Published May 23, 2023
| Version v2
Dataset
Open
Water will find its way: transport through narrow tunnels in hydrolases (hEpx protein)
- 1. Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Poznan, Poland
- 2. International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
Description
Water will find its way: transport through narrow tunnels in hydrolases (hEpx protein)
The input files and results used for the paper "Water will find its way: transport through narrow tunnels in hydrolases" are separated in the different files depending the stage they belong to.
- 01_Simulations.tar.gz: All the files used to get the data employing Molecular Dynamics simulations.
- 02_Caver.tar.gz: Caver config used together with the "Divide-and-conquer approach to study protein tunnels in long molecular dynamics simulations" method (https://doi.org/10.1016/j.mex.2022.101968), and after re-clustering as described in the methods section of the paper.
- 03_Aquaduct.tar.gz: Aquaduct results for all the MD trajectories.
- 04_TransportTools.tar.gz: TransportTools results for hEpx and E470G systems together, since we employed the comparative approach to analyze the results with TransportTools (https://doi.org/10.1093/bioinformatics/btab872).
- 05_WaterAnalysis.tar.gz: The results from the exact matching analysis were parsed to perform H-bond analysis. Here are the PDBs where the *minimum sphere event* is present. Also the txt files with the results from the H-bond analysis are here.
Files
- 01_build_database.py Python3 script to parse the results from the exact matching analysis from TransportTools into a dictionary of transport events. For more detailed information read the script documentation.
- hEpx_E470G.dat Parsed database of transport events for hEpx_E470G system. Command used: python3 01_build_database.py -c 04_TransportTools/hEpx_E470G_tt.ini -o hEpx_E470G.dat
Notes
Files
README.md
Files
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Additional details
Related works
- Has part
- Dataset: 10.5281/zenodo.7966082 (DOI)
- Dataset: 10.5281/zenodo.7966059 (DOI)
- Dataset: 10.5281/zenodo.7966092 (DOI)
- Dataset: 10.5281/zenodo.7965881 (DOI)
- Is published in
- Preprint: 10.1101/2023.05.24.542065 (DOI)