U1A protein-stem loop 2 RNA recognition: prediction of structural differences from protein mutations

Examining the capacity of human U1 snRNA variants to facilitate pre-mRNA splicing

The human U1 snRNA is encoded by a multigene family consisting of transcribed variants and defective pseudogenes. Many variant U1 (vU1) snRNAs have been demonstrated to not only be transcribed but also processed by the addition of a trimethylated guanosine cap, packaged into snRNPs, and assembled into spliceosomes; however, their capacity to facilitate pre-mRNA splicing has, so far, not been tested. A recent systematic analysis of the human snRNA genes identified 178 U1 snRNA genes that are present in the genome as either tandem arrays or single genes on multiple chromosomes. Of these, 15 were found to be expressed in human tissues and cell lines, although at significantly low levels from their endogenous loci, <0.001% of the canonical U1 snRNA. In this study, we found that placing the variants in the context of the regulatory elements of the RNU1-1 gene improves the expression of many variants to levels comparable to the canonical U1 snRNA. Application of a previously established HeLa cell-based minigene reporter assay to examine the capacity of the vU1 snRNAs to support pre-mRNA splicing revealed that even though the exogenously expressed variant snRNAs were enriched in the nucleus, only a few had a measurable effect on splicing.

High Energy Channeling and Malleable Transition States: Molecular Dynamics Simulations and Free Energy Landscapes for the Thermal Unfolding of Protein U1A and 13 Mutants

The spliceosome protein U1A is a prototype case of the RNA recognition motif (RRM) ubiquitous in biological systems. The in vitro kinetics of the chemical denaturation of U1A indicate that the unfolding of U1A is a two-state process but takes place via high energy channeling and a malleable transition state, an interesting variation of typical two-state behavior. Molecular dynamics (MD) simulations have been applied extensively to the study of two-state unfolding and folding of proteins and provide an opportunity to obtain a theoretical account of the experimental results and a molecular model for the transition state ensemble. We describe herein all-atom MD studies including explicit solvent of up to 100 ns on the thermal unfolding (UF) of U1A and 13 mutants. Multiple MD UF trajectories are carried out to ensure accuracy and reproducibility. A vector representation of the MD unfolding process in RMSD space is obtained and used to calculate a free energy landscape for U1A unfolding. A corresponding MD simulation and free energy landscape for the protein CI2, well known to follow a simple two state folding/unfolding model, is provided as a control. The results indicate that the unfolding pathway on the MD calculated free energy landscape of U1A shows a markedly extended transition state compared with that of CI2. The MD results support the interpretation of the observed chevron plots for U1A in terms of a high energy, channel-like transition state. Analysis of the MDUF structures shows that the transition state ensemble involves microstates with most of the RRM secondary structure intact but expanded by ~14% with respect to the radius of gyration. Comparison with results on a prototype system indicates that the transition state involves an ensemble of molten globule structures and extends over the region of ~1-35 ns in the trajectories. Additional MDUF simulations were carried out for 13 U1A mutants, and the calculated φ-values show close accord with observed results and serve to validate our methodology.

Interpreting the Dynamics of Binding Interactions of snRNA and U1A Using a Coarse-Grained Model

The binding interactions of small nuclear RNAs (snRNA) and the associated protein factors are critical to the function of spliceosomes in alternatively splicing primary RNA transcripts. Although molecular dynamics simulations are a powerful tool to interpret the mechanism of biological processes, the atomic-level simulations are, however, too expensive and with limited accuracy for the large-size systems, such as snRNA-protein complexes. We extend the coarse-grained Gaussian network model, which models the RNA-protein complexes as a harmonic chain of Cα, P, and O4' atoms, to investigating the impact of the snRNA-binding interaction on the dynamic stability of the human U1A protein, which is a major component of the spliceosomal U1 small nuclear ribonucleoprotein particle. The results reveal that the first and third loops and the C-terminal helix regions of the U1A domain undergo a significant loss of flexibility upon the RNA binding due to the forming of mostly electrostatic and hydrogen bond interactions with RNA 5' stem and loop. By examining the residues whose mutations significantly change the binding free energy between U1A and snRNA, the Gaussian network model-based calculations show that not only the residues at the binding sites that are traditionally considered to play a major role in U1A-RNA association but also those residues that are far away from the RNA-binding interface can participate in the long-range allosteric signal transmission; these calculations are quantitatively consistent with the data observed in the recent snRNA binding experiments. The study demonstrates a useful avenue to utilize the simplified elastic network model to investigate the dynamics characteristics of the biologically important macromolecular interactions.

