Computational studies of molecular machines: the ribosome

On the Power and Challenges of Atomistic Molecular Dynamics to Investigate RNA Molecules

RNA molecules play a vital role in biological processes within the cell, with significant implications for science and medicine. Notably, the biological functions exerted by specific RNA molecules are often linked to the RNA conformational ensemble. However, the experimental characterization of such three-dimensional RNA structures is challenged by the structural heterogeneity of RNA and by its multiple dynamic interactions with binding partners such as small molecules, proteins, and metal ions. Consequently, our current understanding of the structure-function relationship of RNA molecules is still limited. In this context, we highlight molecular dynamics (MD) simulations as a powerful tool to complement experimental efforts on RNAs. Despite the recognized limitations of current force fields for RNA MD simulations, examining the dynamics of selected RNAs has provided valuable functional insights into their structures.

SPANA: Spatial decomposition analysis for cellular-scale molecular dynamics simulations

The rapid increase in computational power with the latest supercomputers has enabled atomistic molecular dynamics (MDs) simulations of biomolecules in biological membrane, cytoplasm, and other cellular environments. These environments often contain a million or more atoms to be simulated simultaneously. Therefore, their trajectory analyses involve heavy computations that can become a bottleneck in the computational studies. Spatial decomposition analysis (SPANA) is a set of analysis tools in the Generalized-Ensemble Simulation System (GENESIS) software package that can carry out MD trajectory analyses of large-scale biological simulations using multiple CPU cores in parallel. SPANA applies the spatial decomposition of a large biological system to distribute structural and dynamical analyses into individual CPU cores, which reduces the computational time and the memory size, significantly. SPANA opens new possibilities for detailed atomistic analyses of biomacromolecules as well as solvent water molecules, ions, and metabolites in MD simulation trajectories of very large biological systems containing more than millions of atoms in cellular environments.

Mechanism for the Unfolding of the TOP7 Protein in Steered Molecular Dynamics Simulations as Revealed by Mutual Information Analysis

We employed mutual information (MI) analysis to detect motions affecting the mechanical resistance of the human-engineered protein Top7. The results are based on the MI analysis of pair contact correlations measured in steered molecular dynamics (SMD) trajectories and their statistical dependence on global unfolding. This study is the first application of the MI analysis to SMD forced unfolding, and we furnish specific SMD recommendations for the utility of parameters and options in the TimeScapes package. The MI analysis provided a global overview of the effect of perturbation on the stability of the protein. We also employed a more conventional trajectory analysis for a detailed description of the mechanical resistance of Top7. Specifically, we investigated 1) the hydropathy of the interactions of structural segments, 2) the H₂O concentration near residues relevant for unfolding, and 3) the changing hydrogen bonding patterns and main chain dihedral angles. The results show that the application of MI in the study of protein mechanical resistance can be useful for the engineering of more resistant mutants when combined with conventional analysis. We propose a novel mutation design based on the hydropathy of residues that would stabilize the unfolding region by mimicking its more stable symmetry mate. The proposed design process does not involve the introduction of covalent crosslinks, so it has the potential to preserve the conformational space and unfolding pathway of the protein.

Getting to the bottom of lncRNA mechanism: structure-function relationships

While long non-coding RNAs are known to play key roles in disease and development, relatively few structural studies have been performed for this important class of RNAs. Here, we review functional studies of long non-coding RNAs and expose the need for high-resolution 3-D structural studies, discussing the roles of long non-coding RNAs in the cell and how structure–function relationships might be used to elucidate further understanding. We then describe structural studies of other classes of RNAs using chemical probing, nuclear magnetic resonance, small-angle X-ray scattering, X-ray crystallography, and cryogenic electron microscopy (cryo-EM). Next, we review early structural studies of long non-coding RNAs to date and describe the way forward for the structural biology of long non-coding RNAs in terms of cryo-EM.

Investigation of Allosteric Effect of 2,8-Dimethylation of A2503 in E. coli 23S rRNA by Molecular-Dynamics Simulations

Ribosome is a molecular machine that synthesizes all cellular proteins. It also is a target of about half of the clinically used antibiotics. Adaptive chemical modification of ribosomal RNAs residues is one of the ways to provide resistance to certain antibiotics. A curious example of such modification is 2,8-dimethylation of A2503 in 23S rRNA, which induces resistance to phenols, linkosamides, oxazolidinones, pleuromutilins, and certain macrolides. In this article the effect of 2,8-dimethylation of A2503 on conformation and mobility of RNA residues of the 70S E. coli ribosome was investigated employing molecular dynamics simulations method. Significant alterations were detected both in the immediate environment of the 2503 23S rRNA residue and in the nucleotides located deeper in the nascent peptide exit tunnel (NPET), which are known to be involved in signal transmission from the antibiotics bound in the NPET to the peptidyl transferase center. These alterations shift the ribosome towards the A/A, P/P-state from the conformationally different state - P/P, E/E one in our case. The obtained results allow us to conclude that the effect of m²m⁸A2503 modification involves additional stabilization of the A/A, P/P-state favoring the peptidyl transferase reaction (PTR) contrary to antibiotics that inhibit PTR.

