Exploring the Energy Landscape of Riboswitches Using Collective Variables Based on Tertiary Contacts

Abstract

Messenger RNA regulatory elements, such as riboswitches, can display a high degree of flexibility. By characterizing their energy landscapes, and corresponding distributions of 3D configurations, structure-function relationships can be elucidated. Molecular dynamics simulation with enhanced sampling is an important strategy used to computationally access free energy landscapes characterizing the accessible 3D conformations of RNAs. While tertiary contacts are thought to play important roles in RNA dynamics, it is difficult, in explicit solvent, to sample the formation and breakage of tertiary contacts, such as helix-helix interactions, pseudoknot interactions, and junction interactions, while maintaining intact secondary structure elements. To this end, we extend previously developed collective variables and metadynamics efforts, to establish a simple metadynamics protocol, which utilizes only one collective variable, based on multiple tertiary contacts, to characterize the underlying free energy landscape of any RNA molecule. We develop a modified collective variable, the tertiary contacts distance (Q_TC), which can probe the formation and breakage of all or selectively chosen tertiary contacts of the RNA. The SAM-I riboswitch in the presence of three ionic and substrate conditions was investigated and validated against the structure ensemble previously generated using SAXS experiments. This efficient and easy to implement all-atom MD simulation based approach incorporating metadynamics to study RNA conformational dynamics can also be transferred to any other type of biomolecule.

Keywords: SAM-I Riboswitch; collective variable; contact distance; free energy; metadynamics.

Figure 1:

(A) Secondary structure of the aptamer domain of SAM-I riboswitch from Thermoanaerobacter tengcongensis bacterium, highlighting the tertiary architecture [36]. Different structural domains are colored as well as labelled as follows: P, helices; J, joining loops; PK, pseudoknot; KT, kink-turn. (B) Three dimensional structure of SAM-I aptamer domain in cartoon representation is depicted with the SAM ligand in van der Waals representation (PDB ID: 3IQR) [37].

Figure 2:

(A) Superimposition of seven conformations of SAM-I based on the SAXS experiments [37]. (B) Four tertiary contacts forming regions along the SAM-I structure are illustrated as surface and labelled according to the secondary structure elements involved. Additional labels d₁ to d₄ correspond to collective variables used during WTmetaD simulations. (C) Depiction of the normalization of collective variables d₁ to d₄ to new ones $d_1^{\prime }$ to $d_4^{\prime }$ using Eq. 6. (D) Time evolution of collective variable $Q_{TC}$ for eight walkers during a WTmetaD simulation performed for the system having a SAM bound SAM-I in the presence of 150 mM KCl and 7.6 mM MgCl₂.

Figure 3:

(A) 1D free energy surfaces as a function of collective variable $Q_{TC}$ from WTmetaD simulations performed for SAM-I in three different ionic/ligand conditions. Error bars indicate the statistical error determined after averaging eight independent runs in each case. (B) Three panels depict 2D free energy landscapes with respect to collective variables $Q_{TC}$ and RMSD determined from same three sets of simulations. Metastable states found along the landscapes are numbered. (C) Superimposition of the representative conformations of SAM-I from six metastable states (1-5 and 10) identified along the 2D free energy surface of the system having only 150 mM KCl. (D) 1D free energy profiles with respect to collective variables d₁ to d₄, which represent the four tertiary bonds forming areas, derived for all three SAM-I setups and depicted in three panels. The numbers indicate the energy difference between the native state (d₁₋₄ ≈ 0.5 nm) and the upper bound of each collective variable (d₁ ≈ 3.9 nm; d₂₋₄ ≈ 1.9 nm). Note that in all panels, free energy estimates for few upper/lower bound values of collective variables are not depicted, because they do not seem to be converged due to the boundary effect.