ClustENM: ENM-Based Sampling of Essential Conformational Space at Full Atomic Resolution

Abstract

Accurate sampling of conformational space and, in particular, the transitions between functional substates has been a challenge in molecular dynamic (MD) simulations of large biomolecular systems. We developed an Elastic Network Model (ENM)-based computational method, ClustENM, for sampling large conformational changes of biomolecules with various sizes and oligomerization states. ClustENM is an iterative method that combines ENM with energy minimization and clustering steps. It is an unbiased technique, which requires only an initial structure as input, and no information about the target conformation. To test the performance of ClustENM, we applied it to six biomolecular systems: adenylate kinase (AK), calmodulin, p38 MAP kinase, HIV-1 reverse transcriptase (RT), triosephosphate isomerase (TIM), and the 70S ribosomal complex. The generated ensembles of conformers determined at atomic resolution show good agreement with experimental data (979 structures resolved by X-ray and/or NMR) and encompass the subspaces covered in independent MD simulations for TIM, p38, and RT. ClustENM emerges as a computationally efficient tool for characterizing the conformational space of large systems at atomic detail, in addition to generating a representative ensemble of conformers that can be advantageously used in simulating substrate/ligand-binding events.

Predicting protein conformational changes for unbound and homology docking: learning from intrinsic and induced flexibility

“…One example would be a discriminative force field that samples conformations in Boltzmann rather than uniform distribution, and such a force field might need to consider both conformational selection and induced fit effects. Several recent studies are following the direction with promising results.…”

Exploring Allosteric Signaling in the Exit Tunnel of the Bacterial Ribosome by Molecular Dynamics Simulations and Residue Network Model

“…The crystal structure of T. thermophilus ribosomal complex with PDB ID 4v5d of resolution 3.5 Å contains 70S with A-, P-, E-tRNAs, and mRNA (Voorhees et al, 2009). In addition, large subunit 50S from 101 different conformers of the T. thermophilus ribosomal complex (PDB ID 4v9m of resolution 4.0 Å) with elongation factor G previously generated by ClustENM (Kurkcuoglu et al, 2016) are used. ClustENM is an iterative algorithm, which generates plausible full-atom conformers by deformation along with the collective modes of the elastic network model.…”

“…To reveal any similarities in potential allosteric communication pathways between bacterial species, the ribosomal complex of T. thermophilus (PDB ID: 4v5d) is studied with the PRS using 500 ns long coarse-grained molecular dynamics simulations. Then, k-shortest pathways of 101 conformers of the ribosomal complex of T. thermophilus previously generated by ClustENM (Kurkcuoglu et al, 2016) using PDB ID 4v9m (Zhou et al, 2013) are calculated. Although the specific interactions between the nascent chain and the ribosomal tunnel are critical in the sequence-dependent arrest of translation, the dynamical traits of nucleotides for this task must strongly rely on the topology of the structure.…”

Advances in image processing for single-particle analysis by electron cryomicroscopy and challenges ahead

“…The method performed a large number of MD simulations, each of them corresponding to the excitation of a randomly determined linear combination of selected normal modes. Similarly, in [110] combinations of ANMs were used to calculate the conformational space for a molecule, and a clustering procedure was applied to construct representative substates.…”