Exploring global motions and correlations in the ribosome

Atomistic simulations of the Escherichia coli ribosome provide selection criteria for translationally active substrates

As genetic code expansion advances beyond L-α-amino acids to backbone modifications and new polymerization chemistries, delineating what substrates the ribosome can accommodate remains a challenge. The Escherichia coli ribosome tolerates non-L-α-amino acids in vitro, but few structural insights that explain how are available, and the boundary conditions for efficient bond formation are so far unknown. Here we determine a high-resolution cryogenic electron microscopy structure of the E. coli ribosome containing α-amino acid monomers and use metadynamics simulations to define energy surface minima and understand incorporation efficiencies. Reactive monomers across diverse structural classes favour a conformational space where the aminoacyl-tRNA nucleophile is <4 Å from the peptidyl-tRNA carbonyl with a Bürgi-Dunitz angle of 76-115°. Monomers with free energy minima that fall outside this conformational space do not react efficiently. This insight should accelerate the in vivo and in vitro ribosomal synthesis of sequence-defined, non-peptide heterooligomers.

R, de Oliveira R, Dunham C, Whitford P. Ratchet, swivel, tilt and roll: a complete description of subunit rotation in the ribosome

Protein synthesis by the ribosome requires large-scale rearrangements of the 'small' subunit (SSU; ∼1 MDa), including inter- and intra-subunit rotational motions. However, with nearly 2000 structures of ribosomes and ribosomal subunits now publicly available, it is exceedingly difficult to design experiments based on analysis of all known rotation states. To overcome this, we developed an approach where the orientation of each SSU head and body is described in terms of three angular coordinates (rotation, tilt and tilt direction) and a single translation. By considering the entire RCSB PDB database, we describe 1208 fully-assembled ribosome complexes and 334 isolated small subunits, which span >50 species. This reveals aspects of subunit rearrangements that are universal, and others that are organism/domain-specific. For example, we show that tilt-like rearrangements of the SSU body (i.e. 'rolling') are pervasive in both prokaryotic and eukaryotic (cytosolic and mitochondrial) ribosomes. As another example, domain orientations associated with frameshifting in bacteria are similar to those found in eukaryotic ribosomes. Together, this study establishes a common foundation with which structural, simulation, single-molecule and biochemical efforts can more precisely interrogate the dynamics of this prototypical molecular machine.

Hyper-swivel head domain motions are required for complete mRNA-tRNA translocation and ribosome resetting

Translocation of messenger RNA (mRNA) and transfer RNA (tRNA) substrates through the ribosome during protein synthesis, an exemplar of directional molecular movement in biology, entails a complex interplay of conformational, compositional, and chemical changes. The molecular determinants of early translocation steps have been investigated rigorously. However, the elements enabling the ribosome to complete translocation and reset for subsequent protein synthesis reactions remain poorly understood. Here, we have combined molecular simulations with single-molecule fluorescence resonance energy transfer imaging to gain insights into the rate-limiting events of the translocation mechanism. We find that diffusive motions of the ribosomal small subunit head domain to hyper-swivelled positions, governed by universally conserved rRNA, can maneuver the mRNA and tRNAs to their fully translocated positions. Subsequent engagement of peptidyl-tRNA and disengagement of deacyl-tRNA from mRNA, within their respective small subunit binding sites, facilitate the ribosome resetting mechanism after translocation has occurred to enable protein synthesis to resume.

The energetics of subunit rotation in the ribosome

Protein synthesis in the cell is controlled by an elaborate sequence of conformational rearrangements in the ribosome. The composition of a ribosome varies by species, though they typically contain ∼ 50-100 RNA and protein molecules. While advances in structural techniques have revolutionized our understanding of long-lived conformational states, a vast range of transiently visited configurations can not be directly observed. In these cases, computational/simulation methods can be used to understand the mechanical properties of the ribosome. Insights from these approaches can then help guide next-generation experimental measurements. In this short review, we discuss theoretical strategies that have been deployed to quantitatively describe the energetics of collective rearrangements in the ribosome. We focus on efforts to probe large-scale subunit rotation events, which involve the coordinated displacement of large numbers of atoms (tens of thousands). These investigations are revealing how the molecular structure of the ribosome encodes the mechanical properties that control large-scale dynamics.

A generic force field for simulating native protein structures using dissipative particle dynamics

A coarse-grained force field for molecular dynamics simulations of the native structures of proteins in a dissipative particle dynamics (DPD) framework is developed. The parameters for bonded interactions are derived by mapping the bonds and angles for 20 amino acids onto target distributions obtained from fully atomistic simulations in explicit solvent. A dual-basin potential is introduced for stabilizing backbone angles, to cover a wide spectrum of protein secondary structures. The backbone dihedral potential enables folding of the protein from an unfolded initial state to the folded native structure. The proposed force field is validated by evaluating the structural properties of several model peptides and proteins including the SARS-CoV-2 fusion peptide, consisting of α-helices, β-sheets, loops and turns. Detailed comparisons with fully atomistic simulations are carried out to assess the ability of the proposed force field to stabilize the different secondary structures present in proteins. The compact conformations of the native states were evident from the radius of gyration and the high intensity peaks of the root mean square deviation histograms, which were found to be within 0.4 nm. The Ramachandran-like energy landscape on the phase space of backbone angles (θ) and dihedrals (ϕ) effectively captured the conformational phase space of α-helices at ∼(ϕ = 50°,θ = 90°) and β-strands at ∼(ϕ = ±180°,θ = 90-120°). Furthermore, the residue-residue native contacts were also well reproduced by the proposed DPD model. The applicability of the model to multidomain complexes was assessed using lysozyme and a large α-helical bacterial pore-forming toxin, cytolysin A. Our study illustrates that the proposed force field is generic, and can potentially be extended for efficient in silico investigations of membrane bound polypeptides and proteins using DPD simulations.

