Biased simulation

Introduction

This simulation aims to find a binding mode containing a specific interaction between two atoms, it provides the user with a list of ranked binding modes of the chosen small molecule with the desired interaction.

For more details, check out our article: Adaptive simulations, towards interactive protein-ligand modeling.

Inputs

  • protein-ligand PDB file

  • YAML file with parameters

Default parameters

  • iterations: 100

  • pele steps: 8

Recommendations

  1. We recommend using at least 50 CPUs.

  2. Expected computational time is 3h but it is system-dependent.

1. Complex Preparation

Prepare the system with maestro (Protein Preparation Wizard) and output a complex.pdb. The complex.pdb must contain the protein-ligand in the desired initial conformation. If the binding site is known, the ligand must be set as close as possible to the protein surface on that side of the protein.

2. Input Preparation

Prepare the input file input.yml:

#####Normal simulation (any type)########
system: 'docking2grid6n4b_thc.pdb' # Protein ligand PDB
chain: 'L' # Ligand chain name
resname: 'THC' # Ligand residue name
seed: 12345
# Distance to track along the simulation
atom_dist:
- "A:2:CA" # First atom (chain ID:residue number:atom name)
- "B:3:CG" # Second atom
cpus: 100
out_in: true # Binding simulation
initial_site: "A:577:N"
final_site: "A:867:CB"
###############BIAS PART#######################
spawning: epsilon # Apply bias
epsilon: 0.25 # Level of bias ranging from 0 to 1
bias_column: 7 # Column of the report starting by one to bias the results towards. (You may want to first launch a simulation with the default bias_column, then inspect the simulation report. Last, kill that simulation to launch another one with the optimized bias column value)

For more optional flags please refer to optional flags.

3. Run simulation

To run the system launch the simulation with the following command:

python -m pele_platform.main input.yml

4. Output

Raw output

Trajectory and report files for each simulation are located in working_folder/output. That’s where you can find detailed information on each snapshot (PDB file, binding energy, metrics, etc.).

Selected poses

Clusters

Upon completion of the simulation, all trajectories are clustered based on ligand heavy atom coordinates. Then, a cluster representative with the best binding energy (or metric of your choice) is selected. Ranked cluster representatives can be found in:

working_folder/results/clusters

Best snapshots

In addition, top 100 structures with the best binding energy (or metric of your choice) are retrieved. This is done to ensure the clustering algorithm did not skip any valuable results. They are stored in:

working_folder/results/top_poses