Introduction

Release Notes

v2.4.1 series come with new and improved sequence, structure, and dynamics analysis features. See release notes for details.

How to Cite

Bakan A, Meireles LM, Bahar I ProDy: Protein Dynamics Inferred from Theory and Experiments
Bioinformatics 2011 27(11):1575-1577.

Bakan A, Dutta A, Mao W, Liu Y, Chennubhotla C, Lezon TR, Bahar I Evol and ProDy for Bridging Protein Sequence Evolution and Structural Dynamics
Bioinformatics 2014 30(18):2681-2683.

Zhang S, Krieger JM, Zhang Y, Kaya C, Kaynak B, Mikulska-Ruminska K, Doruker P, Li H, Bahar I ProDy 2.0: Increased scale and scope after 10 years of protein dynamics modelling with Python
Bioinformatics 2021 37(20):3657-3659.

Introduction¶

ClustENMD [KD21] is a highly efficient, unbiased conformational search algorithm, which is suitable for generating atomistic conformers for ensemble docking purposes and for large, supramolecular assemblies like the ribosome [KD16]. In this hybrid method, the following steps are carried out at each generation/cycle: (1) conformer generation by random sampling along global ANM modes, (2) hierarchical clustering of generated conformers and (3) relaxation of cluster representatives by short MD simulations using OpenMM [E17]. The relaxed conformers are then fed back to Step 1, each being used as a starting point for a new generation of conformers. This iterative procedure (Steps 1-3) is repeated for several generations to allow for sufficiently large excursions from the initial structure. Thus, conformational sampling can be efficiently performed for highly flexible systems composed of proteins, RNA and/or DNA chains. Furthermore, the generated ensemble can be analyzed and utilized using the available tools in ProDy.

This tutorial demonstrates how to use ClustENMD to perform conformational sampling for the homo-dimeric enzyme HIV-1 protease in an open conformation without any ligand (PDB id: 1tw7). Furthermore, we will show the application of ProDy ensemble analysis tools to study the conformers and generate their population distribution.

Required Programs¶

The latest versions of ProDy, OpenMM, and PDBFixer are required for ClustENMD.

Getting Started¶

We recommend that you will follow this tutorial by typing commands in an IPython session, e.g.:

$ ipython

or with pylab environment:

$ ipython --pylab

First, we will make necessary imports from ProDy, NumPy, and Matplotlib packages.

In [1]: import numpy as np

In [2]: import matplotlib.pyplot as plt

In [3]: from prody import *

In [4]: plt.ion()

We have included these imports in every part of the tutorial, so that code copied from the online pages is complete. You do not need to repeat imports in the same Python session.

How to Cite¶

If you benefited from ClustENMD in your research, please cite the following paper:

[KD16]

Kurkcuoglu Z., Bahar I., and Doruker P., ClustENM: ENM-Based Sampling of Essential Conformational Space at Full Atomic Resolution, J Chem Theory Comput 2016 12: 4549.

[KD21]

Kaynak B.T., Zhang S., Bahar I., and Doruker P., ClustENMD: Efficient sampling of biomolecular conformational space at atomic resolution, Bioinformatics 2021 (in publication).

Additionally, please also cite the following paper for OpenMM:

[E17]

Eastman P., et al. OpenMM 7: Rapid development of high performance algorithms for molecular dynamics, PLoS Comput Biol 2017 13:e1005659.