Gmx_qk

Gmx_qk automates protein and protein–ligand complex molecular dynamics simulations in Gromacs and performs MM/PBSA calculations to estimate binding affinities.


Key Features:

  • Automated MD workflow: Executes energy minimization, NVT and NPT equilibration, and production MD simulations in an automated bash workflow.
  • Gromacs integration: Uses Gromacs for all MD simulation steps and trajectory generation.
  • MM/PBSA bridging: Performs MM/PBSA calculations on simulation outputs to derive binding affinity estimates.
  • Parameter-driven execution: Accepts inputs including energy minimization parameters, simulation duration, and output file naming to control the automated run.
  • Reproducibility and standardization: Standardizes the simulation protocol to improve reproducibility and reduce user-induced variability.

Scientific Applications:

  • Drug discovery: Estimation of binding affinities for protein–ligand complexes to support compound prioritization.
  • Protein–protein and protein–ligand interaction analysis: Simulation of protein/protein-ligand complexes to study molecular interactions and complex stability.
  • Binding energy evaluation: MM/PBSA-based binding affinity evaluation from MD trajectories.

Methodology:

A bash workflow invokes Gromacs to perform energy minimization, NVT and NPT equilibration, and MD production runs, then applies MM/PBSA calculations to the simulation outputs using provided protein or protein–ligand complex files and specified parameters.

Topics

Details

License:
GPL-3.0
Cost:
Free of charge
Tool Type:
workflow
Operating Systems:
Mac, Linux, Windows
Programming Languages:
Bash
Added:
12/1/2023
Last Updated:
11/24/2024

Operations

Data Inputs & Outputs

Publications

Singh H, Raja A, Prakash A, Medhi B. Gmx_qk: An Automated Protein/Protein–Ligand Complex Simulation Workflow Bridged to MM/PBSA, Based on Gromacs and Zenity-Dependent GUI for Beginners in MD Simulation Study. Journal of Chemical Information and Modeling. 2023;63(9):2603-2608. doi:10.1021/acs.jcim.3c00341. PMID:37079775.

PMID: 37079775
Funding: - University Grants Commission: 315733