Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 491

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

Gaussian docking functions

McGann, Mark R., Almond, Harold R., Nicholls, Anthony, Grant, J. Andrew, Brown, Frank K.·2003·Biopolymers

Abstract

A shape‐based Gaussian docking function is constructed which uses Gaussian functions to represent the shapes of individual atoms. A set of 20 trypsin ligand–protein complexes are drawn from the Protein Data Bank (PDB), the ligands are separated from the proteins, and then are docked back into the active sites using numerical optimization of this function. It is found that by employing this docking function, quasi‐Newton optimization is capable of moving ligands great distances [on average 7 Å root mean square distance (RMSD)] to locate the correctly docked structure. It is also found that a ligand drawn from one PDB file can be docked into a trypsin structure drawn from any of the trypsin PDB files. This implies that this scoring function is not limited to more accurate x‐ray structures, as is the case for many of the conventional docking methods, but could be extended to homology models. © 2002 Wiley Periodicals, Inc. Biopolymers 68: 76–90, 2003

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/bip.10207

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

Show all 1 references

Cited by

See all 491

Metadata

Authors
McGann, M. R., Almond, H. R., Nicholls, A., Grant, J. A., & Brown, F. K.
Venue
Biopolymers
Publisher
Wiley
Published
2002-12-02
Volume
68
Issue
1
Pages
76-90
ISSN
  • 0006-3525 (ISSN-L)
  • 1097-0282
OpenAlex
W2068672372
Cited by
491
References
1
FWCI
7.59
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: Gaussian docking functions. https://app.cochat.ai/papers/10.1002/bip.10207
The paper
McGann, M. R., Almond, H. R., Nicholls, A., Grant, J. A., & Brown, F. K. (2003). Gaussian docking functions. Biopolymers. https://doi.org/10.1002/bip.10207

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.