RNA 3D Structure Prediction Using Coarse-Grained Models

The three-dimensional (3D) structures of Ribonucleic acid (RNA) molecules are essential to understanding their various and important biological functions. However, experimental determination of the atomic structures is laborious and technically difficult. The large gap between the number of sequences and the experimentally determined structures enables the thriving development of computational approaches to modeling RNAs. However, computational methods based on all-atom simulations are intractable for large RNA systems, which demand long time simulations. Facing such a challenge, many coarse-grained (CG) models have been developed. Here, we provide a review of CG models for modeling RNA 3D structures, compare the performance of the different models, and offer insights into potential future developments.

Organic nanoelectronics inside us: charge transport and localization in RNA could orchestrate ribosome operation

Translation - protein synthesis at the ribonucleic acid (RNA) based molecular machine, the ribosome, - proceeds in a similar manner in all life forms. However, despite several decades of research, the physics underlying this process remains enigmatic. Specifically, during translation, a ribosome undergoes large-scale conformational changes of its distant parts, and these motions are coordinated by an unknown mechanism. In this study, we suggest that such a mechanism could be related to charge (electron hole) transport along and between the RNA molecules, localization of these charges at certain sites and successive relaxation of the molecular geometry. Thus, we suppose that RNA-based molecular machines, e.g., the ribosome, could be electronically controlled, having "wires", "actuators", "a battery", and other "circuitry". Taking transfer RNA as an example, we justify the reasonability of our suggestion using ab initio and atomistic simulations. Specifically, very large hole transfer integrals between the nucleotides (up to above 100 meV) are observed so that the hole can migrate over nearly the whole tRNA molecule. Hole localization at several guanines located at functionally important sites (G27, G10, G34 and G63) is predicted, which is shown to induce geometry changes in these sites, their neighborhoods and even rather distant moieties. If our hypothesis is right, we anticipate that our findings will qualitatively advance the understanding of the key biological processes and could inspire novel approaches in medicine.

Local and Global Motions Underlying Antibiotic Binding in Bacterial Ribosome

The bacterial ribosome is one of the most important targets in the treatment of infectious diseases. As antibiotic resistance in bacteria poses a growing threat, a significant amount of effort is concentrated on exploring new drug-binding sites where testable predictions are of significance. Here, we study the dynamics of a ribosomal complex and 67 small and large subunits of the ribosomal crystal structures (64 antibiotic-bound, 3 antibiotic-free) from Deinococcus radiodurans, Escherichia coli, Haloarcula marismortui, and Thermus thermophilus by the Gaussian network model. Interestingly, a network of nucleotides coupled in high-frequency fluctuations reveals known antibiotic-binding sites. These sites are seen to locate at the interface of dynamic domains that have an intrinsic dynamic capacity to interfere with functional globular motions. The nucleotides and the residues fluctuating in the fast and slow modes of motion thus have promise for plausible antibiotic-binding and allosteric sites that can alter antibiotic binding and resistance. Overall, the present analysis brings a new dynamic perspective to the long-discussed link between small-molecule binding and large conformational changes of the supramolecule.

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

The bacterial ribosomal tunnel is equipped with numerous sites highly sensitive to the course of the translation process. This study investigates allosteric pathways linking distant functional sites that collaboratively play a role either in translation regulation or recruitment of chaperones. We apply perturbation response scanning (PRS) analysis to 700 ns long and 500 ns long coarse-grained molecular dynamics simulations of E. coli and T. thermophilus large subunits, respectively, to reveal nucleotides/residues with the ability to transmit perturbations by dynamic rationale. We also use the residue network model with the k-shortest pathways method to calculate suboptimal pathways based on the contact topology of the ribosomal tunnel of E. coli crystal structure and 101 ClustENM generated conformers of T. thermophilus large subunit. In the upper part of the tunnel, results suggest that A2062 and A2451 can communicate in both directions for translation stalling, mostly through dynamically coupled C2063, C2064, and A2450. For a similar purpose, U2585 and U2586 are coupled with A2062, while they are also sensitive to uL4 and uL22 at the constriction region through two different pathways at the opposite sides of the tunnel wall. In addition, the constriction region communicates with the chaperone binding site on uL23 at the solvent side but through few nucleotides. Potential allosteric communication pathways between the lower part of the tunnel and chaperone binding site mostly use the flexible loop of uL23, while A1336–G1339 provide a suboptimal pathway. Both species seem to employ similar mechanisms in the long tunnel, where a non-conserved cavity at the bacterial uL23 and 23S rRNA interface is proposed as a novel drug target.

Large-scale simulations of nucleoprotein complexes: ribosomes, nucleosomes, chromatin, chromosomes and CRISPR

Recent advances in biotechnology such as Hi-C, CRISPR/Cas9 and ribosome display have placed nucleoprotein complexes at center stage. Understanding the structural dynamics of these complexes aids in optimizing protocols and interpreting data for these new technologies. The integration of simulation and experiment has helped advance mechanistic understanding of these systems. Coarse-grained simulations, reduced-description models, and explicit solvent molecular dynamics simulations yield useful complementary perspectives on nucleoprotein complex structural dynamics. When combined with Hi-C, cryo-EM, and single molecule measurements, these simulations integrate disparate forms of experimental data into a coherent mechanism.

Coarse-Grained Simulation of Full-Length Integrin Activation

Integrin conformational dynamics are critical to their receptor and signaling functions in many cellular processes, including spreading, adhesion, and migration. However, assessing integrin conformations is both experimentally and computationally challenging because of limitations in resolution and dynamic sampling. Thus, structural changes that underlie transitions between conformations are largely unknown. Here, focusing on integrin αvβ₃, we developed a modified form of the coarse-grained heterogeneous elastic network model (hENM), which allows sampling conformations at the onset of activation by formally separating local fluctuations from global motions. Both local fluctuations and global motions are extracted from all-atom molecular dynamics simulations of the full-length αvβ₃ bent integrin conformer, but whereas the former are incorporated in the hENM as effective harmonic interactions between groups of residues, the latter emerge by systematically identifying and treating weak interactions between long-distance domains with flexible and anharmonic connections. The new hENM model allows integrins and single-point mutant integrins to explore various conformational states, including the initiation of separation between α- and β-subunit cytoplasmic regions, headpiece extension, and legs opening.

