Skip to content

tillsiebenmorgen/RS-REMD_tutorial

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

22 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Tutorial for RS-REMD

Tutorial to perform RS-REMD simulations as introduced in the following publications:


Prediction of protein–protein complexes using replica exchange with repulsive scaling

Till Siebenmorgen till.siebenmorgen@tum.de, Michael Engelhard, Martin Zacharias

https://doi.org/10.1002/jcc.26187


Efficient Refinement and Free Energy Scoring of Predicted Protein–Protein Complexes Using Replica Exchange with Repulsive Scaling

Till Siebenmorgen, Martin Zacharias

https://doi.org/10.1021/acs.jcim.0c00853


Scripts are written in python 2.7 (for Amber users)

Example_preparation

Following these steps you can set up a RS-REMD simulation

Perform a setup of the groupfile, modify the Lennard-Jones parameters and start the simulation:

python prepare_files_rs.py
python lj.py parm.top 4 -d 0.00 0.1 0.2 0.5 -e 1.00 0.95 0.90 0.80 -c heated.rst -r :1-66 -l :67-123 -hMassRepartitioning -o system.top | tee lj.log
source rs.run

lj.py (python lj.py -help):

parm.top = input topology file that you have created in advance of your system

4 = Number of replicas that you want to use, in our case 4; for proper systems between 8 and 16

-d = distance parameter for LJ scaling of the individual replica; for my systems with 16 replicas: -d 0.00 0.01 0.02 0.04 0.08 0.12 0.16 0.20 0.24 0.28 0.32 0.38 0.44 0.50 0.58 0.68

-e = epsilon parameter for LJ scaling of the individual replica; for my systems with 16 replicas: -e 1.00 0.99 0.98 0.97 0.96 0.94 0.92 0.90 0.88 0.86 0.84 0.82 0.80 0.78 0.76 0.74

-c = heated restart file

-r = receptor mask, specifies the receptor residues whose interaction should be scaled

-l = ligand mask, specifies the receptor residues whose interaction should be scaled

-hMassRepartitioning = if specified performs hMassRepartitioning on the topology files

-o = outputfile name of the generated replicas

Calc_free_energy

From generated trajectories we can now calculate free energy differences. The simulations were performed in explicit solvent and the water molecues were stripped.

python reevaluate_trajs_for_biases.py 

python mbar_freeEnergies.py

Installation

You might be able to use your python installation from ambertools. You can also install the necessary packages using anaconda

conda install -c conda-forge mdtraj
conda install -c ambermd ambertools

For the pymbar installation (in order to calculate free energies) you can use pip install pymbar

About

This is a tutorial to perform the lennard-jones parameter scaling for rs-remd (repulsive scaling remd) simulations for the amber package.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages