prody

ProDy - Protein Dynamics & Structural Biology

ProDy is designed to model the collective motions of proteins. It treats proteins as elastic networks, allowing researchers to predict functional movements and structural flexibility from a single PDB file or an ensemble of structures.

When to Use

• Predicting protein flexibility and collective motions (ANM/GNM).
• Performing Principal Component Analysis (PCA) on structural ensembles or MD trajectories.
• Analyzing structural conservation and co-evolution (Evol).
• Comparing multiple protein structures (Ensemble analysis).
• Identifying hinge regions and rigid domains in proteins.
• Docking preparation and binding site analysis (druggability).
• Filtering MD trajectories based on collective modes.

Reference Documentation

Official docs: http://prody.csb.pitt.edu/
Manual: http://prody.csb.pitt.edu/manual/
Search patterns: prody.parsePDB, prody.ANM, prody.GNM, prody.select, prody.Ensemble

Core Principles

Atom Selection Algebra

ProDy features a powerful selection language similar to VMD or PyMOL. You can select atoms by chain, residue, property, or proximity (e.g., 'protein and resname TRP and within 5 of resname HEM').

Elastic Network Models (ENM)

• GNM (Gaussian Network Model): Predicts magnitude of fluctuations (B-factors).
• ANM (Anisotropic Network Model): Predicts direction and magnitude of motion.

Ensembles

A collection of structures (e.g., multiple NMR models or MD frames) stored in a way that allows for rapid statistical analysis and PCA.

Quick Reference

Installation

pip install prody

Standard Imports

import numpy as np
from prody import *
# Optional: for plotting
# confProDy(auto_show=False)

Basic Pattern - Normal Mode Analysis

from prody import *

# 1. Parse structure
atoms = parsePDB('1p38')
calphas = atoms.select('protein and calpha')

# 2. Build and solve ANM
anm = ANM('p38_anm')
anm.buildHessian(calphas)
anm.calcModes(n_modes=20)

# 3. Analyze results
for mode in anm[:3]:
    print(f"Mode {mode.getIndex()}: Variance = {mode.getVariance():.2f}")

# 4. Save for visualization (NMD format for VMD/PyMOL)
writeNMD('p38_modes.nmd', anm, calphas)