Anisotropic Fluctuations in the Ribosome Determine tRNA Kinetics

The ribosome is a large ribonucleoprotein complex that is responsible for the production of proteins in all organisms. Accommodation is the process by which an incoming aminoacyl-tRNA (aa-tRNA) molecule binds the ribosomal A site, and its kinetics has been implicated in the accuracy of tRNA selection. In addition to rearrangements in the aa-tRNA molecule, the L11 stalk can undergo large-scale anisotropic motions during translation. To explore the potential impact of this protruding region on the rate of aa-tRNA accommodation, we used molecular dynamics simulations with a simplified model to evaluate the free energy as a function of aa-tRNA position. Specifically, these calculations describe the transition between A/T and elbow-accommodated (EA) configurations (∼20 Å displacement). We find that the free-energy barrier associated with elbow accommodation is proportional to the degree of mobility exhibited by the L11 stalk. That is, when L11 is more rigid, the free-energy barrier height is decreased. This effect arises from the ability of L11 to confine, and thereby destabilize, the A/T ensemble. In addition, when elongation factor Tu (EF-Tu) is present, the A/T ensemble is further destabilized in an L11-dependent manner. These results provide a framework that suggests how next-generation experiments may precisely control the dynamics of the ribosome.

Analysis of ribosomal inter-subunit sites as targets for complementary oligonucleotides

The bacterial ribosome has many functional ribosomal RNA (rRNA) sites. We have computationally analyzed the rRNA regions involved in the interactions between the 30S and 50S subunits. Various properties of rRNA such as solvent accessibility, opening energy, hydrogen bonding pattern, van der Waals energy, thermodynamic stability were determined. Based on these properties we selected rRNA targets for hybridization with complementary 2'-O-methyl oligoribonucleotides (2'-OMe RNAs). Further, the inhibition efficiencies of the designed ribosome-interfering 2'-OMe RNAs were tested using a β-galactosidase assay in a translation system based on the E. coli extract. Several of the oligonucleotides displayed IC₅₀ values below 1 μM, which were in a similar range as those determined for known ribosome inhibitors, tetracycline and pactamycin. The calculated opening and van der Waals stacking energies of the rRNA targets correlated best with the inhibitory efficiencies of 2'-OMe RNAs. Moreover, the binding affinities of several oligonucleotides to both 70S ribosomes and isolated 30S and 50S subunits were measured using a double-filter retention assay. Further, we applied heat-shock chemical transformation to introduce 2'-OMe RNAs to E. coli cells and verify inhibition of bacterial growth. We observed high correlation between IC₅₀ in the cell-free extract and bacterial growth inhibition. Overall, the results suggest that the computational analysis of potential rRNA targets within the conformationally dynamic regions of inter-subunit bridges can help design efficient antisense oligomers to probe the ribosome function.

A better prediction of conformational changes of proteins using minimally connected network models

Elastic network models have recently been used for studying low-frequency collective motions of proteins. These models simplify the complexity that arises from normal mode analysis by considering a simplified potential involving a few parameters. Two common parameters in most of the elastic network models are cutoff radius and force constant. Although the latter has been studied extensively and even elaborate new models were introduced, for the former usually an ad-hoc cutoff radius is considered. Moreover, the quality of the network models is usually assessed by evaluating their prediction against experimental B-factors. In this work, we consider various common elastic network models with different cutoff radii and assess them by their ability to predict conformational changes of proteins in complexes from unbound to bound state. This prediction is performed by perturbing the unbound structure using a number of low-frequency normal modes of its network model to optimally fit the bound structure. We evaluated a dataset of 30 proteins with distinct unbound and bound structures using this criterion. The results showed that, opposed to the common calibration process based on B-factors, a meaningful relationship exists between the quality of the prediction and model parameters. It was shown that the cutoff radius has a major role in this prediction and minimally connected network models, which use the shortest cutoff radius for which the network is stable, give the best results. It was also shown that by considering the first ten normal modes, the conformational changes can be predicted by about 25 percent. Hence, the evaluation process was extended to the case of considering the contribution of all normal modes in the prediction. The results indicated that minimally connected network models are superior, despite their simplicity, when any number of modes are considered in the prediction.

The fluctuating ribosome: thermal molecular dynamics characterized by neutron scattering

Conformational changes associated with ribosome function have been identified by X-ray crystallography and cryo-electron microscopy. These methods, however, inform poorly on timescales. Neutron scattering is well adapted for direct measurements of thermal molecular dynamics, the ‘lubricant’ for the conformational fluctuations required for biological activity. The method was applied to compare water dynamics and conformational fluctuations in the 30 S and 50 S ribosomal subunits from Haloarcula marismortui, under high salt, stable conditions. Similar free and hydration water diffusion parameters are found for both subunits. With respect to the 50 S subunit, the 30 S is characterized by a softer force constant and larger mean square displacements (MSD), which would facilitate conformational adjustments required for messenger and transfer RNA binding. It has been shown previously that systems from mesophiles and extremophiles are adapted to have similar MSD under their respective physiological conditions. This suggests that the results presented are not specific to halophiles in high salt but a general property of ribosome dynamics under corresponding, active conditions. The current study opens new perspectives for neutron scattering characterization of component functional molecular dynamics within the ribosome.

