Conformational deformability of RNA: a harmonic mode analysis

Predicting RNA structure and dynamics with deep learning and solution scattering

Advanced deep learning and statistical methods can predict structural models for RNA molecules. However, RNAs are flexible, and it remains difficult to describe their macromolecular conformations in solutions where varying conditions can induce conformational changes. Small-angle x-ray scattering (SAXS) in solution is an efficient technique to validate structural predictions by comparing the experimental SAXS profile with those calculated from predicted structures. There are two main challenges in comparing SAXS profiles to RNA structures: the absence of cations essential for stability and charge neutralization in predicted structures and the inadequacy of a single structure to represent RNA's conformational plasticity. We introduce a solution conformation predictor for RNA (SCOPER) to address these challenges. This pipeline integrates kinematics-based conformational sampling with the innovative deep learning model, IonNet, designed for predicting Mg2+ ion binding sites. Validated through benchmarking against 14 experimental data sets, SCOPER significantly improved the quality of SAXS profile fits by including Mg2+ ions and sampling of conformational plasticity. We observe that an increased content of monovalent and bivalent ions leads to decreased RNA plasticity. Therefore, carefully adjusting the plasticity and ion density is crucial to avoid overfitting experimental SAXS data. SCOPER is an efficient tool for accurately validating the solution state of RNAs given an initial, sufficiently accurate structure and provides the corrected atomistic model, including ions.

Predicting RNA Structure and Dynamics with Deep Learning and Solution Scattering

Advanced deep learning and statistical methods can predict structural models for RNA molecules. However, RNAs are flexible, and it remains difficult to describe their macromolecular conformations in solutions where varying conditions can induce conformational changes. Small-angle X-ray scattering (SAXS) in solution is an efficient technique to validate structural predictions by comparing the experimental SAXS profile with those calculated from predicted structures. There are two main challenges in comparing SAXS profiles to RNA structures: the absence of cations essential for stability and charge neutralization in predicted structures and the inadequacy of a single structure to represent RNA's conformational plasticity. We introduce Solution Conformation Predictor for RNA (SCOPER) to address these challenges. This pipeline integrates kinematics-based conformational sampling with the innovative deep-learning model, IonNet, designed for predicting Mg2+ ion binding sites. Validated through benchmarking against fourteen experimental datasets, SCOPER significantly improved the quality of SAXS profile fits by including Mg2+ ions and sampling of conformational plasticity. We observe that an increased content of monovalent and bivalent ions leads to decreased RNA plasticity. Therefore, carefully adjusting the plasticity and ion density is crucial to avoid overfitting experimental SAXS data. SCOPER is an efficient tool for accurately validating the solution state of RNAs given an initial, sufficiently accurate structure and provides the corrected atomistic model, including ions.

NMR structures and magnetic force spectroscopy studies of small molecules binding to models of an RNA CAG repeat expansion

RNA repeat expansions fold into stable structures and cause microsatellite diseases such as Huntington's disease (HD), myotonic dystrophy type 1 (DM1), and spinocerebellar ataxias (SCAs). The trinucleotide expansion of r(CAG), or r(CAG)exp, causes both HD and SCA3, and the RNA's toxicity has been traced to its translation into polyglutamine (polyQ; HD) as well as aberrant pre-mRNA alternative splicing (SCA3 and HD). Previously, a small molecule, 1, was discovered that binds to r(CAG)exp and rescues aberrant pre-mRNA splicing in patient-derived fibroblasts by freeing proteins bound to the repeats. Here, we report the structures of single r(CAG) repeat motif (5'CAG/3'GAC where the underlined adenosines form a 1×1 nucleotide internal loop) in complex with 1 and two other small molecules via nuclear magnetic resonance (NMR) spectroscopy combined with simulated annealing. Compound 2 was designed based on the structure of 1 bound to the RNA while 3 was selected as a diverse chemical scaffold. The three complexes, although adopting different 3D binding pockets upon ligand binding, are stabilized by a combination of stacking interactions with the internal loop's closing GC base pairs, hydrogen bonds, and van der Waals interactions. Molecular dynamics (MD) simulations performed with NMR-derived restraints show that the RNA is stretched and bent upon ligand binding with significant changes in propeller-twist and opening. Compound 3 has a distinct mode of binding by insertion into the helix, displacing one of the loop nucleotides into the major groove and affording a rod-like shape binding pocket. In contrast, 1 and 2 are groove binders. A series of single molecule magnetic force spectroscopy studies provide a mechanistic explanation for how bioactive compounds might rescue disease-associated cellular phenotypes.

