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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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Divide-and-conquer approach to study protein tunnels in long molecular dynamics simulations

Authors: Sequeiros-Borja, Carlos;

Divide-and-conquer approach to study protein tunnels in long molecular dynamics simulations

Abstract

# *"Divide-and-conquer approach to study protein tunnels in long molecular dynamics simulations"* The input files and data used for the paper *"Divide-and-conquer approach to study protein tunnels in long molecular dynamics simulations"* are separated in the different folders depending stage they belong to. ## Folders 1. **01_inputs:** The MD trajectory of DhaA used (only protein atoms present) 2. **02_sliced_trajectory:** The CAVER3 results for the sliced trajectory (eight parts) 3. **03_sliced_filtered:** Filtered CAVER3 results and results from the divide-and-conquer approach 4. **04_full_trajectory:** The CAVER3 results for the full trajectory analysis 5. **05_guided_example:** Guided example for the divide-and-conquer approach

Keywords

Molecular dynamics simulations, Proteins, High-throughput workflow, Transport tunnels

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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