Determination of contact maps in proteins: A combination of structural and chemical approaches

Contact map selection is a crucial step in structure-based molecular dynamics modelling of proteins. The map can be determined in many different ways. We focus on the methods in which residues are represented as clusters of effective spheres. One contact map, denoted as overlap (OV), is based on the overlap of such spheres. Another contact map, named Contacts of Structural Units (CSU), involves the geometry in a different way and, in addition, brings chemical considerations into account. We develop a variant of the CSU approach in which we also incorporate Coulombic effects such as formation of the ionic bridges and destabilization of possible links through repulsion. In this way, the most essential and well defined contacts are identified. The resulting residue-residue contact map, dubbed repulsive CSU (rCSU), is more sound in its physico-chemical justification than CSU. It also provides a clear prescription for validity of an inter-residual contact: the number of attractive atomic contacts should be larger than the number of repulsive ones - a feature that is not present in CSU. However, both of these maps do not correlate well with the experimental data on protein stretching. Thus, we propose to use rCSU together with the OV map. We find that the combined map, denoted as OV+rCSU, performs better than OV. In most situations, OV and OV+rCSU yield comparable folding properties but for some proteins rCSU provides contacts which improve folding in a substantial way. We discuss the likely residue-specificity of the rCSU contacts. Finally, we make comparisons to the recently proposed shadow contact map, which is derived from different principles.

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

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.

Steric interactions lead to collective tilting motion in the ribosome during mRNA-tRNA translocation

Translocation of mRNA and tRNA through the ribosome is associated with large-scale rearrangements of the head domain in the 30S ribosomal subunit. To elucidate the relationship between 30S head dynamics and mRNA–tRNA displacement, we apply molecular dynamics simulations using an all-atom structure-based model. Here we provide a statistical analysis of 250 spontaneous transitions between the A/P–P/E and P/P–E/E ensembles. Consistent with structural studies, the ribosome samples a chimeric ap/P–pe/E intermediate, where the 30S head is rotated ∼18°. It then transiently populates a previously unreported intermediate ensemble, which is characterized by a ∼10° tilt of the head. To identify the origins of head tilting, we analyse 781 additional simulations in which specific steric features are perturbed. These calculations show that head tilting may be attributed to specific steric interactions between tRNA and the 30S subunit (PE loop and protein S13). Taken together, this study demonstrates how molecular structure can give rise to large-scale collective rearrangements.

During protein elongation, the translocation of mRNA and tRNA molecules across the 30S ribosomal subunit is associated with large-scale motions of the 30S head domain. Here the authors carry out MD simulations to probe the associated steric interactions and identify novel tilting motions during the late stages of translocation.

Ribosome Mechanics Informs about Mechanism

The essential aspects of the ribosome's mechanism can be extracted from coarse-grained simulations, including the ratchet motion, the movement together of critical bases at the decoding center, and movements of the peptide tunnel lining that assist in the expulsion of the synthesized peptide. Because of its large size, coarse graining helps to simplify and to aid in the understanding of its mechanism. Results presented here utilize coarse-grained elastic network modeling to extract the dynamics, and both RNAs and proteins are coarse grained. We review our previous results, showing the well-known ratchet motions and the motions in the peptide tunnel and in the mRNA tunnel. The motions of the lining of the peptide tunnel appear to assist in the expulsion of the growing peptide chain, and clamps at the ends of the mRNA tunnel with three proteins ensure that the mRNA is held tightly during decoding and essential for the helicase activity at the entrance. The entry clamp may also assist in base recognition to ensure proper selection of the incoming tRNA. The overall precision of the ribosome machine-like motions is remarkable.

Computing the Amino Acid Specificity of Fluctuations in Biomolecular Systems

We developed a new amino acid specific method for the computation of spatial fluctuations of proteins around their native structures. We show the consistency with experimental values and the increased performance in comparison to an established model, based on statistical estimates for a set of test proteins. We apply the new method to HIV-1 protease in its wild-type form and to a V82F-I84V mutant that shows resistance to protease inhibitors. We further show how the method can be successfully used to explain the molecular biophysics of drug resistance of the mutant.

The ribosome's energy landscape: Recent insights from computation

The ever-increasing capacity of computing resources has extended ribosome calculations from the study of small-scale fluctuations to large-scale barrier-crossing processes. As the field of computational/theoretical biophysics shifts focus to large-scale conformational transitions, there is a growing need for a systematic framework to interpret and analyze ribosome dynamics. To this end, energy landscape principles, largely developed for the study of biomolecular folding, have proven to be invaluable. These tools not only provide a foundation for describing simulations but can be used to reconcile experimental results, as well. In this review, I will discuss recent efforts to employ computational methods to reveal the characteristics of the ribosome's landscape and how these studies can help guide a new generation of experiments that more closely probe the underlying energetics. As a result of these investigations, general principles about ribosome function are beginning to emerge, including that: (1) small-scale fluctuations are the result of structure, rather than detailed energetics, (2) molecular flexibility leads to entropically favored rearrangements, and (3) tRNA dynamics may be accurately described as diffusive movement across an energy landscape.

RedMDStream: Parameterization and Simulation Toolbox for Coarse-Grained Molecular Dynamics Models

Coarse-grained (CG) models in molecular dynamics (MD) are powerful tools to simulate the dynamics of large biomolecular systems on micro- to millisecond timescales. However, the CG model, potential energy terms, and parameters are typically not transferable between different molecules and problems. So parameterizing CG force fields, which is both tedious and time-consuming, is often necessary. We present RedMDStream, a software for developing, testing, and simulating biomolecules with CG MD models. Development includes an automatic procedure for the optimization of potential energy parameters based on metaheuristic methods. As an example we describe the parameterization of a simple CG MD model of an RNA hairpin.

A multi-scale-multi-stable model for the rhodopsin photocycle

We report a multi-scale simulation study of the photocycle of the rhodopsins. The quasi-atomistic representation ("united atoms" UA) of retinal is combined with a minimalist coarse grained (CG, one-bead-per amino acid) representation of the protein, in a hybrid UA/CG approach, which is the homolog of QM/MM, but at lower resolution. An accurate multi-stable parameterization of the model allows simulating each state and transition among them, and the combination of different scale representation allows addressing the entire photocycle. We test the model on bacterial rhodopsin, for which more experimental data are available, and then also report results for mammalian rhodopsins. In particular, the analysis of simulations reveals the spontaneous appearance of meta-stable states in quantitative agreement with experimental data.

