NEMAT: An Automated Non-Equilibrium Free-Energy Framework for Predicting Ligand Affinity in Membrane Proteins

NEMAT (Non-Equilibrium Membrane Alchemical Transformations) is an open-source framework designed to make non-equilibrium free-energy calculations for ligand binding in membrane proteins accessible, reproducible, and automated.

Built around established molecular simulation workflows, NEMAT guides users through the full process—from system preparation and execution to analysis—enabling the estimation of ligand binding affinities directly from non-equilibrium molecular dynamics simulations. It is particularly tailored for membrane protein systems, where setup and analysis are often complex and error-prone.

By providing a structured, modular workflow, NEMAT reduces manual intervention, improves consistency across simulations, and allows researchers to focus on interpreting results rather than managing infrastructure.

For detailed instructions on execution, configuration, available options, and tutorials, please refer to the project documentation.

1. Install

Download NEMAT from GitHub using:

git clone https://github.com/QTC-IQAC/NEMAT.git

First set up env:

cd NEMAT
bash bin/set_env.sh

Then give execute permissions to the NEMAT executable

chmod +x $NMT_HOME/bin/nemat

If using nemat is not available, try updating the .bashrc file:

source ~/.bashrc

Prepare directory for a NEMAT run: nemat start.

Create a new empty directory and, inside the directory, use:

nemat start 

This will copy into your directory the following elements:

1. A folder named membrane
2. A folder named proteins
3. A folder named mdppath
4. A folder named ligands
5. A folder named logs
6. A file named input.yaml

Now you have the structure to start a NEMAT run. Create the inputs for ligands, membrane, and protein as explained in the documentation.

Set up of NEMAT: the input.yaml file

An example of an input for the FEP simulation can be found in input.yaml:

##############################
#       PREPARE INPUTS       #
##############################

inputDirName: 'input_name'             # path to the directory where the input files will be located. 
proteinName: 'prot_name'               # name of the protein in inputDirName/proteins that will be used.


##############################
#      SIMULATION INPUTS     #
##############################


workPath: 'workpath_name'                # path to the directory where the simulations will run
replicas: 3                              # set the number of replicas (several repetitions of calculation are useful to obtain reliable statistics)
edges:                                   # List of lists containing the edges.  
  - ['small_molec_1', 'small_molec_2']   # without the .mol2 
  - ['small_molec_1', 'small_molec_3']
  - ['small_molec_2', 'small_molec_3']

pname: 'NA'                              # Which positive ions to use in the ligand simulations
nname: 'CL'                              # Which negative ions to use in the ligand simulations 
# slotsToUse: 6                          # Use if you want to limit the number of jobs running at the same time in the cluster.
saveFrames: 200                          # Number of frames to save in the production MD. The default is 400 frames.
frameNum: 100                            # Number of frames to extract to make transitions. The default upper limit is frameNum.
temp: 298                                # Temperature of the systems.
units: 'kcal'                            # Units for the free energy calculations ("kJ" for kJ/mol or "kcal" for kcal/mol)
mdtime: 20                               # Production MD time in ns. If you want to use the time in the mdp files, don't set this parameter or set it to None.
titime: 0.2                              # Transition MD time in ns. If you want to use the time in the mdp files, don't set this parameter or set it to None.
tstart: 5                                # Starting time (in ns) to extract frames from the production MD for transition simulations. If None, tstart will be determined by frameNum.


##############################
#    JOB SUBMISSION INPUTS   #
##############################

JOBsimcpu: 24                            # Number of CPUs to use for the simulation jobs
JOBmodules:                              # List of modules to load for the simulation jobs
  - 'gromacs-plumed/2024.2-2.9.2'  
JOBgmx: 'gmx mdrun -maxh 72'             # Command to run the simulation jobs
JOBpartition: 'gpu'                      # Partition to use for the simulation jobs
JOBsimtime: '3-00:00'                    # Time limit for the simulation jobs. Can be set to none.
JOBmpi: False                            # Set to True if you want to specifically display -ntmpi 1 (solves problem of rank division)
JOBexport:                               # List of environment variables to export for the simulation jobs (the jobs will include "export SET_SOME_VAR=1")
  - 'SET_SOME_VAR=1'

JOBsource:                               # List of source files to run before the simulation jobs (the jobs will include "source file.sh")
  - 'file.sh'                          
              
JOBcommands:                             # List of commands to run before the simulation jobs 
  - 'conda activate NEMAT'    
  
  
##############################
#          ANALYSIS          #
##############################

precision: 1                             # Number of decimal places to use in the analysis output (results.png)
framesAnalysis: [start_frame, end_frame] # List of frames to analyze. If you want to analyze all frames, ignore this field. 
nframesAnalysis: 80                      # Number of frames to use in the analysis (max frameNum, which is the number of transitions).
spacedFrames: False                      # if True, nframesAnalysis are evenly spaced. If False, all frames in nframesAnalysis are selected

Remember to load GROMACS using JOBmodules if it's a module or manually. More modules can be loaded, but only GROMACS is strictly necessary.

On the other hand, it is important that the GROMACS executable gmx exists. If you only have gmx_mpi as an executable, the program will fail.

See all options here.

Running NEMAT.

Use nemat or nemat help to display all the options. You can use nemat wf to display a simplified workflow for a NEMAT run:

>>> submit this steps sequentially for a complete NEMAT run... ([ ]  <-- You are here!  marks the last completed step)

	 1. Prepare the system        : nemat prep

   [ 2. Prepare minimization      : nemat prep_min ] 	 <-- You are here!

	 3. Run minimization          : nemat run_min

	 4. Prepare equilibration     : nemat prep_eq
	 5. Run equilibration         : nemat run_eq

	 6. Prepare production        : nemat prep_md
	 7. Run production            : nemat run_md

	 8. Prepare transitions       : nemat prep_ti
	 9. Run transitions           : nemat run_ti

	10. Analyze results           : nemat analyze

This is the order to run from start to finish a complete run. For more details on every step, refer to the executing documentation.

Reproduce the results of the paper.

NEMAT allows you to create a starting directory with the precomputed input files used in the paper (DOI (preprint): https://www.biorxiv.org/content/10.64898/2025.12.09.692605v1). Follow these steps:

1. Create a new directory (for example, nemat_test).
2. cd nemat_test
3. nemat example
4. You can now follow the steps from section 8.

In case you want to reproduce the 6a analogues (Tab. 2), you must change the edges in input.yaml with:

edges:                                 # List of lists containing the edges.  
  - ['6a', '6i']
  - ['6a', '6f']
  - ['6a', '6h']
  - ['6a', '6m']
  - ['6a', '6g']
  - ['6a', '6l']
  - ['6a', '6j']
  - ['6a', '6n']  

License

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