The dynamics of t1 adenosine binding on human Argonaute 2: Understanding recognition with conformational selection

The control of expression in genetic regulation is a fundamental process for cell life. In RNA-mediated silencing, human Argonaute-2 protein (hAgo2) uses sequence information encoded in small RNAs (guide) to identify complementary sites in messenger RNAs (target) for repression. The specificity of this molecular recognition lies at the basis of the mechanisms that control the expression of thousands of genes, which necessarily requires a fine tuning of complex events. Among these, the binding of the first nucleotide of the target RNA (t1) is emerging as an important modulator of hAgo2-mediated machinery. Using atomistic molecular dynamics-derived analyses, we address the mechanism behind t1-dependent regulation and study the impact of different t1 nucleotides (t1A, t1C, t1G, t1U) on the conformational dynamics of both hAgo2 and guide-target RNAs. Only when an adenine is found at this position, t1 directly interacts with a specific hAgo2 binding pocket, favoring the stabilization of target binding. Our findings show that hAgo2 exploits a dynamic recognition mechanism of the t1-target thanks to a modulation of RNA conformations. Here, t1-adenine is the only nucleobase endowed with a dual binding mode: a T-shape and a co-planar conformation, respectively, orthogonal and parallel to the following base-pairs of guide-target duplex. This triggers a composite set of molecular interactions that stabilizes distinctive conformational ensembles. Our comparative analyses show characteristic traits of local and global dynamic interplay between hAgo2 and the RNA molecules and highlight how t1A binding acts as a molecular switch for target recognition and complex stabilization. Implications for future mechanistic studies are discussed.

Effects of Noncanonical Base Pairing on RNA Folding: Structural Context and Spatial Arrangements of G·A Pairs

Noncanonical base pairs play important roles in assembling the three-dimensional structures critical to the diverse functions of RNA. These associations contribute to the looped segments that intersperse the canonical double-helical elements within folded, globular RNA molecules. They stitch together various structural elements, serve as recognition elements for other molecules, and act as sites of intrinsic stiffness or deformability. This work takes advantage of new software (DSSR) designed to streamline the analysis and annotation of RNA three-dimensional structures. The multiscale structural information gathered for individual molecules, combined with the growing number of unique, well-resolved RNA structures, makes it possible to examine the collective features deeply and to uncover previously unrecognized patterns of chain organization. Here we focus on a subset of noncanonical base pairs involving guanine and adenine and the links between their modes of association, secondary structural context, and contributions to tertiary folding. The rigorous descriptions of base-pair geometry that we employ facilitate characterization of recurrent geometric motifs and the structural settings in which these arrangements occur. Moreover, the numerical parameters hint at the natural motions of the interacting bases and the pathways likely to connect different spatial forms. We draw attention to higher-order multiplexes involving two or more G·A pairs and the roles these associations appear to play in bridging different secondary structural units. The collective data reveal pairing propensities in base organization, secondary structural context, and deformability and serve as a starting point for further multiscale investigations and/or simulations of RNA folding.

