This repository contains a step-by-step tutorial for analyzing molecular dynamics (MD) simulations using GROMACS.
These methods provide insights into the structural changes and stability of the system throughout the simulation. They help in understanding how the structure of the molecule changes over time.
- Root Mean Square Deviation (RMSD): Measures the average distance between the atoms of superimposed proteins.
- Root Mean Square Fluctuation (RMSF): Determines the flexibility of different parts of a protein structure.
- Radius of Gyration (ROG/Rg): This gives an idea about the compactness of the protein structure during the simulation.
- Hydrogen-bond Analysis (HBond): Provides insights into the stability of the protein structure.
- Solvent Accessible Surface Areas (SASA): Calculates the exposure of the protein to the solvent.
- Secondary Structure Element (SSE) Analysis: Provides information about the secondary structure elements of the protein during the simulation.
These methods provide insights into the system's dynamic behaviour. They help to understand the movements and interactions of the molecule.
- Principal Component Analysis (PCA).
- Porcupine plot analysis of PCA.
- Clustering analysis.
- MM-PB(GB)SA
- Decomposition
Create a new directory for analysis and link the required files from the parent directory.
Clean the trajectory and extract the first frame using gmx trjconv
.
Calculate the Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), and Radius of Gyration (Rg/ROG) using gmx rms
, gmx rmsf
, gmx gyrate
, gmx sasa
and gmx do_dssp
respectively.
- Perform Principal Component Analysis (PCA) using the
pca.py
script from the MODE-TASK tool. - Comparing PCA results from two different trajectories (Will be updated soon).
Perform clustering to group similar structures from a trajectory using the ttclust
tool.
Calculate the binding free energy of a system using the gmx_MMPBSA
tool.