Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 298

The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.

Geo-Measures: A PyMOL plugin for protein structure ensembles analysis

Kagami, Luciano Porto, das Neves, Gustavo Machado, Timmers, Luís Fernando Saraiva Macedo, Caceres, Rafael Andrade, Eifler-Lima, Vera Lucia·2020·Computational Biology and Chemistry

Abstract

Although molecular dynamics encompasses several applications, studies focusing on biomolecular systems are central issues of this research area. Such simulations require the generation of trajectory files, which provide a path for the analysis and interpretation of results with biological significance. However, although several programs have been developed in Python language for the analyses of molecular dynamics (MD) trajectories, they usually require some knowledge of programming languages in order to write or run the scripts using command lines, which certainly hinders the access of MD simulations to many scientists with the necessary biological background to interpret their results. To ease the access to Python packages focusing on MD trajectory analyses, we built a user-friendly and easy-to-install graphical PyMOL interface. Geo-Measures integrates the PyMOL functionalities with MDTraj, a powerful library of trajectory analyses, allowing the users to access up to 14 different types of analyses. Two sample cases are reported here to demonstrate the use of Geo-Measures. In the first example, which involves the use a MD trajectory file of hemoglobin from the MoDEL MD bank, we exemplified the analyses of the following variables: root mean square deviation, radius of gyration, free energy landscape and principal component analysis. In the second case, we built a trajectory file for the ecto-5'-nucleotidase using the LiGRO program to study the carbon alpha pincer angles, to define the secondary structure of the proteins and to analyze the Modevectors. This user-friendly graphical PyMOL plugin, which can be used to generate several descriptive analyses for protein structures, is open source and can be downloaded at: https://pymolwiki.org/index.php/Geo_Measures_Plugin.

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 · 10.1016/j.compbiolchem.2020.107322

Cites

37 of 37 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 37 references

Metadata

Authors
Kagami, L. P., das Neves, G. M., Timmers, L. F. S. M., Caceres, R. A., & Eifler-Lima, V. L.
Venue
Computational Biology and Chemistry
Publisher
Elsevier BV
Published
2020-08
Volume
87
Pages
107322
ISSN
1476-9271 (ISSN-L)
OpenAlex
W3036997165
Cited by
298
References
37
FWCI
4.36
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: Geo-Measures: A PyMOL plugin for protein structure ensembles analysis. https://app.cochat.ai/papers/10.1016/j.compbiolchem.2020.107322
The paper
Kagami, L. P., das Neves, G. M., Timmers, L. F. S. M., Caceres, R. A., & Eifler-Lima, V. L. (2020). Geo-Measures: A PyMOL plugin for protein structure ensembles analysis. Computational Biology and Chemistry. https://doi.org/10.1016/j.compbiolchem.2020.107322

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.