Arginine Methylation Regulates Ribosome CAR Function

The ribosome CAR interaction surface is hypothesized to provide a layer of translation regulation through hydrogen-bonding to the +1 mRNA codon that is next to enter the ribosome A site during translocation. The CAR surface consists of three residues, 16S/18S rRNA C1054, A1196 (E. coli 16S numbering), and R146 of yeast ribosomal protein Rps3. R146 can be methylated by the Sfm1 methyltransferase which is downregulated in stressed cells. Through molecular dynamics analysis, we show here that methylation of R146 compromises the integrity of CAR by reducing the cation-pi stacking of the R146 guanidinium group with A1196, leading to reduced CAR hydrogen-bonding with the +1 codon. We propose that ribosomes assembled under stressed conditions have unmethylated R146, resulting in elevated CAR/+1 codon interactions, which tunes translation levels in response to the altered cellular context.

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.

Modeling to Understand Plant Protein Structure-Function Relationships-Implications for Seed Storage Proteins

Proteins are among the most important molecules on Earth. Their structure and aggregation behavior are key to their functionality in living organisms and in protein-rich products. Innovations, such as increased computer size and power, together with novel simulation tools have improved our understanding of protein structure-function relationships. This review focuses on various proteins present in plants and modeling tools that can be applied to better understand protein structures and their relationship to functionality, with particular emphasis on plant storage proteins. Modeling of plant proteins is increasing, but less than 9% of deposits in the Research Collaboratory for Structural Bioinformatics Protein Data Bank come from plant proteins. Although, similar tools are applied as in other proteins, modeling of plant proteins is lagging behind and innovative methods are rarely used. Molecular dynamics and molecular docking are commonly used to evaluate differences in forms or mutants, and the impact on functionality. Modeling tools have also been used to describe the photosynthetic machinery and its electron transfer reactions. Storage proteins, especially in large and intrinsically disordered prolamins and glutelins, have been significantly less well-described using modeling. These proteins aggregate during processing and form large polymers that correlate with functionality. The resulting structure-function relationships are important for processed storage proteins, so modeling and simulation studies, using up-to-date models, algorithms, and computer tools are essential for obtaining a better understanding of these relationships.

Resolution-exchanged structural modeling and simulations jointly unravel that subunit rolling underlies the mechanism of programmed ribosomal frameshifting

MOTIVATION

Programmed ribosomal frameshifting (PRF) is widely used by viruses and bacteria to produce different proteins from a single mRNA template. How steric hindrance of a PRF-stimulatory mRNA structure transiently modifies the conformational dynamics of the ribosome, and thereby allows tRNA slippage, remains elusive.

RESULTS

Here, we leverage linear response theories and resolution-exchanged simulations to construct a structural/dynamics model that connects and rationalizes existing structural, single-molecule and mutagenesis data by resolution-exchanged structural modelling and simulations. Our combined theoretical techniques provide a temporal and spatial description of PRF with unprecedented mechanistic details. We discover that ribosomal unfolding of the PRF-stimulating pseudoknot exerts resistant forces on the mRNA entrance of the ribosome, and thereby drives 30S subunit rolling. Such motion distorts tRNAs, leads to tRNA slippage, and in turn serves as a delicate control of cis-element's unwinding forces over PRF.

AVAILABILITY AND IMPLEMENTATION

All the simulation scripts and computational implementations of our methods/analyses (including linear response theory) are included in the bioStructureM suite, provided through GitHub at https://github.com/Yuan-Yu/bioStructureM.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.

New tricks for old dogs: improving the accuracy of biomolecular force fields by pair-specific corrections to non-bonded interactions

In contrast to ordinary polymers, the vast majority of biological macromolecules adopt highly ordered three-dimensional structures that define their functions. The key to folding of a biopolymer into a unique 3D structure or to an assembly of several biopolymers into a functional unit is a delicate balance between the attractive and repulsive forces that also makes such self-assembly reversible under physiological conditions. The all-atom molecular dynamics (MD) method has emerged as a powerful tool for studies of individual biomolecules and their functional assemblies, encompassing systems of ever increasing complexity. However, advances in parallel computing technology have outpaced the development of the underlying theoretical models-the molecular force fields, pushing the MD method into an untested territory. Recent tests of the MD method have found the most commonly used molecular force fields to be out of balance, overestimating attractive interactions between charged and hydrophobic groups, which can promote artificial aggregation in MD simulations of multi-component protein, nucleic acid, and lipid systems. One route towards improving the force fields is through the NBFIX corrections method, in which the intermolecular forces are calibrated against experimentally measured quantities such as osmotic pressure by making atom pair-specific adjustments to the non-bonded interactions. In this article, we review development of the NBFIX (Non-Bonded FIX) corrections to the AMBER and CHARMM force fields and discuss their implications for MD simulations of electrolyte solutions, dense DNA systems, Holliday junctions, protein folding, and lipid bilayer membranes.

