Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 258

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

An algorithm for determining the conformation of polypeptide segments in proteins by systematic search

Moult, J., James, M. N. G.·1986·Proteins: Structure, Function, and Bioinformatics

Abstract

The feasibility of determining the conformation of segments of polypeptide chain up to six residues in length in globular proteins by means of systematic search through the possibles conformations has been investigated. Trial conformations are generated by using representative sets of ϕ, ψ, and χ angels that have been derived from an examination of the distributions of these angles in refined protein structures. A set of filters based on simple rules that protein structures obey is used to reduce the number of conformations to a manageable total. The most important filters are the maintenance of chain integrity and the avoidance of tooshort van der Waals contacts with the rest of the protein and with other portions of the segment under construction. The procedure is intended to be used with approximate models so that allowance is made throughout for errors in the rest of the structure. All possible main chains are first constructed and then all possible side‐chain conformations are built onto each of these. The electrostatic energy, including a solvent screening term, and the exposed hyrophobic area are evaluated for each accepted conformation. The method has been tested on two segments of chain in the trypsin like enzyme from Streptomyces griseus. It is found that there is a wide spread of energies among the accepted conformations, and the lowest energy ones have satisfactorily small root mean square deviations from the X‐ray structure.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/prot.340010207

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 258

Metadata

Authors
Moult, J., & James, M. N. G.
Venue
Proteins: Structure, Function, and Bioinformatics
Publisher
Wiley
Published
1986-02
Volume
1
Issue
2
Pages
146-163
ISSN
  • 0887-3585 (ISSN-L)
  • 1097-0134
OpenAlex
W2125793518
Cited by
258
References
1
FWCI
4.70
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.