Minimalist Model for the Dynamics of Helical Polypeptides: A Statistic-Based Parametrization

Low-resolution models are often used to address macroscopic time and size scales in molecular dynamics simulations of biomolecular systems. Coarse graining is often coupled to knowledge-based parametrization to obtain empirical potentials able to reproduce the system thermodynamic behavior. Here, a minimalist coarse grained (GC) model for the helical structures of proteins is reported. A knowledge-based parametrization strategy is coupled to the explicit inclusion of hydrogen-bonding-related terms, resulting in an accurate reproduction of the structure and dynamics of each single helical type, as well as the internal conformational variables correlation. The proposed strategy of basing the force field terms on real physicochemical interactions is transferable to different secondary structures. Thus, this work, though conclusive for helices, is to be considered the first of a series devoted to the application of the knowledge-based, physicochemical model to extended secondary structures and unstructured proteins.

Evolutionary Algorithm in the Optimization of a Coarse-Grained Force Field

Simulations using residue-scale coarse-grained models of biomolecules are less computationally demanding than simulations employing full-atomistic force fields. However, the coarse-grained models are often difficult and tedious to parametrize for certain applications. Therefore, a systematic and objective method to help develop or adapt the coarse-grained models is needed. We present an automatic method that implements an evolutionary algorithm to find a set of optimal force field parameters for a one-bead coarse-grained model. In addition to an optimized force field, parameter correlations and significance of the potential energy terms can be determined. The method is applied to two classes of problems: the dynamics of an RNA helix and the RNA structure prediction.

Connecting the kinetics and energy landscape of tRNA translocation on the ribosome

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.

Influence of thiostrepton binding on the ribosomal GTPase associated region characterized by molecular dynamics simulation

The thiostrepton antibiotic inhibits bacterial protein synthesis by binding to a cleft formed by the ribosomal protein L11 and 23S's rRNA helices 43-44 on the 70S ribosome. It was proposed from crystal structures that the ligand restricts L11's N-terminal movement and thus prevents proper translation factor binding. An exact understanding of thiostrepton's impact on the binding site's dynamics at atomistic resolution is still missing. Here we report an all-atom molecular dynamics simulations of the binary L11·rRNA and the ternary L11·rRNA·thiostrepton complex (rRNA = helices 43-44). We demonstrate that thiostrepton directly impacts the binding site's atomic and biomacromolecular dynamics.

Mechanistic insights into phosphopeptide--BRCT domain association: preorganization, flexibility, and phosphate recognition

Promiscuous proteins are commonly observed in biological systems, for example, in modular domains that recognize phosphopeptides during signal transduction. This promiscuous recognition is of fundamental interest in chemistry and biology but is challenging when designing phosphopeptides in silico for cell biology studies. To investigate promiscuous recognition and binding processes of phosphopeptides and the modular domain, we selected a domain essential in breast cancer-the breast-cancer-associated protein 1 (BRCA1) C-terminal (BRCT) repeats as our model system. We performed molecular dynamics simulations and detailed analyses of the dihedral space to study protein fluctuation and conformational changes with phosphopeptide binding. We also studied the association processes of phosphorylated and unphosphorylated peptides using Brownian dynamics with a coarse-grained model. We found that the BRCT domain is preorganized for phosphopeptide binding but has a moderate arrangement of side chains to form complexes with various types of phosphopeptides. Phosphopeptide binding restricts the system motion in general, while the nonpolar phosphopeptide becomes more flexible in the bound state. Our analysis found that the BRCT domain utilizes different mechanisms, usually termed lock and key, induced-fit, and population-shift/conformational-selection models, to recognize peptides with different features. Brownian dynamics simulations revealed that the charged phosphate group may not always accelerate peptide association processes, but it helps the phosphopeptide orient into binding pockets accurately and stabilizes the complex. This work provides insights into molecular recognition in the promiscuous protein system.

Mechanisms of SecM-mediated stalling in the ribosome

Nascent-peptide modulation of translation is a common regulatory mechanism of gene expression. In this mechanism, while the nascent peptide is still in the exit tunnel of the ribosome, it induces translational pausing, thereby controlling the expression of downstream genes. One example is SecM, which inhibits peptide-bond formation in the ribosome's peptidyl transferase center (PTC) during its own translation, upregulating the expression of the protein translocase SecA. Although biochemical experiments and cryo-electron microscopy data have led to the identification of some residues involved in SecM recognition, the full pathway of interacting residues that connect SecM to the PTC through the ribosome has not yet been conclusively established. Here, using the cryo-electron microscopy data, we derived the first (to our knowledge) atomic model of the SecM-stalled ribosome via molecular-dynamics flexible fitting, complete with P- and A-site tRNAs. Subsequently, we carried out simulations of native and mutated SecM-stalled ribosomes to investigate possible interaction pathways between a critical SecM residue, R163, and the PTC. In particular, the simulations reveal the role of SecM in altering the position of the tRNAs in the ribosome, and thus demonstrate how the presence of SecM in the exit tunnel induces stalling. Finally, steered molecular-dynamics simulations in which SecM was pulled toward the tunnel exit suggest how SecA interacting with SecM from outside the ribosome relieves stalling.

Structure and mechanical properties of the ribosomal L1 stalk three-way junction

The L1 stalk is a key mobile element of the large ribosomal subunit which interacts with tRNA during translocation. Here, we investigate the structure and mechanical properties of the rRNA H76/H75/H79 three-way junction at the base of the L1 stalk from four different prokaryotic organisms. We propose a coarse-grained elastic model and parameterize it using large-scale atomistic molecular dynamics simulations. Global properties of the junction are well described by a model in which the H76 helix is represented by a straight, isotropically flexible elastic rod, while the junction core is represented by an isotropically flexible spherical hinge. Both the core and the helix contribute substantially to the overall H76 bending fluctuations. The presence of wobble pairs in H76 does not induce any increased flexibility or anisotropy to the helix. The half-closed conformation of the L1 stalk seems to be accessible by thermal fluctuations of the junction itself, without any long-range allosteric effects. Bending fluctuations of H76 with a bulge introduced in it suggest a rationale for the precise position of the bulge in eukaryotes. Our elastic model can be generalized to other RNA junctions found in biological systems or in nanotechnology.