Solution structure of an ultra-stable single-chain insulin analog connects protein dynamics to a novel mechanism of receptor binding

Domain-minimized insulin receptors (IRs) have enabled crystallographic analysis of insulin-bound "micro-receptors." In such structures, the C-terminal segment of the insulin B chain inserts between conserved IR domains, unmasking an invariant receptor-binding surface that spans both insulin A and B chains. This "open" conformation not only rationalizes the inactivity of single-chain insulin (SCI) analogs (in which the A and B chains are directly linked), but also suggests that connecting (C) domains of sufficient length will bind the IR. Here, we report the high-resolution solution structure and dynamics of such an active SCI. The hormone's closed-to-open transition is foreshadowed by segmental flexibility in the native state as probed by heteronuclear NMR spectroscopy and multiple conformer simulations of crystallographic protomers as described in the companion article. We propose a model of the SCI's IR-bound state based on molecular-dynamics simulations of a micro-receptor complex. In this model, a loop defined by the SCI's B and C domains encircles the C-terminal segment of the IR α-subunit. This binding mode predicts a conformational transition between an ultra-stable closed state (in the free hormone) and an active open state (on receptor binding). Optimization of this switch within an ultra-stable SCI promises to circumvent insulin's complex global cold chain. The analog's biphasic activity, which serendipitously resembles current premixed formulations of soluble insulin and microcrystalline suspension, may be of particular utility in the developing world.

Toward Large-Scale Computational Prediction of Protein Complexes

Cellular functions are often performed by multiprotein structures called protein complexes. These complexes are dynamic structures that evolve during the cell cycle or in response to external and internal stimuli, and are tightly regulated by protein expression in different tissues resulting in quantitative and qualitative variation of protein complexes. Advances in high-throughput techniques, such as mass-spectrometry and yeast two-hybrid provided a large amount of data on protein-protein interactions. This sparked the development of computational methods able to predict protein complex formation under a variety of biological and clinical conditions. However, the challenges that need to be addressed for successful computational protein complex prediction are highly complex.The post-genomic era saw an emerging number of algorithms and software, which are able to predict protein complexes from protein-protein interaction networks and a variety of other sources. Despite the high capacity of these methods to qualitatively predict protein complexes, they could provide only limited or no quantitative information of the predicted complexes. Recently, a new large-scale simulation of protein complexes was able to achieve this task by simulating protein complex formation on the proteome scale.In this chapter, we review representative methods that can predict multiple protein complexes at different scales and discuss how these can be combined with emerging sources of data in order to improve protein complex characterization.

Conformational dynamics of human protein kinase CK2α and its effect on function and inhibition

Protein kinase, casein kinase II (CK2), is ubiquitously expressed and highly conserved protein kinase that shows constitutive activity. It phosphorylates a diverse set of proteins and plays crucial role in several cellular processes. The catalytic subunit of this enzyme (CK2α) shows remarkable flexibility as evidenced in numerous crystal structures determined till now. Here, using analysis of multiple crystal structures and long timescale molecular dynamics simulations, we explore the conformational flexibility of CK2α. The enzyme shows considerably higher flexibility in the solution as compared to that observed in crystal structure ensemble. Multiple conformations of hinge region, located near the active site, were observed during the dynamics. We further observed that among these multiple conformations, the most populated conformational state was inadequately represented in the crystal structure ensemble. The catalytic spine, was found to be less dismantled in this state as compared to the "open" hinge/αD state crystal structures. The comparison of dynamics in unbound (Apo) state and inhibitor (CX4945) bound state exhibits inhibitor induced suppression in the overall dynamics of the enzyme. This is especially true for functionally important glycine-rich loop above the active site. Together, this work gives novel insights into the dynamics of CK2α in solution and relates it to the function. This work also explains the effect of inhibitor on the dynamics of CK2α and paves way for development of better inhibitors.

Molecular simulations of the ribosome and associated translation factors

The ribosome is a macromolecular complex which is responsible for protein synthesis in all living cells according to their transcribed genetic information. Using X-ray crystallography and, more recently, cryo-electron microscopy (cryo-EM), the structure of the ribosome was resolved at atomic resolution in many functional and conformational states. Molecular dynamics simulations have added information on dynamics and energetics to the available structural information, thereby have bridged the gap to the kinetics obtained from single-molecule and bulk experiments. Here, we review recent computational studies that brought notable insights into ribosomal structure and function.

