Single-molecule RNA folding

Single-molecule experiments significantly expand our capability to characterize complex dynamics of biological processes. This relatively new approach has contributed significantly to our understanding of the RNA folding problem. Recent single-molecule experiments, together with structural and biochemical characterizations of RNA at the ensemble level, show that RNA molecules typically fold across a highly rugged energy landscape. As a result, long-lived folding intermediates, multiple folding pathways, and heterogeneous conformational dynamics are commonly found for RNA enzymes. While initial results have suggested that stable secondary structures are partly responsible for the rugged energy landscape of RNA, a complete mechanistic understanding of the complex folding behavior has not yet been obtained. A combination of single-molecule experiments, which are well suited to analyze transient and heterogeneous dynamic behaviors, with ensemble characterizations that can provide structural information at a superior resolution will likely provide more answers.     

The Two-Step Clustering Approach for Metastable States Learning

Understanding the energy landscape and the conformational dynamics is crucial for studying many biological or chemical processes, such as protein–protein interaction and RNA folding. Molecular Dynamics (MD) simulations have been a major source of dynamic structure. Although many methods were proposed for learning metastable states from MD data, some key problems are still in need of further investigation. Here, we give a brief review on recent progresses in this field, with an emphasis on some popular methods belonging to a two-step clustering framework, and hope to draw more researchers to contribute to this area.     

Tracking dynamics of glass formers and modifiers via correlation maps of molecular dynamics simulation

In this study, we describe a method to construct a correlation map that captures the evolution of species-specific dynamic information through the spatial correlation of high-dimensional time-series molecular dynamics (MD) simulation dataset for a series of borosilicate glasses. The correlation is based on ‘displacement’ between a pair of atomic configurations determined by the root mean square distance (RMSD) metric. We implement the correlation map as a quantitative visualization tool that provides a compressed representation of a high-dimensional molecular dynamics dataset to inspect various physical aspects and capture distinct atomic dynamics—from large fluctuations to small local oscillations—for high-temperature melt, linear cooling, and low-temperature equilibration processes during molecular dynamics simulation of glasses. We capture species-specific dynamics using this method that show different cooling dynamics for different glass formers and modifiers, especially the onset of slow dynamics and the variation of atomic dynamics at high temperatures. Furthermore, we show that the species-specific atomic dynamics have structural origins that depend on the composition of the simulated borosilicate glasses. The correlation map serves as a visualization tool to rapidly survey changes in atomic configurations during different simulation conditions.     

Conservation and specialization in PAS domain dynamics

The PAS (Per-ARNT-Sim) superfamily is presented as a well-suited study case to demonstrate how comparison of functional motions among distant homologous proteins with conserved fold characteristics may give insight into their functional specialization. Based on the importance of structural flexibility of the receptive structures in anticipating the signal-induced conformational changes of these sensory systems, the dynamics of these structures were analysed. Molecular dynamics was proved to be an effective method to obtain a reliable picture of the dynamics of the crystal structures of HERG, phy3, PYP and FixL, provided that an extensive conformational space sampling is performed. Other reliable sources of dynamic information were the ensembles of NMR structures of hPASK, HIF-2alpha and PYP. Essential dynamics analysis was successfully employed to extract the relevant information from the sampled conformational spaces. Comparison of motion patterns in the essential subspaces, based on the structural alignment, allowed identification of the specialized region in each domain. This appears to be evolved in the superfamily by following a specific trend, that also suggests the presence of a limited number of general solutions adopted by the PAS domains to sense external signals. These findings may give insight into unknown mechanisms of PAS domains and guide further experimental studies.     