Biomolecular dynamics: order-disorder transitions and energy landscapes

While the energy landscape theory of protein folding is now a widely accepted view for understanding how relatively weak molecular interactions lead to rapid and cooperative protein folding, such a framework must be extended to describe the large-scale functional motions observed in molecular machines. In this review, we discuss (1) the development of the energy landscape theory of biomolecular folding, (2) recent advances toward establishing a consistent understanding of folding and function and (3) emerging themes in the functional motions of enzymes, biomolecular motors and other biomolecular machines. Recent theoretical, computational and experimental lines of investigation have provided a very dynamic picture of biomolecular motion. In contrast to earlier ideas, where molecular machines were thought to function similarly to macroscopic machines, with rigid components that move along a few degrees of freedom in a deterministic fashion, biomolecular complexes are only marginally stable. Since the stabilizing contribution of each atomic interaction is on the order of the thermal fluctuations in solution, the rigid body description of molecular function must be revisited. An emerging theme is that functional motions encompass order-disorder transitions and structural flexibility provides significant contributions to the free energy. In this review, we describe the biological importance of order-disorder transitions and discuss the statistical-mechanical foundation of theoretical approaches that can characterize such transitions.

A computational investigation on the connection between dynamics properties of ribosomal proteins and ribosome assembly

Assembly of the ribosome from its protein and RNA constituents has been studied extensively over the past 50 years, and experimental evidence suggests that prokaryotic ribosomal proteins undergo conformational changes during assembly. However, to date, no studies have attempted to elucidate these conformational changes. The present work utilizes computational methods to analyze protein dynamics and to investigate the linkage between dynamics and binding of these proteins during the assembly of the ribosome. Ribosomal proteins are known to be positively charged and we find the percentage of positive residues in r-proteins to be about twice that of the average protein: Lys+Arg is 18.7% for E. coli and 21.2% for T. thermophilus. Also, positive residues constitute a large proportion of RNA contacting residues: 39% for E. coli and 46% for T. thermophilus. This affirms the known importance of charge-charge interactions in the assembly of the ribosome. We studied the dynamics of three primary proteins from E. coli and T. thermophilus 30S subunits that bind early in the assembly (S15, S17, and S20) with atomic molecular dynamic simulations, followed by a study of all r-proteins using elastic network models. Molecular dynamics simulations show that solvent-exposed proteins (S15 and S17) tend to adopt more stable solution conformations than an RNA-embedded protein (S20). We also find protein residues that contact the 16S rRNA are generally more mobile in comparison with the other residues. This is because there is a larger proportion of contacting residues located in flexible loop regions. By the use of elastic network models, which are computationally more efficient, we show that this trend holds for most of the 30S r-proteins.

Ribosomes are complex cellular machines that synthesize new proteins in the cell. The accurate and efficient assembly of ribosomal proteins (r-proteins) and ribosomal RNA (rRNA) to form a functional ribosome is important for cell growth, metabolic reactions, and other cellular processes. Additionally, some antibacterial drugs are believed to target the bacterial ribosome during its construction. Hence, ribosomal assembly has been an active research topic for many years because understanding the assembly mechanisms can provide insight into protein/RNA recognitions important in many other cellular processes, as well as optimize the development of antibacterial therapeutics. Experimental studies thus far have provided still limited understanding about the assembly process. To further understand the assembly process, we have computationally studied the dynamic properties that r-proteins exhibit during assembly and the relationship between dynamics, physical properties, and binding propensity. We observe significant charged interactions between r-proteins and rRNA. We also detect a strong correlation between contact residues and their dynamic mobilities. Protein residues contacting with rRNA are observed to be more mobile in comparison with other residues. We also relate the location of the r-protein in the fully assembled ribosome to its susceptibility for large conformational changes prior to binding.

Unwrapping of nucleosomal DNA ends: a multiscale molecular dynamics study

To permit access to DNA-binding proteins involved in the control and expression of the genome, the nucleosome undergoes structural remodeling including unwrapping of nucleosomal DNA segments from the nucleosome core. Here we examine the mechanism of DNA dissociation from the nucleosome using microsecond timescale coarse-grained molecular dynamics simulations. The simulations exhibit short-lived, reversible DNA detachments from the nucleosome and long-lived DNA detachments not reversible on the timescale of the simulation. During the short-lived DNA detachments, 9 bp dissociate at one extremity of the nucleosome core and the H3 tail occupies the space freed by the detached DNA. The long-lived DNA detachments are characterized by structural rearrangements of the H3 tail including the formation of a turn-like structure at the base of the tail that sterically impedes the rewrapping of DNA on the nucleosome surface. Removal of the H3 tails causes the long-lived detachments to disappear. The physical consistency of the CG long-lived open state was verified by mapping a CG structure representative of this state back to atomic resolution and performing molecular dynamics as well as by comparing conformation-dependent free energies. Our results suggest that the H3 tail may stabilize the nucleosome in the open state during the initial stages of the nucleosome remodeling process.

Computational studies of molecular machines: the ribosome

The past decade has produced an avalanche of experimental data on the structure and dynamics of the ribosome. Groundbreaking studies in structural biology and kinetics have placed important constraints on ribosome structural dynamics. However, a gulf remains between static structures and time dependent data. In particular, X-ray crystallography and cryo-EM studies produce static models of the ribosome in various states, but lack dynamic information. Single molecule studies produce information on the rates of transitions between these states but do not have high-resolution spatial information. Computational studies have aided in bridging this gap by providing atomic resolution simulations of structural fluctuations and transitions between configurations.