Tracking fluctuation hotspots on the yeast ribosome through the elongation cycle

Chemical modification was used to quantitatively determine the flexibility of nearly the entire rRNA component of the yeast ribosome through 8 discrete stages of translational elongation, revealing novel observations at the gross and fine-scales. These include (i) the bulk transfer of energy through the intersubunit bridges from the large to the small subunit after peptidyltransfer, (ii) differences in the interaction of the sarcin ricin loop with the two elongation factors and (iii) networked information exchange pathways that may functionally facilitate intra- and intersubunit coordination, including the 5.8S rRNA. These analyses reveal hot spots of fluctuations that set the stage for large-scale conformational changes essential for translocation and enable the first molecular dynamics simulation of an 80S complex. Comprehensive datasets of rRNA base flexibilities provide a unique resource to the structural biology community that can be computationally mined to complement ongoing research toward the goal of understanding the dynamic ribosome.

Stringent Nucleotide Recognition by the Ribosome at the Middle Codon Position

Accurate translation of the genetic code depends on mRNA:tRNA codon:anticodon base pairing. Here we exploit an emissive, isosteric adenosine surrogate that allows direct measurement of the kinetics of codon:anticodon base formation during protein synthesis. Our results suggest that codon:anticodon base pairing is subject to tighter constraints at the middle position than at the 5′- and 3′-positions, and further suggest a sequential mechanism of formation of the three base pairs in the codon:anticodon helix.

GENESIS 1.1: A hybrid-parallel molecular dynamics simulator with enhanced sampling algorithms on multiple computational platforms

GENeralized-Ensemble SImulation System (GENESIS) is a software package for molecular dynamics (MD) simulation of biological systems. It is designed to extend limitations in system size and accessible time scale by adopting highly parallelized schemes and enhanced conformational sampling algorithms. In this new version, GENESIS 1.1, new functions and advanced algorithms have been added. The all-atom and coarse-grained potential energy functions used in AMBER and GROMACS packages now become available in addition to CHARMM energy functions. The performance of MD simulations has been greatly improved by further optimization, multiple time-step integration, and hybrid (CPU + GPU) computing. The string method and replica-exchange umbrella sampling with flexible collective variable choice are used for finding the minimum free-energy pathway and obtaining free-energy profiles for conformational changes of a macromolecule. These new features increase the usefulness and power of GENESIS for modeling and simulation in biological research. © 2017 Wiley Periodicals, Inc.

Investigation of Ribosomes Using Molecular Dynamics Simulation Methods

The ribosome as a complex molecular machine undergoes significant conformational changes while synthesizing a protein molecule. Molecular dynamics simulations have been used as complementary approaches to X-ray crystallography and cryoelectron microscopy, as well as biochemical methods, to answer many questions that modern structural methods leave unsolved. In this review, we demonstrate that all-atom modeling of ribosome molecular dynamics is particularly useful in describing the process of tRNA translocation, atomic details of behavior of nascent peptides, antibiotics, and other small molecules in the ribosomal tunnel, and the putative mechanism of allosteric signal transmission to functional sites of the ribosome.

The Renormalization Group and Its Applications to Generating Coarse-Grained Models of Large Biological Molecular Systems

Understanding the dynamics of biomolecules is the key to understanding their biological activities. Computational methods ranging from all-atom molecular dynamics simulations to coarse-grained normal-mode analyses based on simplified elastic networks provide a general framework to studying these dynamics. Despite recent successes in studying very large systems with up to a 100,000,000 atoms, those methods are currently limited to studying small- to medium-sized molecular systems due to computational limitations. One solution to circumvent these limitations is to reduce the size of the system under study. In this paper, we argue that coarse-graining, the standard approach to such size reduction, must define a hierarchy of models of decreasing sizes that are consistent with each other, i.e., that each model contains the information of the dynamics of its predecessor. We propose a new method, Decimate, for generating such a hierarchy within the context of elastic networks for normal-mode analysis. This method is based on the concept of the renormalization group developed in statistical physics. We highlight the details of its implementation, with a special focus on its scalability to large systems of up to millions of atoms. We illustrate its application on two large systems, the capsid of a virus and the ribosome translation complex. We show that highly decimated representations of those systems, containing down to 1% of their original number of atoms, still capture qualitatively and quantitatively their dynamics. Decimate is available as an OpenSource resource.

Probing the structural dynamics of the CRISPR-Cas9 RNA-guided DNA-cleavage system by coarse-grained modeling

