Introduction

ProDy is an application programming interface (API) designed for structure-based analysis of protein dynamics, in particular for inferring protein dynamics from large heterogeneous structural ensembles. It comes with several command line applications (ProDy Applications) and graphical user interface for visualization (Normal Mode Wizard). This tutorial shows core features of ProDy and some basic analysis tasks. You can find links to more detailed and advanced tutorials below.

Structural Ensemble Analysis

ProDy is primarily designed for analysis of large heterogeneous structural datasets for a protein composed of sequence homologs, mutants, or ligand bound structures that have with missing loops or terminal residues. Dominant patterns in structural variability are extracted by principal component analysis (PCA) of the ensemble. Helper functions allow for comparison of dynamics inferred from experiments with theoretical models and simulation data. For detailed usage examples see Ensemble Analysis.

Elastic Network Models

ProDy can be used for normal mode analysis (NMA) of protein dynamics based on elastic network models (ENMs). Flexible classes allow for developing and using customized gamma functions in ENMs and numerous helper functions allow for comparative analysis of experimental and theoretical datasets. See Elastic Network Models for detailed usage examples.

Trajectory Analysis

In addition to analysis of experimental data and theoretical models, ProDy can be used to analyze trajectories from molecular dynamics simulations, such as for performing essential dynamics analysis (EDA). ProDy supports DCD file format, but trajectories in other formats can be parsed using other Python packages and analyzed using ProDy. See Trajectory Analysis for detailed usage examples.

Visualization

Finally, results from ProDy calculations can be visualized using NMWiz, which is a VMD plugin GUI. NMWiz can also be used for submitting ProDy calculations for molecules in VMD. See NMWiz Tutorial for analysis of various types of datasets and visualization of protein dynamics.