A-site residues move independently from P-site residues in all-atom molecular dynamics simulations of the 70S bacterial ribosome

The ribosome is a large macromolecular machine, and correlated motion between residues is necessary for coordinating function across multiple protein and RNA chains. We ran two all-atom, explicit solvent molecular dynamics simulations of the bacterial ribosome and calculated correlated motion between residue pairs by using mutual information. Because of the short timescales of our simulation (ns), we expect that dynamics are largely local fluctuations around the crystal structure. We hypothesize that residues that show coupled dynamics are functionally related, even on longer timescales. We validate our model by showing that crystallographic B-factors correlate well with the entropy calculated as part of our mutual information calculations. We reveal that A-site residues move relatively independently from P-site residues, effectively insulating A-site functions from P-site functions during translation.

Key intermolecular interactions in the E. coli 70S ribosome revealed by coarse-grained analysis

The ribosome is a very large complex that consists of many RNA and protein molecules and plays a central role in protein biosynthesis in all organisms. Extensive interactions between different molecules are critical to ribosomal functional dynamics. In this work, intermolecular interactions in the Escherichia coli 70S ribosome are investigated by coarse-grained (CG) analysis. CG models are defined to preserve dynamic domains in RNAs and proteins and to capture functional motions in the ribosome, and then the CG sites are connected by harmonic springs, and spring constants are obtained by matching the computed fluctuations to those of an all-atom molecular dynamics (MD) simulation. Those spring constants indicate how strong the interactions are between the ribosomal components, and they are in good agreement with various experimental data. Nearly all the bridges between the small and large ribosomal subunits are indicated by CG interactions with large spring constants. The head of the small subunit is very mobile because it has minimal CG interactions with the rest of the subunit; however, a large number of small subunit proteins bind to maintain the internal structure of the head. The results show a clear connection between the intermolecular interactions and the structural and functional properties of the ribosome because of the reduced complexity in domain-based CG models. The present approach also provides a useful strategy to map interactions between molecules within large biomolecular complexes since it is not straightforward to investigate these by either atomistic MD simulations or residue-based elastic network models.

Gating and Intermolecular Interactions in Ligand-Protein Association: Coarse-Grained Modeling of HIV-1 Protease

Most biological processes are initiated or mediated by the association of ligands and proteins. This work studies multistep, ligand-protein association processes by Brownian dynamics simulations with coarse-grained models for HIV-1 protease (HIVp) and its neutral ligands. We report the average association times when the ligand concentration is 100 μM. The influence of crowding on the simulated binding time was also studied. HIVp has flexible loops that serve as a gate during the ligand binding processes. It is believed that the flaps are partially closed most of the time in its free state. To accelerate our simulations, we fixed a part of the HIVp and reparameterized our coarse-grained model, using atomistic molecular dynamics simulations, to reproduce the "gating" motions of HIVp. HIVp-ligand interactions changed the gating behavior of HIVp and helped ligands diffuse on HIVp surface to accelerate binding. The structural adjustment of the ligand toward its final stable state was the limiting step in the binding processes, which is highly system dependent. The intermolecular attraction between the ligands and crowder proteins contributes the most to the crowding effects. The results highlight broader implications in recognition pathways under more complex environment that considers molecular dynamics and conformational changes. This work brings insights into ligand-protein associations and is helpful in the design of targeted ligands.

Brownian dynamics study of the association between the 70S ribosome and elongation factor G

Protein synthesis on the ribosome involves a number of external protein factors that bind at its functional sites. One key factor is the elongation factor G (EF-G) that facilitates the translocation of transfer RNAs between their binding sites, as well as advancement of the messenger RNA by one codon. The details of the EF-G/ribosome diffusional encounter and EF-G association pathway still remain unanswered. Here, we applied Brownian dynamics methodology to study bimolecular association in the bacterial EF-G/70S ribosome system. We estimated the EF-G association rate constants at 150 and 300 mM monovalent ionic strengths and obtained reasonable agreement with kinetic experiments. We have also elucidated the details of EF-G/ribosome association paths and found that positioning of the L11 protein of the large ribosomal subunit is likely crucial for EF-G entry to its binding site.

Coarse-grained modeling study of nonpeptide RGD ligand density and PEG molecular weight on the conformation of poly(γ-glutamyl-glutamate) paclitaxel conjugates

Molecular shape, flexibility, and surface hydrophilicity are thought to influence the ability of nanoparticles to cross biological barriers during drug delivery. In this study, coarse-grained (CG) molecular dynamics (MD) simulations were used to study these properties of a polymer-drug construct in potential clinical development: poly(γ-glutamyl-glutamate)-paclitaxel-poly(ethylene glycol) nonpeptide RGD (PGG-PTX-PEG-npRGD), a linear glutamyl-glutamate polymer with paclitaxel and poly(ethylene glycol)-nonpeptide RGD side groups. It was hypothesized that the PEG molecular weight (MW) (500 Da; 1,000 Da; and 2,000 Da) and nonpeptide RGD ligand density (4, 8, 12, and 16 per molecule), respectively, may have advantageous effects on the shape, flexibility, and surface hydrophilicity of PGG-PTX-PEG-npRGD. Circular dichroism spectroscopy was used to suggest initial structures for the all-atom (AA) models of PGG-PTX-PEG-npRGD, which were further converted to CG models using a commercially available mapping algorithm. Due to its semi-flexibility, PGG-PTX-PEG-npRGD is not limited to one specific conformation. Thus, CG MD simulations were run until statistical equilibrium, at which PGG-PTX-PEG-npRGD is represented as an ensemble of statistically similar conformations. The size of a PGG-PTX-PEG-npRGD molecule is not affected by the PEG MW or the nonpeptide RGD density, but higher PEG MW results in increased surface density of a PGG-PTX-PEG-npRGD molecule. Most PGG-PTX-PEG-npRGD shapes are globular, although filamentous shapes were also observed in the PEG500 and PEG1000 molecules. PEG500 and PEG1000 molecules are more flexible than PEG2000 systems. A higher presence of npRGD ligands results in decrease surface hydrophilicity of PGG-PTX-PEG-npRGD. These results indicate that the PGG-PTX-PEG1000-npRGD₄ and PGG-PTX-PEG1000-npRGD₈ molecules are the most efficacious candidates and are further recommended for experimental preclinical studies.