In the adaptive immune systems of many bacteria and archaea, the Cas9 endonuclease forms a complex with specific guide/scaffold RNA to identify and cleave complementary target sequences in foreign DNA. This DNA targeting machinery has been exploited in numerous applications of genome editing and transcription control. However, the molecular mechanism of the Cas9 system is still obscure. Recently, high-resolution structures have been solved for Cas9 in different structural forms (e.g., unbound forms, RNA-bound binary complexes, and RNA-DNA-bound tertiary complexes, corresponding to an inactive state, a pre-target-bound state, and a cleavage-competent or product state), which offered key structural insights to the Cas9 mechanism. To further probe the structural dynamics of Cas9 interacting with RNA and DNA at the amino-acid level of details, we have performed systematic coarse-grained modeling using an elastic network model and related analyses. Our normal mode analysis predicted a few key modes of collective motions that capture the observed conformational changes featuring large domain motions triggered by binding of RNA and DNA. Our flexibility analysis identified specific regions with high or low flexibility that coincide with key functional sites (such as DNA/RNA-binding sites, nuclease cleavage sites, and key hinges). We also identified a small set of hotspot residues that control the energetics of functional motions, which overlap with known functional sites and offer promising targets for future mutagenesis efforts to improve the specificity of Cas9. Finally, we modeled the conformational transitions of Cas9 from the unbound form to the binary complex and then the tertiary complex, and predicted a distinct sequence of domain motions. In sum, our findings have offered rich structural and dynamic details relevant to the Cas9 machinery, and will guide future investigation and engineering of the Cas9 systems. Proteins 2017; 85:342-353. © 2016 Wiley Periodicals, Inc.

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.

Multiple program/multiple data molecular dynamics method with multiple time step integrator for large biological systems

Parallelization of molecular dynamics (MD) simulation is essential for investigating conformational dynamics of large biological systems, such as ribosomes, viruses, and multiple proteins in cellular environments. To improve efficiency in the parallel computation, we have to reduce the amount of data transfer between processors by introducing domain decomposition schemes. Also, it is important to optimize the computational balance between real-space non-bonded interactions and reciprocal-space interactions for long-range electrostatic interactions. Here, we introduce a novel parallelization scheme for large-scale MD simulations on massively parallel supercomputers consisting of only CPUs. We make use of a multiple program/multiple data (MPMD) approach for separating the real-space and reciprocal-space computations on different processors. We also utilize the r-RESPA multiple time step integrator on the framework of the MPMD approach in an efficient way: when the reciprocal-space computations are skipped in r-RESPA, processors assigned for them are utilized for half of the real-space computations. The new scheme allows us to use twice as many as processors that are available in the conventional single program approach. The best performances of all-atom MD simulations for 1 million (STMV), 8.5 million (8_STMV), and 28.8 million (27_STMV) atom systems on K computer are 65, 36, and 24 ns/day, respectively. The MPMD scheme can accelerate 23.4, 10.2, and 9.2 ns/day from the maximum performance of single-program approach for STMV, 8_STMV, and 27_STMV systems, respectively, which correspond to 57%, 39%, and 60% speed up. This suggests significant speedups by increasing the number of processors without losing parallel computational efficiency. © 2016 Wiley Periodicals, Inc.

Nanoscale Engineering of Designer Cellulosomes

Biocatalysts showcase the upper limit obtainable for high-speed molecular processing and transformation. Efforts to engineer functionality in synthetic nanostructured materials are guided by the increasing knowledge of evolving architectures, which enable controlled molecular motion and precise molecular recognition. The cellulosome is a biological nanomachine, which, as a fundamental component of the plant-digestion machinery from bacterial cells, has a key potential role in the successful development of environmentally-friendly processes to produce biofuels and fine chemicals from the breakdown of biomass waste. Here, the progress toward so-called "designer cellulosomes", which provide an elegant alternative to enzyme cocktails for lignocellulose breakdown, is reviewed. Particular attention is paid to rational design via computational modeling coupled with nanoscale characterization and engineering tools. Remaining challenges and potential routes to industrial application are put forward.

Scanning of 16S Ribosomal RNA for Peptide Nucleic Acid Targets

We have designed a protocol and server to aid in the search for putative binding sites in 16S rRNA that could be targeted by peptide nucleic acid oligomers. Various features of 16S rRNA were considered to score its regions as potential targets for sequence-specific binding that could result in inhibition of ribosome function. Specifically, apart from the functional importance of a particular rRNA region, we calculated its accessibility, flexibility, energetics of strand invasion by an oligomer, as well as similarity to human rRNA. To determine 16S rRNA flexibility in the ribosome context, we performed all-atom molecular dynamics simulations of the 30S subunit in explicit solvent. We proposed a few 16S RNA target sites, and one of them was tested experimentally to verify inhibition of bacterial growth by a peptide nucleic acid oligomer.

Centers of motion associated with EF-Tu binding to the ribosome

Structural centers of motion (pivot points) in the ribosome have recently been identified by measurement of conformational changes in rRNA resulting from EF-G GTP hydrolysis. This series of measurements is extended here to the ribosome's interactions with the cofactor EF-Tu. Four recent EF-Tu bound ribosome structures were compared to unbound structures. A total of 16 pivots were identified, of which 4 are unique to the EF-Tu interaction. Pivots in the GTPase associated center and the sarcin-ricin loop omitted previously, are found to be mobile in response to both EF-Tu and EF-G binding. Pivots in the intersubunit bridge rRNAs are found to be cofactor specific. Head swiveling motions in the small subunit are observed in the EF-Tu bound structures that were trapped post GTP hydrolysis. As in the case of pivots associated with EF-G, the additional pivots described here are associated with weak points in the rRNA structures such as non-canonical pairs and bulge loops. The combined set of pivots should be regarded as a minimal set. Only several states available to the ribosome have been presented in this work. Future, precise crystal structures in conjunction with experimental data will likely show additional functional pivoting elements in the rRNA.

