Published July 5, 2021 | Version v1

Simulation and analysis data set for apo-conformational kinetics and gated ligand binding to HIV-1 protease

Authors/Creators

  • 1. European Molecular Biology Laboratory

Description

The data set provided here accompanies a study described in the manuscript:

S. Kashif Sadiq, Abraham Muñiz Chicharro, Patrick Friedrich, Rebecca Wade, A multiscale approach for computing gated ligand binding from molecular dynamics and Brownian dynamics simulations. (2021) Preprint available: https://doi.org/10.1101/2021.06.22.449380

This study combines molecular dynamics MD simulations and associated conformational analyses and Markov state models (MSMs) with Brownian dynamics (BD) simulations to compute conformation gated ligand association kinetics to HIV-1 protease.

To download the data, go to a directory where you would like to download the files. Then for each of the provided tar files enter the following command:

tar xvf $X.tar

where $X is the name prefix of the corresponding tar file.

The unpacked data set  creates a ./data sub-directory which itself contains two further sub-directories: MD and BD. Please see README.txt files within these sub directories for further instructions on the software tools and scripts that have been provided therein for using and reproducing the data set.  The MD README.txt is found within: data_MD_MSM_analysis.tar, the BD README.txt is found within: data_BD_examples.tar.

Please note, the python Jupyter notebook and associated module for further analysis of the MSM from the pre-defined feature set calculated in the study as well as other analyses can also be found at:

https://github.com/kashifsadiq/hiv1pr-msm/

MD trajectory files are provided for further analysis but are not required to reproduce the MSM and conformational analyses reported in the study.  To facilitate overview, MSM analysis has been stored in several object files.  To exactly reproduce the reported MD/MSM analyses, untar only the 1) data_MD_MSM_analysis.tar and 2) data_MD_MSMobj.tar files and work through the python Jupyter notebook.

 

Files

Files (25.7 GB)

Name Size
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