Computing Molecular Devices in L.major through Transcriptome Analysis: Structured Simulation Approach

In the modern era of post genomics and transcriptomics, non-coding RNAs and non-coding regions of many RNAs are a big puzzle when we try deciphering their role in specific gene function. Gene function assessment is a main task wherein high throughput technologies provide an impressive body of data that enables the design of hypotheses linking genes to phenotypes. Gene knockdown technologies and RNA-dependent gene silencing are the most frequent approaches to assess the role of key effectors in a particular scenario. Ribozymes are effective modulators of gene expression because of their simple structure, site-specific cleavage activity, and catalytic potential. In our study, after an extensive transcriptomic search of Leishmania major transcriptome we found a Putative ATP dependent DNA helicase (Lmjf_09_0590) 3’ UTR which has a structural signature similar to well-known HDV hammerhead ribozyme, even though they have variable sequence motifs. Henceforth, to determine their structural stability and sustainability we analyzed our predicted structural model of this 3’UTR with a 30ns MD simulation, further confirmed with 100ns MD simulation in presence of 5mM MgCl₂ ionic environment. In this environment, structural stability was significantly improved by bonded interactions between a RNA backbone and Mg²⁺ ions. These predictions were further validated in silico using RNA normal mode analysis and anisotropic network modelling (ANM) studies. The study may be significantly imparted to know the functional importance of many such 3’UTRs to predict their role in a mechanistic manner.

Characterizing RNA ensembles from NMR data with kinematic models

Functional mechanisms of biomolecules often manifest themselves precisely in transient conformational substates. Researchers have long sought to structurally characterize dynamic processes in non-coding RNA, combining experimental data with computer algorithms. However, adequate exploration of conformational space for these highly dynamic molecules, starting from static crystal structures, remains challenging. Here, we report a new conformational sampling procedure, KGSrna, which can efficiently probe the native ensemble of RNA molecules in solution. We found that KGSrna ensembles accurately represent the conformational landscapes of 3D RNA encoded by NMR proton chemical shifts. KGSrna resolves motionally averaged NMR data into structural contributions; when coupled with residual dipolar coupling data, a KGSrna ensemble revealed a previously uncharacterized transient excited state of the HIV-1 trans-activation response element stem-loop. Ensemble-based interpretations of averaged data can aid in formulating and testing dynamic, motion-based hypotheses of functional mechanisms in RNAs with broad implications for RNA engineering and therapeutic intervention.

Transcriptome de novo assembly sequencing and analysis of the toxic dinoflagellate Alexandrium catenella using the Illumina platform

In this article, high-throughput de novo transcriptomic sequencing was performed in Alexandrium catenella, which provided the first view of the gene repertoire in this dinoflagellate based on next-generation sequencing (NGS) technologies. A total of 118,304 unigenes were identified with an average length of 673bp (base pair). Of these unigenes, 77,936 (65.9%) were annotated with known proteins based on sequence similarities, among which 24,149 and 22,956 unigenes were assigned to gene ontology categories (GO) and clusters of orthologous groups (COGs), respectively. Furthermore, 16,467 unigenes were mapped onto 322 pathways using the Kyoto Encyclopedia of Genes and Genomes Pathway database (KEGG). We also detected 1143 simple sequence repeats (SSRs), in which the tri-nucleotide repeat motif (69.3%) was the most abundant. The genetic facts and significance derived from the transcriptome dataset were suggested and discussed. All four core nucleosomal histones and linker histones were detected, in addition to the unigenes involved in histone modifications.190 unigenes were identified as being involved in the endocytosis pathway, and clathrin-dependent endocytosis was suggested to play a role in the heterotrophy of A. catenella. A conserved 22-nt spliced leader (SL) was identified in 21 unigenes which suggested the existence of trans-splicing processing of mRNA in A. catenella.