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.

Role of Electrostatics in Protein-RNA Binding: The Global vs the Local Energy Landscape

U1A protein-stem loop 2 RNA association is a basic step in the assembly of the spliceosomal U1 small nuclear ribonucleoprotein. Long-range electrostatic interactions due to the positive charge of U1A are thought to provide high binding affinity for the negatively charged RNA. Short range interactions, such as hydrogen bonds and contacts between RNA bases and protein side chains, favor a specific binding site. Here, we propose that electrostatic interactions are as important as local contacts in biasing the protein-RNA energy landscape toward a specific binding site. We show by using molecular dynamics simulations that deletion of two long-range electrostatic interactions (K22Q and K50Q) leads to mutant-specific alternative RNA bound states. One of these states preserves short-range interactions with aromatic residues in the original binding site, while the other one does not. We test the computational prediction with experimental temperature-jump kinetics using a tryptophan probe in the U1A-RNA binding site. The two mutants show the distinct predicted kinetic behaviors. Thus, the stem loop 2 RNA has multiple binding sites on a rough RNA-protein binding landscape. We speculate that the rough protein-RNA binding landscape, when biased to different local minima by electrostatics, could be one way that protein-RNA interactions evolve toward new binding sites and novel function.

Molecular Dynamics Simulations for Deciphering the Structural Basis of Recognition of Pre-let-7 miRNAs by LIN28

LIN28 protein inhibits biogenesis of miRNAs belonging to the let-7 family by binding to precursor forms of miRNAs. Overexpression of LIN28 and low levels of let-7 miRNAs are associated with several forms of cancer cells. We have performed multiple explicit solvent molecular dynamics simulations ranging from 200 to 500 ns in length on different isoforms of preE-let-7 in complex with LIN28 and also in isolation to identify structural features and key specificity-determining residues (SDRs) that are important for the inhibitory role of LIN28. Our simulations suggest that a conserved structural feature of the loop regions of preE-let-7 miRNAs is more important for LIN28 recognition than sequence conservation among members of the let-7 family or the presence of the GGAG motif in the 3' region. The loop region consisting of a minimum of five nucleotides helps pre-miRNAs to acquire a conformation ideal for binding to LIN28, but pre-let-7c-2 prefers a conformation with a three-nucleotide loop. Thus, our simulations provide a theoretical rationale for the recent experimental observation of the escape of LIN28-mediated repression by pre-let-7c-2. The essential structural and sequence features highlighted in this study might aid in designing synthetic small molecule inhibitors for modulating LIN28-let-7 interaction in malignant cells. We have also identified crucial SDRs of the LIN28-preE-let-7 complex involving 13 residues of LIN28 and 10 residues of the pre-miRNA. On the basis of the conservation profile of these 13 SDRs, we have identified 10 novel proteins that are not annotated as LIN28 like but are similar in sequence, domain, or fold level to LIN28.

Synergy between NMR measurements and MD simulations of protein/RNA complexes: application to the RRMs, the most common RNA recognition motifs

RNA recognition motif (RRM) proteins represent an abundant class of proteins playing key roles in RNA biology. We present a joint atomistic molecular dynamics (MD) and experimental study of two RRM-containing proteins bound with their single-stranded target RNAs, namely the Fox-1 and SRSF1 complexes. The simulations are used in conjunction with NMR spectroscopy to interpret and expand the available structural data. We accumulate more than 50 μs of simulations and show that the MD method is robust enough to reliably describe the structural dynamics of the RRM-RNA complexes. The simulations predict unanticipated specific participation of Arg142 at the protein-RNA interface of the SRFS1 complex, which is subsequently confirmed by NMR and ITC measurements. Several segments of the protein-RNA interface may involve competition between dynamical local substates rather than firmly formed interactions, which is indirectly consistent with the primary NMR data. We demonstrate that the simulations can be used to interpret the NMR atomistic models and can provide qualified predictions. Finally, we propose a protocol for 'MD-adapted structure ensemble' as a way to integrate the simulation predictions and expand upon the deposited NMR structures. Unbiased μs-scale atomistic MD could become a technique routinely complementing the NMR measurements of protein-RNA complexes.

