Biotechnology, University of Sheffield, S10 2UH, Sheffield, UK
178 rdf:type schema:Organization
179 grid-institutes:grid.136594.c schema:alternateName Department of Biotechnology, Tokyo University of Agriculture and Technology, Koganei, 184, Tokyo, Japan
180 schema:name Department of Biotechnology, Tokyo University of Agriculture and Technology, Koganei, 184, Tokyo, Japan
181 rdf:type schema:Organization
 




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


...