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.

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.

GENESIS: a hybrid-parallel and multi-scale molecular dynamics simulator with enhanced sampling algorithms for biomolecular and cellular simulations

GENESIS (Generalized-Ensemble Simulation System) is a new software package for molecular dynamics (MD) simulations of macromolecules. It has two MD simulators, called ATDYN and SPDYN. ATDYN is parallelized based on an atomic decomposition algorithm for the simulations of all-atom force-field models as well as coarse-grained Go-like models. SPDYN is highly parallelized based on a domain decomposition scheme, allowing large-scale MD simulations on supercomputers. Hybrid schemes combining OpenMP and MPI are used in both simulators to target modern multicore computer architectures. Key advantages of GENESIS are (1) the highly parallel performance of SPDYN for very large biological systems consisting of more than one million atoms and (2) the availability of various REMD algorithms (T-REMD, REUS, multi-dimensional REMD for both all-atom and Go-like models under the NVT, NPT, NPAT, and NPγT ensembles). The former is achieved by a combination of the midpoint cell method and the efficient three-dimensional Fast Fourier Transform algorithm, where the domain decomposition space is shared in real-space and reciprocal-space calculations. Other features in SPDYN, such as avoiding concurrent memory access, reducing communication times, and usage of parallel input/output files, also contribute to the performance. We show the REMD simulation results of a mixed (POPC/DMPC) lipid bilayer as a real application using GENESIS. GENESIS is released as free software under the GPLv2 licence and can be easily modified for the development of new algorithms and molecular models. WIREs Comput Mol Sci 2015, 5:310–323. doi: 10.1002/wcms.1220

Structural Insights into tRNA Dynamics on the Ribosome

High-resolution structures at different stages, as well as biochemical, single molecule and computational approaches have highlighted the elasticity of tRNA molecules when bound to the ribosome. It is well acknowledged that the inherent structural flexibility of the tRNA lies at the heart of the protein synthesis process. Here, we review the recent advances and describe considerations that the conformational changes of the tRNA molecules offer about the mechanisms grounded in translation.

Major centers of motion in the large ribosomal RNAs

Major centers of motion in the rRNAs of Thermus thermophilus are identified by alignment of crystal structures of EF-G bound and EF-G unbound ribosomal subunits. Small rigid helices upstream of these 'pivots' are aligned, thereby decoupling their motion from global rearrangements. Of the 21 pivots found, six are observed in the large subunit rRNA and 15 in the small subunit rRNA. Although the magnitudes of motion differ, with only minor exceptions equivalent pivots are seen in comparisons of Escherichia coli structures and one Saccharomyces cerevisiae structure pair. The pivoting positions are typically associated with structurally weak motifs such as non-canonical, primarily U-G pairs, bulge loops and three-way junctions. Each pivot is typically in direct physical contact with at least one other in the set and often several others. Moving helixes include rRNA segments in contact with the tRNA, intersubunit bridges and helices 28, 32 and 34 of the small subunit. These helices are envisioned to form a network. EF-G rearrangement would then provide directional control of this network propagating motion from the tRNA to the intersubunit bridges to the head swivel or along the same path backward.

Molecular dynamics simulations of large macromolecular complexes

Connecting dynamics to structural data from diverse experimental sources, molecular dynamics simulations permit the exploration of biological phenomena in unparalleled detail. Advances in simulations are moving the atomic resolution descriptions of biological systems into the million-to-billion atom regime, in which numerous cell functions reside. In this opinion, we review the progress, driven by large-scale molecular dynamics simulations, in the study of viruses, ribosomes, bioenergetic systems, and other diverse applications. These examples highlight the utility of molecular dynamics simulations in the critical task of relating atomic detail to the function of supramolecular complexes, a task that cannot be achieved by smaller-scale simulations or existing experimental approaches alone.

Systematic methods for defining coarse-grained maps in large biomolecules

Large biomolecules are involved in many important biological processes. It would be difficult to use large-scale atomistic molecular dynamics (MD) simulations to study the functional motions of these systems because of the computational expense. Therefore various coarse-grained (CG) approaches have attracted rapidly growing interest, which enable simulations of large biomolecules over longer effective timescales than all-atom MD simulations. The first issue in CG modeling is to construct CG maps from atomic structures. In this chapter, we review the recent development of a novel and systematic method for constructing CG representations of arbitrarily complex biomolecules, in order to preserve large-scale and functionally relevant essential dynamics (ED) at the CG level. In this ED-CG scheme, the essential dynamics can be characterized by principal component analysis (PCA) on a structural ensemble, or elastic network model (ENM) of a single atomic structure. Validation and applications of the method cover various biological systems, such as multi-domain proteins, protein complexes, and even biomolecular machines. The results demonstrate that the ED-CG method may serve as a very useful tool for identifying functional dynamics of large biomolecules at the CG level.

