Published May 23, 2023
| Version v2
Dataset
Open
Water will find its way: transport through narrow tunnels in hydrolases (Lip 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
- 3. National Institute of Nuclear Physics, Sezione di Roma Tor Vergata, Italy
Description
Water will find its way: transport through narrow tunnels in hydrolases (Lip 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 folders 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 (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.
- Lip.dat Parsed database of transport events for Lip system. Command used: python3 01_build_database.py -c 04_TransportTools/Lip_tt.ini -o Lip.dat
Notes
Files
README.md
Files
(38.4 GB)
Name | Size | Download all |
---|---|---|
md5:5d637eb3e8d59d35b219bea892500013
|
6.9 kB | Download |
md5:cf32a5684f9953cf2626f9f9bc1044c9
|
199.3 MB | Download |
md5:144812f59facadd03d9030674ca182a1
|
799 Bytes | Download |
md5:7422360f65e01024e5781c958e502aba
|
551.5 MB | Download |
md5:3ed5f73a9673e3825fdaf97aa9a5900b
|
36.1 GB | Download |
md5:845681ac88a68695877b6484b7107e77
|
1.5 GB | Download |
md5:268746930f7f397af3a663bef4e6d22a
|
771.5 kB | Download |
md5:5e9e2eca785773aa9a1caf7d7f3a79b4
|
1.5 kB | Preview Download |
Additional details
Related works
- Has part
- Dataset: 10.5281/zenodo.7966082 (DOI)
- Dataset: 10.5281/zenodo.7966059 (DOI)
- Dataset: 10.5281/zenodo.7965661 (DOI)
- Dataset: 10.5281/zenodo.7965881 (DOI)
- Is published in
- Preprint: 10.1101/2023.05.24.542065 (DOI)