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Title: Connecting the Kinetics and Energy Landscape of tRNA Translocation on the Ribosome}
Article:
Abstract:
Functional rearrangements in biomolecular assemblies result from diffusion across an underlying energy landscape. While bulk kinetic measurements rely on discrete state-like approximations to the energy landscape, single-molecule methods can project the free energy onto specific coordinates. With measures of the diffusion, one may establish a quantitative bridge between state-like kinetic measurements and the continuous energy landscape. We used an all-atom molecular dynamics simulation of the 70S ribosome( 2. 1 million atoms; 1. 3 microseconds) to provide this bridge for specific conformational events associated with the process of tRNA translocation. Starting from a pre-translocation configuration, we identified sets of residues that collectively undergo rotary rearrangements implicated in ribosome function. Estimates of the diffusion coefficients along these collective coordinates for translocation were then used to interconvert between experimental rates and measures of the energy landscape. This analysis, in conjunction with previously reported experimental rates of translocation, provides an upper-bound estimate of the free-energy barriers associated with translocation. While this analysis was performed for a particular kinetic scheme of translocation, the quantitative framework is general and may be applied to energetic and kinetic descriptions that include any number of intermediates and transition states.
Introduction:
Biological machines are ubiquitous in the cell and typically contain many molecules that include protein, RNA, and other cofactors. Each molecule provides a unique contribution to an assembly's energy landscape, which then governs the machine's function. Accordingly, quantifying the landscape's features and molecular origins may allow one to precisely manipulate the physical-chemical properties that dictate the biological dynamics. Despite the pressing need for a quantitative description of the energy landscapes that underpin function, most experimental techniques report on the rates of interconversion between states, where each state is a discretized approximation to an energetic basin. To bridge discrete and continuous descriptions for a molecular machine, such as the ribosome, it is necessary to quantify the diffusive properties of functionally-relevant collective rearrangements. The observed, or effective, diffusion of each component of a biomolecular complex is determined by the intrinsic diffusion of that component( free in solution) as well as the short-scale energetic roughness that is introduced by molecular interfaces[1]–[5]. In other words, the landscape is characterized by energetic barriers that are associated with a hierarchy of length scales( Fig. 1)[6],[7], where the effective diffusion is dictated by the magnitude of the short length-scale roughness. Structural rearrangements may then be described by effective( short length-scale averaged) diffusion on a smooth, large-scale, energy landscape. By measuring the effective diffusion, one may determine the relationship between the long length-scale free-energy barriers and the kinetics associated with interconversion between well-defined states. The ribosome has long been considered to function as a “thermal ratchet machine”[8], in that random energetic fluctuations that result from finite temperatures lead to large-scale diffusive( i. e. Brownian) configurational rearrangements. While smFRET and simulations directly monitor diffusive movement across the landscape, kinetic and structural measures utilize discrete state-like approximations to describe a molecule's dynamics. These seemingly disparate perspectives can be rationalized by adopting energy landscape theory[9],[10], which was developed in the context of protein folding and then extended to describe functional dynamics[11]–[15]. To this end, we have combined all-atom molecular dynamics simulations and principles from energy landscape theory to provide the quantities necessary to describe large-scale collective dynamics in the ribosome. To achieve this, we analyzed the dynamics of an explicit-solvent simulation of an intact ribosome to identify groups of residues that undergo collective rotations/displacements. From this, we identified collective reaction coordinates that capture 30S-body rotation( i. e. “ratchet-like” motion), 30S-head swivel and tRNA displacements( Fig. 2 and 3), which are essential motions during substrate translocation( i. e. the directional movement of tRNA and mRNA molecules, with respect to the ribosomal subunits; described in detail in Text S1)[16],[17]. In a continuous 1. 3 microsecond explicit-solvent simulation of the pre-translocation complex, frequent small-scale body-rotation, head-swiveling and tRNA fluctuations were observed, from which effective diffusion coefficients were calculated in each coordinate space( Fig. 4). Full body and head rotation during translocation encompass angular displacements of and[18]–[23]. Smaller net rotations( and) were observed in the simulation. Dynamics of the pre-translocation complex provided quantitative measures of the short time-scale( 10–100 ns) fluctuations and effective diffusion in each space, which were used to relate the kinetics and free-energy barriers of translocation. From this analysis, we provide experimentally-grounded upper bounds for the long length-scale barriers associated with translocation, as well as estimates for the magnitude of the short-scale energetic roughness.
Discussion:
The ability to rigorously interconvert between the energy landscape and kinetics will be essential in order to unambiguously quantify the features of the biomolecular landscapes that underpin function. With knowledge of the diffusive properties, theoretical and experimental probes of the energy landscape may be directly compared to kinetic measurements, which will enable a comprehensive picture of the landscape to emerge. Thus, the diffusion provides a unifying foundation for understanding and interpreting all available data for a given biological process. In the presented study, we have made the first steps towards establishing such a framework for tRNA translocation in the ribosome. To do this, we probed the diffusive characteristics of subunit rotations and tRNA displacements, essential sub-processes that facilitate protein elongation in the cell. As computer hardware continues to increase in power, and new computational algorithms and models are developed, the current study will provide the context for understanding a gamut of biophysical measurements and predictions. Of particular interest are the detailed features of the underlying energy landscape, as well as the robustness of ribosome dynamics to external perturbations. Similar to macroscopic machines, by understanding the interplay between the moving parts of these systems, it may be possible to design strategies to exploit this knowledge and provide precise regulation of biomolecular dynamics in the cell. In such efforts, the presented approach for bridging kinetics and free-energies provides a way to systematically verify predictions about the landscape against experimental data. These tools allow us to integrate complementary information from experimental and computational techniques, which will be crucial when identifying the features of the energy landscapes that govern biological function.
With a comprehensive understanding of the underlying energetics for a biomolecular machine , such as the ribosome , we may quantitatively identify the essential factors that determine function . In molecular-level machines , the energetic fluctuations arising from the surrounding solvent become comparable to the energetics that direct each process . In this regime , structural rearrangements may be described as diffusive movements across a free-energy landscape . By adopting this framework , it is possible to quantitatively relate theoretical predictions , computational results , experimental rates and biochemical data , which will allow for a self-consistent description to be obtained . To this end , we have used an explicit-solvent simulation ( 2 . 1 million atoms , 1 . 3 microseconds ) to measure the diffusion along multiple structural coordinates that have been implicated in tRNA translocation in the ribosome . With the diffusion coefficients in hand , we demonstrate how they may be used to bridge theoretical and experimental descriptions of complex collective dynamics in a molecular machine .