From static to dynamic: the need for structural ensembles and a predictive model of RNA folding and function

To understand RNA, it is necessary to move beyond a descriptive categorization towards quantitative predictions of its molecular conformations and functional behavior. An incisive approach to understanding the function and folding of biological RNA systems involves characterizing small, simple components that are largely responsible for the behavior of complex systems including helix-junction-helix elements and tertiary motifs. State-of-the-art methods have permitted unprecedented insight into the conformational ensembles of these elements revealing, for example, that conformations of helix-junction-helix elements are confined to a small region of the ensemble, that this region is highly dependent on the junction's topology, and that the correct alignment of tertiary motifs may be a rare conformation on the overall folding landscape. Further characterization of RNA components and continued development of experimental and computational methods with the goal of quantitatively predicting RNA folding and functional behavior will be critical to understanding biological RNA systems.

Molecular dynamic simulations of protein/RNA complexes: CRISPR/Csy4 endoribonuclease

BACKGROUND

Many prokaryotic genomes comprise Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) offering defense against foreign nucleic acids. These immune systems are conditioned by the production of small CRISPR-derived RNAs matured from long RNA precursors. This often requires a Csy4 endoribonuclease cleaving the RNA 3'-end.

METHODS

We report extended explicit solvent molecular dynamic (MD) simulations of Csy4/RNA complex in precursor and product states, based on X-ray structures of product and inactivated precursor (55 simulations; ~3.7μs in total).

RESULTS

The simulations identify double-protonated His29 and deprotonated terminal phosphate as the likely dominant protonation states consistent with the product structure. We revealed potential substates consistent with Ser148 and His29 acting as the general base and acid, respectively. The Ser148 could be straightforwardly deprotonated through solvent and could without further structural rearrangements deprotonate the nucleophile, contrasting similar studies investigating the general base role of nucleobases in ribozymes. We could not locate geometries consistent with His29 acting as general base. However, we caution that the X-ray structures do not always capture the catalytically active geometries and then the reactive structures may be unreachable by the simulation technique.

CONCLUSIONS

We identified potential catalytic arrangement of the Csy4/RNA complex but we also report limitations of the simulation technique. Even for the dominant protonation state we could not achieve full agreement between the simulations and the structural data.

GENERAL SIGNIFICANCE

Potential catalytic arrangement of the Csy4/RNA complex is found. Further, we provide unique insights into limitations of simulations of protein/RNA complexes, namely, the influence of the starting experimental structures and force field limitations. This article is part of a Special Issue entitled Recent developments of molecular dynamics.

Close encounters with DNA

Over the past ten years, the all-atom molecular dynamics method has grown in the scale of both systems and processes amenable to it and in its ability to make quantitative predictions about the behavior of experimental systems. The field of computational DNA research is no exception, witnessing a dramatic increase in the size of systems simulated with atomic resolution, the duration of individual simulations and the realism of the simulation outcomes. In this topical review, we describe the hallmark physical properties of DNA from the perspective of all-atom simulations. We demonstrate the amazing ability of such simulations to reveal the microscopic physical origins of experimentally observed phenomena. We also discuss the frustrating limitations associated with imperfections of present atomic force fields and inadequate sampling. The review is focused on the following four physical properties of DNA: effective electric charge, response to an external mechanical force, interaction with other DNA molecules and behavior in an external electric field.

Molecular mechanics of 30S subunit head rotation

During ribosomal translocation, a process central to the elongation phase of protein synthesis, movement of mRNA and tRNAs requires large-scale rotation of the head domain of the small (30S) subunit of the ribosome. It has generally been accepted that the head rotates by pivoting around the neck helix (h28) of 16S rRNA, its sole covalent connection to the body domain. Surprisingly, we observe that the calculated axis of rotation does not coincide with the neck. Instead, comparative structure analysis across 55 ribosome structures shows that 30S head movement results from flexing at two hinge points lying within conserved elements of 16S rRNA. Hinge 1, although located within the neck, moves by straightening of the kinked helix h28 at the point of contact with the mRNA. Hinge 2 lies within a three-way helix junction that extends to the body through a second, noncovalent connection; its movement results from flexing between helices h34 and h35 in a plane orthogonal to the movement of hinge 1. Concerted movement at these two hinges accounts for the observed magnitudes of head rotation. Our findings also explain the mode of action of spectinomycin, an antibiotic that blocks translocation by binding to hinge 2.