Exploring the mechanism how Marburg virus VP35 recognizes and binds dsRNA by molecular dynamics simulations and free energy calculations

Filoviruses often cause terrible infectious disease which has not been successfully dealt with pharmacologically. All filoviruses encode a unique protein termed VP35 which can mask doubled-stranded RNA to deactivate interferon. The interface of VP35-dsRNA would be a feasible target for structure-based antiviral agent design. To explore the essence of VP35-dsRNA interaction, molecular dynamics simulation combined with MM-GBSA calculations were performed on Marburg virus VP35-dsRNA complex and several mutational complexes. The energetic analysis indicates that nonpolar interactions provide the main driving force for the binding process. Although the intermolecular electrostatic interactions play important roles in VP35-dsRNA interaction, the whole polar interactions are unfavorable for binding which result in a low binding affinity. Compared with wild type VP35, the studied mutants F228A, R271A, and K298A have obviously reduced binding free energies with dsRNA reflecting in the reduction of polar or nonpolar interactions. The results also indicate that the loss of binding affinity for one dsRNA strand would abolish the total binding affinity. Three important residues Arg271, Arg294, and Lys298 which makes the largest contribution for binding in VP35 lose their binding affinity significantly in mutants. The uncovering of VP35-dsRNA recognition mechanism will provide some insights for development of antiviral drug.

Can We Execute Stable Microsecond-Scale Atomistic Simulations of Protein-RNA Complexes?

We report over 30 μs of unrestrained molecular dynamics simulations of six protein-RNA complexes in explicit solvent. We utilize the AMBER ff99bsc0χ(OL3) RNA force field combined with the ff99SB protein force field and its more recent ff12SB version with reparametrized side-chain dihedrals. The simulations show variable behavior, ranging from systems that are essentially stable to systems with progressive deviations from the experimental structure, which we could not stabilize anywhere close to the starting experimental structure. For some systems, microsecond-scale simulations are necessary to achieve stabilization after initial sizable structural perturbations. The results show that simulations of protein-RNA complexes are challenging and every system should be treated individually. The simulations are affected by numerous factors, including properties of the starting structures (the initially high force field potential energy, resolution limits, conformational averaging, crystal packing, etc.), force field imbalances, and real flexibility of the studied systems. These factors, and thus the simulation behavior, differ from system to system. The structural stability of simulated systems does not correlate with the size of buried interaction surface or experimentally determined binding affinities but reflects the type of protein-RNA recognition. Protein-RNA interfaces involving shape-specific recognition of RNA are more stable than those relying on sequence-specific RNA recognition. The differences between the protein force fields are considerably smaller than the uncertainties caused by sampling and starting structures. The ff12SB improves description of the tyrosine side-chain group, which eliminates some problems associated with tyrosine dynamics.

Combined mechanism of conformational selection and induced fit in U1A-RNA molecular recognition

In this study, we demonstrate that U1A-RNA molecular recognition is mediated by a combined mechanism of conformational selection and induced fit. The binding of U1A to RNA has been discussed in the context of induced fit that involves the reorientation of the α-helix in the C-terminal region (Helix-C) of U1A to permit RNA access only when U1A correctly recognizes RNA. However, according to our molecular dynamics simulations, even in the absence of RNA, Helix-C spontaneously reoriented to permit RNA access. Nonetheless, such a conformational change was still incomplete. Helix-C was often partially or even fully unfolded and in an infrequent RNA-accessible conformation, which can be detected using state-of-the-art nuclear magnetic resonance methodology. These results suggest that the formation of an energetically stabilized complex is promoted by specific interactions between U1A and RNA. In conclusion, in the recognition of RNA by U1A protein, we propose a combined mechanism that requires the reorientation of Helix-C and the subsequent contact with RNA through conformational selection, although the stabilization of the U1A-RNA complex is caused by induced fit. We further propose a modification to the conventional assumption regarding the mechanism of U1A-RNA molecular recognition.