Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 229

The DOI matches its Crossref record.

The geometry of metal–ligand interactions relevant to proteins

Harding, Marjorie M.·1999·Acta Crystallographica Section D Biological Crystallography

Abstract

Geometrical data which could be of relevance in the structure determination, structure refinement, assessment or understanding of metalloproteins have been extracted from the Cambridge Structural Database (CSD). The CSD contains crystallographic data from `small-molecule' structures determined by X-ray or neutron diffraction to an accuracy much better than that of most current protein structure determinations. The structures selected have a crystallographic R factor ≤ 0.065 and contain Ca, Mg, Mn, Fe, Cu or Zn interacting with ligands which are analogues of the amino-acid side chains commonly found in proteins; they include carboxylate groups, alcohols, phenolates, thiolates, imidazole groups and also water molecules. For each pair, the mean metal–donor-atom distance, the sample standard deviation and the range of observed values are tabulated, using ∼4500 observations in all. Where practicable, subsets with different coordination numbers and/or oxidation states are given. Also included are inter-bond angles at the ligand donor atom, the orientation of carboxylate and imidazole groups with respect to the metal–donor-atom bond and some other aspects of ligand geometry. Thus, for example, target distances and their standard deviations could be easily looked up for the validation of a metalloprotein structure or for use in restrained refinement with low-resolution data.

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 · 10.1107/s0907444999007374

Cites

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

Cited by

See all 229

Metadata

Authors
Harding, M. M.
Venue
Acta Crystallographica Section D Biological Crystallography
Published
1999-08-01
Volume
55
Issue
8
Pages
1432-1443
ISSN
0907-4449 (ISSN-L)
OpenAlex
W2052317605
Cited by
229
References
0
FWCI
7.74
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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: The geometry of metal–ligand interactions relevant to proteins. https://app.cochat.ai/papers/10.1107/s0907444999007374
The paper
Harding, M. M. (1999). The geometry of metal–ligand interactions relevant to proteins. Acta Crystallographica Section D Biological Crystallography. https://doi.org/10.1107/s0907444999007374

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.