Recognition of planar and nonplanar ligands in the malachite green-RNA aptamer complex

Ribonucleic acids are an attractive drug target owing to their central role in many pathological processes. Notwithstanding this potential, RNA has only rarely been successfully targeted with novel drugs. The difficulty of targeting RNA is at least in part due to the unusual mode of binding found in most small-molecule-RNA complexes: the ligand binding pocket of the RNA is largely unstructured in the absence of ligand and forms a defined structure only with the ligand acting as scaffold for folding. Moreover, electrostatic interactions between RNA and ligand can also induce significant changes in the ligand structure due to the polyanionic nature of the RNA. Aptamers are ideal model systems to study these kinds of interactions owing to their small size and the ease with which they can be evolved to recognize a large variety of different ligands. Here we present the solution structure of an RNA aptamer that binds triphenyl dyes in complex with malachite green and compare it with a previously determined crystal structure of a complex formed with tetramethylrosamine. The structures illustrate how the same RNA binding pocket can adapt to accommodate both planar and nonplanar ligands. Binding studies with single- and double-substitution mutant aptamers are used to correlate three-dimensional structure with complex stability. The two RNA-ligand complex structures allow a discussion of structural changes that have been observed in the ligand in the context of the overall complex structure. Base pairing and stacking interactions within the RNA fold the phosphate backbone into a structure that results in an asymmetric charge distribution within the binding pocket that forces the ligand to adapt through a redistribution of the positive partial charge.     

Modeling and selection of flexible proteins for structure-based drug design: backbone and side chain movements in p38 MAPK

Receptor rearrangement upon ligand binding (induced fit) is a major stumbling block in docking and virtual screening. Even though numerous studies have stressed the importance of including protein flexibility in ligand docking, currently available methods provide only a partial solution to the problem. Most of these methods, being computer intensive, are often impractical to use in actual drug discovery settings. We had earlier shown that ligand-induced receptor side-chain conformational changes could be modeled statistically using data on known receptor-ligand complexes. In this paper, we show that a similar approach can be used to model more complex changes like backbone flips and loop movements. We have used p38 MAPK as a test case and have shown that a few simple structural features of ligands are sufficient to predict the induced variation in receptor conformations. Rigorous validation, both by internal resampling methods and on an external test set, corroborates this finding and demonstrates the robustness of the models. We have also compared our results with those from an earlier molecular dynamics simulation study on DFG loop conformations of p38 MAPK, and found that the results matched in the two cases. Our statistical approach enables one to predict the final ligand-induced conformation of the active site of a protein, based on a few ligand properties, prior to docking the ligand. We can do this without having to trace the step-by-step process by which this state is arrived at (as in molecular dynamics simulations), thereby drastically reducing computational effort.     

Modeling the structural evolution of carbide-derived carbons using quenched molecular dynamics

We develop morphologically realistic models for amorphous carbon using quenched molecular dynamics. We show that as the thermal quench rate is decreased, the model structures become more highly ordered, forming large graphene-like fragments and regularly shaped porous features. The evolution of these changes is compared with a series of carbide-derived carbons synthesized from crystalline TiC using different chlorination temperatures. In general, we find that the structural changes in the models are similar to those seen in experiment and that these changes have a significant impact on pore size distributions, specific surface areas, and adsorption isotherms, which are used to empirically characterize microporous carbons.     

Mass Spectrometry Coupled Experiments and Protein Structure Modeling Methods

With the accumulation of next generation sequencing data, there is increasing interest in the study of intra-species difference in molecular biology, especially in relation to disease analysis. Furthermore, the dynamics of the protein is being identified as a critical factor in its function. Although accuracy of protein structure prediction methods is high, provided there are structural templates, most methods are still insensitive to amino-acid differences at critical points that may change the overall structure. Also, predicted structures are inherently static and do not provide information about structural change over time. It is challenging to address the sensitivity and the dynamics by computational structure predictions alone. However, with the fast development of diverse mass spectrometry coupled experiments, low-resolution but fast and sensitive structural information can be obtained. This information can then be integrated into the structure prediction process to further improve the sensitivity and address the dynamics of the protein structures. For this purpose, this article focuses on reviewing two aspects: the types of mass spectrometry coupled experiments and structural data that are obtainable through those experiments; and the structure prediction methods that can utilize these data as constraints. Also, short review of current efforts in integrating experimental data in the structural modeling is provided.     

