The Elastic Network Contact Model applied to RNA: enhanced accuracy for conformational space prediction

Abstract

Motivation:The use of Normal Mode Analysis (NMA) methods to study both protein and nucleic acid dynamics is well established. However, the most widely used coarse-grained methods are based on backbone geometry alone and do not take into account the chemical nature of the residues. Elastic Network Contact Model (ENCoM) is a coarse-grained NMA method that includes a pairwise atom-type non-bonded interaction term, which makes it sensitive to the sequence of the studied molecule. We adapted ENCoM to simulate the dynamics of ribonucleic acid (RNA) molecules.

Advances in coarse-grained modeling of macromolecular complexes

“…Importantly, many recent CG models have opted to hybridize both network-based and native-contact-based approaches [35,36,40–43]; for example, a network model could represent different intra-protein conformers, while a native-contact model represents inter-protein interfaces. Indeed, this type of approach is well-suited for studies of large-scale macromolecular complexes.…”

“…For instance, parameter sets for network models have been introduced that delineate different inter-residue coupling forces to reproduce experimental Debye-Waller factors [46]. On the basis of statistical distributions of residue contacts observed in training sets of experimental structures, it is possible to formulate hybrid network/native-contact models that capture pairwise energies [47], vibrational entropies [42,43], relative entropies [48,49], and maintained contacts [50]. In the case of intrinsically disordered proteins, in which native states are largely unknown, large datasets of radius of gyrations were used to parameterize effective CG potentials.…”

Enhancements of the Gaussian network model in describing nucleotide residue fluctuations for RNA

“…It is found that EN-CoM can better simulate the dynamics of RNA compared with the conventional ENM. [32] Moreover, the study of Wang et al illustrated that a multiscale ENM, in which the multiscale harmonic interactions with variable force constants were adopted, distinctly improves the characterization of the dynamical properties of RNA. However, in the multiscale ENM, the force constants need to be optimized by using the experimental Bfactors for each studied RNA molecule separately, and thus the optimized model for one RNA molecule is not generally applicable for other RNA systems.…”