Statistical mechanics of the denatured state of a protein using replica-averaged metadynamics

The characterization of denatured states of proteins is challenging because the lack of permanent structure in these states makes it difficult to apply to them standard methods of structural biology. In this work we use all-atom replica-averaged metadynamics (RAM) simulations with NMR chemical shift restraints to determine an ensemble of structures representing an acid-denatured state of the 86-residue protein ACBP. This approach has enabled us to reach convergence in the free energy landscape calculations, obtaining an ensemble of structures in relatively accurate agreement with independent experimental data used for validation. By observing at atomistic resolution the transient formation of native and non-native structures in this acid-denatured state of ACBP, we rationalize the effects of single-point mutations on the folding rate, stability, and transition-state structures of this protein, thus characterizing the role of the unfolded state in determining the folding process.

Understanding the influence of codon translation rates on cotranslational protein folding

Protein domains can fold into stable tertiary structures while they are synthesized by the ribosome in a process known as cotranslational folding. If a protein does not fold cotranslationally, however, it has the opportunity to do so post-translationally, that is, after the nascent chain has been fully synthesized and released from the ribosome. The rate at which a ribosome adds an amino acid encoded by a particular codon to the elongating nascent chain can vary significantly and is called the codon translation rate. Recent experiments have illustrated the profound impact that codon translation rates can have on the cotranslational folding process and the acquisition of function by nascent proteins. Synonymous codon mutations in an mRNA molecule change the chemical identity of a codon and its translation rate without changing the sequence of the synthesized protein. This change in codon translation rate can, however, cause a nascent protein to malfunction as a result of cotranslational misfolding. In some situations, such dysfunction can have profound implications; for example, it can alter the substrate specificity of an ABC transporter protein, resulting in patients who are nonresponsive to chemotherapy treatment. Thus, codon translation rates are crucial in coordinating protein folding in a cellular environment and can affect downstream cellular processes that depend on the proper functioning of newly synthesized proteins. As the importance of codon translation rates makes clear, a necessary aspect of fully understanding cotranslational folding lies in considering the kinetics of the process in addition to its thermodynamics. In this Account, we examine the contributions that have been made to elucidating the mechanisms of cotranslational folding by using the theoretical and computational tools of chemical kinetics, molecular simulations, and systems biology. These efforts have extended our ability to understand, model, and predict the influence of codon translation rates on cotranslational protein folding and misfolding. The application of such approaches to this important problem is creating a framework for making quantitative predictions of the impact of synonymous codon substitutions on cotranslational folding that has led to a novel hypothesis regarding the role of fast-translating codons in coordinating cotranslational folding. In addition, it is providing new insights into proteome-wide cotranslational folding behavior and making it possible to identify potential molecular mechanisms by which molecular chaperones can influence such behavior during protein synthesis. As we discuss in this Account, bringing together these theoretical developments with experimental approaches is increasingly helping answer fundamental questions about the nature of nascent protein folding on the ribosome.

Molecular Dynamics Simulations of Nucleic Acids. From Tetranucleotides to the Ribosome

We present a brief overview of explicit solvent molecular dynamics (MD) simulations of nucleic acids. We explain physical chemistry limitations of the simulations, namely, the molecular mechanics (MM) force field (FF) approximation and limited time scale. Further, we discuss relations and differences between simulations and experiments, compare standard and enhanced sampling simulations, discuss the role of starting structures, comment on different versions of nucleic acid FFs, and relate MM computations with contemporary quantum chemistry. Despite its limitations, we show that MD is a powerful technique for studying the structural dynamics of nucleic acids with a fast growing potential that substantially complements experimental results and aids their interpretation.

Modified Amber Force Field Correctly Models the Conformational Preference for Tandem GA pairs in RNA

Molecular mechanics with all-atom models was used to understand the conformational preference of tandem guanine-adenine (GA) noncanonical pairs in RNA. These tandem GA pairs play important roles in determining stability, flexibility, and structural dynamics of RNA tertiary structures. Previous solution structures showed that these tandem GA pairs adopt either imino (cis Watson-Crick/Watson-Crick A-G) or sheared (trans Hoogsteen/sugar edge A-G) conformations depending on the sequence and orientation of the adjacent closing base pairs. The solution structures (GCGGACGC)2 [Biochemistry, 1996, 35, 9677-9689] and (GCGGAUGC)2 [Biochemistry, 2007, 46, 1511-1522] demonstrate imino and sheared conformations for the two central GA pairs, respectively. These systems were studied using molecular dynamics and free energy change calculations for conformational changes, using umbrella sampling. For the structures to maintain their native conformations during molecular dynamics simulations, a modification to the standard Amber ff10 force field was required, which allowed the amino group of guanine to leave the plane of the base [J. Chem. Theory Comput., 2009, 5, 2088-2100] and form out-of-plane hydrogen bonds with a cross-strand cytosine or uracil. The requirement for this modification suggests the importance of out-of-plane hydrogen bonds in stabilizing the native structures. Free energy change calculations for each sequence demonstrated the correct conformational preference when the force field modification was used, but the extent of the preference is underestimated.