Mesoscopic model parametrization of hydrogen bonds and stacking interactions of RNA from melting temperatures

Information about molecular interactions in DNA can be obtained from experimental melting temperature data by using mesoscopic statistical physics models. Here, we extend the technique to RNA and show that the new parameters correctly reproduce known properties such as the stronger hydrogen bonds of AU base pairs. We also were able to calculate a complete set of elastic constants for all 10 irreducible combinations of nearest neighbours (NNs). We believe that this is particularly useful as experimentally derived information about RNA elasticity is relatively scarce. The melting temperature prediction using the present model improves over those from traditional NN model, providing thus an alternative way to calculate these temperatures for RNA. Additionally, we calculated the site-dependent base pair oscillation to explain why RNA shows larger oscillation amplitudes despite having stronger AU hydrogen bonds.

Synthesis, gene silencing, and molecular modeling studies of 4'-C-aminomethyl-2'-O-methyl modified small interfering RNAs

The linear syntheses of 4'-C-aminomethyl-2'-O-methyl uridine and cytidine nucleoside phosphoramidites were achieved using glucose as the starting material. The modified RNA building blocks were incorporated into small interfering RNAs (siRNAs) by employing solid phase RNA synthesis. Thermal melting studies showed that the modified siRNA duplexes exhibited slightly lower T(m) (∼1 °C/modification) compared to the unmodified duplex. Molecular dynamics simulations revealed that the 4'-C-aminomethyl-2'-O-methyl modified nucleotides adopt South-type conformation in a siRNA duplex, thereby altering the stacking and hydrogen-bonding interactions. These modified siRNAs were also evaluated for their gene silencing efficiency in HeLa cells using a luciferase-based reporter assay. The results indicate that the modifications are well tolerated in various positions of the passenger strand and at the 3' end of the guide strand but are less tolerated in the seed region of the guide strand. The modified siRNAs exhibited prolonged stability in human serum compared to unmodified siRNA. This work has implications for the use of 4'-C-aminomethyl-2'-O-methyl modified nucleotides to overcome some of the challenges associated with the therapeutic utilities of siRNAs.

Molecular recognition of RNA: challenges for modelling interactions and plasticity

There is growing interest in molecular recognition processes of RNA because of RNA's widespread involvement in biological processes. Computational approaches are increasingly used for analysing and predicting binding to RNA, fuelled by encouraging progress in developing simulation, free energy and docking methods for nucleic acids. These developments take into account challenges regarding the energetics of RNA-ligand binding, RNA plasticity, and the presence of water molecules and ions in the binding interface. Accordingly, we will detail advances in force field and scoring function development for molecular dynamics (MD) simulations, free energy computations and docking calculations of nucleic acid complexes. Furthermore, we present methods that can detect moving parts within RNA structures based on graph-theoretical approaches or normal mode analysis (NMA). As an example of the successful use of these developments, we will discuss recent structure-based drug design approaches that focus on the bacterial ribosomal A-site RNA as a drug target.

Coupling of fast and slow modes in the reaction pathway of the minimal hammerhead ribozyme cleavage

By employing classical molecular dynamics, correlation analysis of coupling between slow and fast dynamical modes, and free energy (umbrella) sampling using classical as well as mixed quantum mechanics molecular mechanics force fields, we uncover a possible pathway for phosphoryl transfer in the self-cleaving reaction of the minimal hammerhead ribozyme. The significance of this pathway is that it initiates from the minimal hammerhead crystal structure and describes the reaction landscape as a conformational rearrangement followed by a covalent transformation. The delineated mechanism is catalyzed by two metal (Mg(2+)) ions, proceeds via an in-line-attack by CYT 17 O2' on the scissile phosphorous (ADE 1.1 P), and is therefore consistent with the experimentally observed inversion configuration. According to the delineated mechanism, the coupling between slow modes involving the hammerhead backbone with fast modes in the cleavage site appears to be crucial for setting up the in-line nucleophilic attack.