A comparison of published crystalline structures of poly(tetramethylene terephthalate)

Recently, various crystalline structures have been published for poly(tetramethylene terephthalate) in both the relaxed and strained forms. The differences between the experimental procedures which have been used to determine these structures are critically discussed in the present paper. It is shown that the unit cell parameters obtained by the various investigators for the relaxed (or α) form do not differ significantly. Improvements can be made in some of the procedures used in structure determination — in particular it is recommended that weighting schemes be used to prevent the stronger reflections unduly biasing the refinement procedure — and these lead to small changes in some of the published structures of the α-form. By using a diffractometer to plot profiles of equatorial reflections it is shown that one of the published cells of the strained (or β) form cannot be correct, and this leads to an incorrect structure. Small changes in the other published structure are also necessary.     

Thermodynamics and kinetics of underpotential deposition of metal monolayers on polycrystalline substrates

The equilibrium and dynamic properties of underpotential deposits are discussed, as are some problems of methodology in estimating these properties. In particular, there is a special emphasis on interpreting the ring—disc electrode response during the underpotential deposition, UPD, of silver on polycrystalline gold. The underpotential-coverage relationship as a function of solution composition provides an insight into particle—substrate, particle—particle and particle—electric field interactions. Some of the features that emerge from the analysis of equilibrium UPD behaviour are: (a) the predominant influence of the particle—substrate interaction through work function changes, (b) the absence of discreteness of charge effects due to any partially charged UPD species over wide coverage ranges, and (c) the importance of particle—particle interactions in causing multiple energy states. The dynamic charge flux during the UPD process is analysed in terms of dynamic changes in double layer capacitance and the potential of zero charge, and other parallel processes through the formalism of a dynamic electrosorption valency, which includes both charge separation and charge-transfer components. The dynamic material flux of the UPD species is found to be under mixed control by solution mass transport, surface adsorption and charge-transfer processes. The phenomenological rate parameters and double layer capacitance changes suggest the formation of ordered structures at higher UPD coverages and random aggregates at lower coverages.     

蛋白质体系分子动力学模拟的前沿进展-从介科学角度重新审视

蛋白质是生命的物质基础,是生命活动的主要承担者,对蛋白质时空多尺度结构及其控制机制的深入理解是探索生命起源、病理认知及新药开发的基础. 受实验表征手段及时空分辨率的限制,计算机模拟已成为研究蛋白质体系结构及功能的重要手段之一. 由于蛋白质体系模拟所涉及的时间和空间跨度均相当大,因此,准确且快速地描述其时空多尺度结构,从而分析体系的控制机制及相关生理过程,成为分子动力学模拟面临的巨大挑战. 本工作对近半个世纪以来的分子模拟方法,特别是分子动力学方法和相关的增强采样技术在蛋白质体系研究中的应用进行了总结,综述了近年来分子动力学的理论模型和算法的发展,并介绍了这些方法在结构化蛋白质的天然结构与构象变化、固有无序蛋白质的动态结构及其结合底物的动力学过程及分子机理、分子伴侣及病毒等蛋白质复合物体系中的研究成果;汇总了高性能计算的飞速发展所带动的分子动力学模拟软件的变革,拓展了蛋白质模拟的时空尺度,重点阐述了大规模高性能分子动力学模拟在蛋白质研究中的应用;最后,基于介科学理论的飞速发展及其在多种复杂体系的成功运用,对未来蛋白质体系的模拟方法和理论研究的趋势进行了思考和展望.     