Coarse-grained models to study dynamics of nanoscale biomolecules and their applications to the ribosome

Biopolymers are of dynamic nature and undergo functional motions spanning a large spectrum of timescales. To study the internal dynamics of nano-sized molecular complexes that exceed hundred thousands of atoms with atomic detail is computationally inefficient. Therefore, to achieve both the spatial and temporal scales of biological interest coarse-grained models of macromolecules are often used. By uniting groups of atoms into single interacting centers one decreases the resolution of the system and gets rid of the irrelevant degrees of freedom. This simplification, even though it requires parameterization, makes the studies of biomolecular dynamics computationally tractable and allows us to reach beyond the microsecond time frame. Here, I review the coarse-grained models of macromolecules composed of proteins and nucleic acids. I give examples of one-bead models that were developed to investigate the internal dynamics and focus on their applications to the ribosome--the nanoscale protein synthesis machine.

Characterizing protein energy landscape by self-learning multiscale simulations: application to a designed β-hairpin

Characterizing the energy landscape of proteins at atomic resolution is still a very challenging problem, since it simultaneously requires high accuracy in estimating specific interactions and high efficiency in conformational sampling. Here, for these two requirements to meet, we extended the self-learning multiscale simulation (SLMS) method developed recently and applied it to the designed β-hairpin CLN025. The SLMS integrates all-atom and coarse-grained (CG) models in an iterative way such that the conformational sampling is performed by the CG model, the AA energy is used to calibrate the energy landscape, and the CG model is improved by the calibrated energy landscape. We extended the SLMS in two aspects, use of the energy decomposition for self-learning of the CG potential and a two-bead/residue CG model. The results show that the self-learning greatly improved the CG potential, and with the derived CG potential, the β-hairpin CLN025 robustly folded to the native structure. The self-learning iteration progressively enhanced the context dependence in the CG potential and increased the energy gap between the native and the denatured states of the CG model, leading to a funnel-like energy landscape. By using the SLMS method, without prior knowledge of the native structure but with the help of the AA energy, we can obtain a tailor-made CG potential specific to the target protein. The method can be useful for de novo structure prediction as well.

Characterization of a clinical polymer-drug conjugate using multiscale modeling

The molecular conformation of certain therapeutic agents has been shown to affect the ability to gain access to target cells, suggesting potential value in defining conformation of candidate molecules. This study explores how the shape and size of poly-γ-glutamyl-glutamate paclitaxel (PGG-PTX), an amphiphilic polymer-drug with potential chemotherapeutic applications, can be systematically controlled by varying hydrophobic and hydrophilic entities. Eighteen different formulations of PGG-PTX varying in three PTX loading fractions (f(PTX)) of 0.18, 0.24, and 0.37 and six spatial arrangements of PTX ('clusters', 'ends', 'even', 'middle', 'random', and 'side') were explored. Molecular dynamics (MD) simulations of all-atom (AA) models of PGG-PTX were run until a statistical equilibrium was reached at 100 ns and then continued as coarse-grained (CG) models until a statistical equilibrium was reached at an effective time of 800 ns. Circular dichroism spectroscopy was used to suggest initial modeling configurations. Results show that a PGG-PTX molecule has a strong tendency to form coil shapes, regardless of the PTX loading fraction and spatial PTX arrangement, although globular shapes exist at f(PTX) = 0.24. Also, less uniform PTX arrangements such as 'ends', 'middle', and 'side' produce coil geometries with more curvature. The prominence of coil shapes over globules suggests that PGG-PTX may confer a long circulation half-life and high propensity for accumulation to tumor endothelia. This multiscale modeling approach may be advantageous for the design of cancer therapeutic delivery systems. © 2010 Wiley Periodicals, Inc. Biopolymers 93: 936-951, 2010.

Non-bulk-like solvent behavior in the ribosome exit tunnel

As nascent proteins are synthesized by the ribosome, they depart via an exit tunnel running through the center of the large subunit. The exit tunnel likely plays an important part in various aspects of translation. Although water plays a key role in many bio-molecular processes, the nature of water confined to the exit tunnel has remained unknown. Furthermore, solvent in biological cavities has traditionally been characterized as either a continuous dielectric fluid, or a discrete tightly bound molecule. Using atomistic molecular dynamics simulations, we predict that the thermodynamic and kinetic properties of water confined within the ribosome exit tunnel are quite different from this simple two-state model. We find that the tunnel creates a complex microenvironment for the solvent resulting in perturbed rotational dynamics and heterogenous dielectric behavior. This gives rise to a very rugged solvation landscape and significantly retarded solvent diffusion. We discuss how this non-bulk-like solvent is likely to affect important biophysical processes such as sequence dependent stalling, co-translational folding, and antibiotic binding. We conclude with a discussion of the general applicability of these results to other biological cavities.

Coarse-Grained Representations of Large Biomolecular Complexes from Low-Resolution Structural Data

High-resolution atomistic structures of many large biomolecular complexes have not yet been solved by experiments, such as X-ray crystallography or NMR. Often however low-resolution information is obtained by alternative techniques, such as cryo-electron microscopy or small-angle X-ray scattering. Coarse-grained (CG) models are an appropriate choice to computationally study these complexes given the limited resolution experimental data. One of the important questions therefore is how to define CG representations from these low-resolution density maps. This work provides a space-based essential dynamics coarse-graining (ED-CG) method to define a CG representation from a density map without detailed knowledge of its underlying atomistic structure and primary sequence information. This method is demonstrated on G-actin (both the atomic structure and its density map). It is then applied to the density maps of the Escherichia coli 70S ribosome and the microtubule. The results indicate that the method can define highly CG models that still preserve functionally important dynamics of large biomolecular complexes.