B-DNA under stress: over- and untwisting of DNA during molecular dynamics simulations

The twist flexibility of DNA is central to its many biological functions. Explicit solvent molecular dynamics simulations in combination with an umbrella sampling restraining potential have been employed to study induced twist deformations in DNA. Simulations allowed us to extract free energy profiles for twist deformations and were performed on six DNA dodecamer duplexes to cover all 10 possible DNA basepair steps. The shape of the free energy curves was similar for all duplexes. The calculated twist deformability was in good agreement with experiment and showed only modest variation for the complete duplexes. However, the response of the various basepair steps on twist stress was highly nonuniform. In particular, pyrimidine/purine steps were much more flexible than purine/purine steps followed by purine/pyrimidine steps. It was also possible to extract correlations of twist changes and other helical as well as global parameters of the DNA molecules. Twist deformations were found to significantly alter the local as well as global shape of the DNA modulating the accessibility for proteins and other ligands. Severe untwisting of DNA below an average of 25 degrees per basepair step resulted in the onset of a global structural transition with a significantly smaller twist at one end of the DNA compared to the other.

Conformational Statistics of Semi-Flexible Macromolecular Chains with Internal Joints

Fluctuations in the bending angles at internal irregularities of DNA and RNA (such as symmetric loops, bulges, and nicks/gaps) have been observed from various experiments. However, little effort has been made to computationally predict and explain the statistical behavior of semi-flexible chains with internal defects. In this paper, we describe the general structure of these macromolecular chains as inextensible elastic chains with one or more internal joints which have limited ranges of rotation, and propose a method to compute the probability density functions of the end-to-end pose of these macromolecular chains. Our method takes advantage of the operational properties of the non-commutative Fourier transform for the group of rigid-body motions in three-dimensional space, SE(3). Two representative types of joints, the hinge for planar rotation and the ball joint for spatial rotation, are discussed in detail. The proposed method applies to various stiffness models of semi-flexible chain-like macromolecules. Examples are calculated using the Kratky-Porod model with specified stiffness, angular fluctuation, and joint locations. Entropic effects associated with internal angular fluctuations of semi-flexible macromolecular chains with internal joints can be computed using this formulation. Our method also provides a potential tool to detect the existence of internal irregularities.

Common patterns in type II restriction enzyme binding sites

Restriction enzymes are among the best studied examples of DNA binding proteins. In order to find general patterns in DNA recognition sites, which may reflect important properties of protein–DNA interaction, we analyse the binding sites of all known type II restriction endonucleases. We find a significantly enhanced GC content and discuss three explanations for this phenomenon. Moreover, we study patterns of nucleotide order in recognition sites. Our analysis reveals a striking accumulation of adjacent purines (R) or pyrimidines (Y). We discuss three possible reasons: RR/YY dinucleotides are characterized by (i) stronger H-bond donor and acceptor clusters, (ii) specific geometrical properties and (iii) a low stacking energy. These features make RR/YY steps particularly accessible for specific protein–DNA interactions. Finally, we show that the recognition sites of type II restriction enzymes are underrepresented in host genomes and in phage genomes.

Sequence-dependent motions of DNA: a normal mode analysis at the base-pair level

Computer simulation of the dynamic structure of DNA can be carried out at various levels of resolution. Detailed high resolution information about the motions of DNA is typically collected for the atoms in a few turns of double helix. At low resolution, by contrast, the sequence-dependence features of DNA are usually neglected and molecules with thousands of base pairs are treated as ideal elastic rods. The present normal mode analysis of DNA in terms of six base-pair "step" parameters per chain residue addresses the dynamic structure of the double helix at intermediate resolution, i.e., the mesoscopic level of a few hundred base pairs. Sequence-dependent effects are incorporated into the calculations by taking advantage of "knowledge-based" harmonic energy functions deduced from the mean values and dispersion of the base-pair "step" parameters in high-resolution DNA crystal structures. Spatial arrangements sampled along the dominant low frequency modes have end-to-end distances comparable to those of exact polymer models which incorporate all possible chain configurations. The normal mode analysis accounts for the overall bending, i.e., persistence length, of the double helix and shows how known discrepancies in the measured twisting constants of long DNA molecules could originate in the deformability of neighboring base-pair steps. The calculations also reveal how the natural coupling of local conformational variables affects the global motions of DNA. Successful correspondence of the computed stretching modulus with experimental data requires that the DNA base pairs be inclined with respect to the direction of stretching, with chain extension effected by low energy transverse motions that preserve the strong van der Waals' attractions of neighboring base-pair planes. The calculations further show how one can "engineer" the macroscopic properties of DNA in terms of dimer deformability so that polymers which are intrinsically straight in the equilibrium state exhibit the mesoscopic bending anisotropy essential to DNA curvature and loop formation.