The Role of Disordered Ribosomal Protein Extensions in the Early Steps of Eubacterial 50 S Ribosomal Subunit Assembly

Although during the past decade research has shown the functional importance of disorder in proteins, many of the structural and dynamics properties of intrinsically unstructured proteins (IUPs) remain to be elucidated. This review is focused on the role of the extensions of the ribosomal proteins in the early steps of the assembly of the eubacterial 50 S subunit. The recent crystallographic structures of the ribosomal particles have revealed the picture of a complex assembly pathway that condenses the rRNA and the ribosomal proteins into active ribosomes. However, little is know about the molecular mechanisms of this process. It is thought that the long basic r-protein extensions that penetrate deeply into the subunit cores play a key role through disorder-order transitions and/or co-folding mechanisms. A current view is that such structural transitions may facilitate the proper rRNA folding. In this paper, the structures of the proteins L3, L4, L13, L20, L22 and L24 that have been experimentally found to be essential for the first steps of ribosome assembly have been compared. On the basis of their structural and dynamics properties, three categories of extensions have been identified. Each of them seems to play a distinct function. Among them, only the coil-helix transition that occurs in a phylogenetically conserved cluster of basic residues of the L20 extension appears to be strictly required for the large subunit assembly in eubacteria. The role of α helix-coil transitions in 23 S RNA folding is discussed in the light of the calcium binding protein calmodulin that shares many structural and dynamics properties with L20.     

Normal Mode Dynamics Comparison of Proteins

Sequence and structure comparisons are fundamental techniques that enable exploration of the sequence and structural spaces of proteins. Homology detection, function prediction, and protein classification rely on these techniques. However, protein structures are dynamic, rather than static, and such protein dynamics play a key role in a wide range of biological activities. Therefore, protein dynamics comparison algorithms may shed light on the relationship between proteins′ dynamics and function. Here, we review different strategies for comparing dynamics of proteins. Special emphasis is given to newly developed algorithms that compare dynamics of proteins with no apparent sequence or structural similarity and to the qualitative differences between these algorithms.     

Dynamics-based amplification of RNA function and its characterization by using NMR spectroscopy

The ever-increasing cellular roles ascribed to RNA raise fundamental questions regarding how a biopolymer composed of only four chemically similar building-block nucleotides achieves such functional diversity. Here, I discuss how RNA achieves added mechanistic and chemical complexity by undergoing highly controlled conformational changes in response to a variety of cellular signals. I examine pathways for achieving selectivity in these conformational changes that rely to different extents on the structure and dynamics of RNA. Finally, I review solution-state NMR techniques that can be used to characterize RNA structural dynamics and its relationship to function.     

NMR Studies of HAR1 RNA Secondary Structures Reveal Conformational Dynamics in the Human RNA

Comparative genomics has shown that noncoding RNAs can display substantial differences between humans and chimpanzees. The human accelerated region 1 (HAR1) is a section in the human genome that exhibits the most strongly accelerated rate of nucleotide substitution in relation to the chimpanzee genome. It is associated with higher cognitive functions in human brains. The HAR1 region of the HAR1F gene is transcribed into a 118 nt noncoding RNA. We provide experimental data to validate available secondary structure models of chimpanzee and human HAR1 RNA by utilizing CD and NMR spectroscopy and applying a “divide‐and‐conquer” strategy. The mutations lead to more dynamic secondary and tertiary structure in the human HAR1 RNA, presumably as part of its function. We have also determined NMR solution structures of helix H1 as the most conserved part of the chimpanzee and human HAR1 RNAs. Helix H1 contains a GAA asymmetric internal loop, the structure of which had not been solved previously. 37 nt chimpanzee and human RNA fragments (c37 and h37 RNAs) differ in a single base pair. h37 RNA folds into a slightly more stable and rigid structure than c37 RNA. Both NMR structures show structural heterogeneity of the residues corresponding to the GAA loop.     

Influence of crystallographic properties on antimony electrode potential—II. Monocrystalline material

Earlier investigation on antimony—antimony oxide electrodes have shown that electrodes with only a few crystal grains exposed to the measuring solution in a plane polished electrode surface are to be preferred for stability reasons. Here, results from measurements on monocrystalline electrode surfaces are discussed. It is shown that these posses a still more stable potential, both regarding short-term and long-term stability. The potential behaviour is compared to structural changes in the electrode surface, and an explanation for this behaviour is suggested in terms of corrosion theory.