Conformational analysis of DNA-trinucleotide-hairpin-loop structures using a continuum solvent model

A number of trinucleotide sequences in DNA can form compact and stable hairpin loops that may have significance for DNA replication and transcription. The conformational analysis of these motifs is important for an understanding of the function and design of nucleic acid structures. Extensive conformational searches have been performed on three experimentally known trinucleotide hairpin loops (AGC, AAA, and GCA) closed by a four-base-pair stem. An implicit solvation model based on the generalized Born method has been employed during energy minimization and conformational search. In addition, energy-minimized conformers were evaluated using a finite-difference Poisson-Boltzmann approach. For all three loop sequences, conformations close to experiment were found as lowest-energy structures among several thousand alternative energy minima. The inclusion of reaction-field contributions was found to be important for a realistic conformer ranking. Most generated hairpin loop structures within approximately 5 kcal x mol(-1) of the lowest-energy structure have a similar topology. Structures within approximately 10 kcal x mol(-1) could be classified into about five structural families representing distinct arrangements of loop nucleotides. Although a large number of backbone torsion angle combinations were compatible with each structural class, some specific patterns could be identified. Harmonic mode analysis was used to account for differences in conformational flexibility of low-energy sub-states. Class-specific differences in the pattern of atomic fluctuations along the sequence were observed; however, inclusion of conformational entropy contributions did not change ranking of structural classes. For an additional loop sequence (AAG) with no available experimental structure, the approach suggests a lowest-energy loop topology overall similar to the other three loop sequences but closed by a different non-canonical base-pairing scheme.

Comparison of molecular dynamics and harmonic mode calculations on RNA

Conformational fluctuations of a double-stranded RNA oligonucleotide have been calculated from a two nanosecond molecular dynamics simulation including explicit waters and ions and from a harmonic mode analysis. The harmonic mode analysis was performed in the absence of solvent using various effective dielectric screening functions. RNA flexibility was analyzed and compared at the level of atomic position fluctuations, helical base-pair descriptor fluctuations and global helix bending, stretching, and twisting flexibilities. Although quantitative differences were found, the qualitative pattern of atomic position and helical descriptor fluctuations along the sequence was similar for both methods. For the helical descriptor flexibility, the largest differences were observed for base-pair roll and rise that showed two times larger fluctuations in the molecular dynamics simulation. A significant overlap between the sub-space spanned by soft principal components calculated from the molecular dynamics simulation and harmonic modes was found. Both approaches predict a negative covariation for most helical base-pair step descriptors of neighboring base pair steps (with the exception of rise), which tend to stiffen the RNA at the global level. The RNA persistence length extracted from the molecular dynamics simulation (350-600 A) is smaller than the experimental value ( approximately 720 A) and estimates based on the harmonic mode approach (1100-1700 A).

Simulation of the structure and dynamics of nonhelical RNA motifs

Computer simulation methods are increasingly being used to study possible conformations and dynamics of structural motifs in RNA. Recent results of molecular dynamics simulations and continum solvent studies of RNA structures and RNA-ligand complexes show promising agreement with experimental data. Combined with the ongoing progress in the experimental characterization of RNA structure and thermodynamics, these computational approaches can help to better understand the mechanism of RNA structure formation and the binding of ligands.