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

Monovalent metal ion binding promotes the first transesterification reaction in the spliceosome

Cleavage and formation of phosphodiester bonds in nucleic acids is accomplished by large cellular machineries composed of both protein and RNA. Long thought to rely on a two-metal-ion mechanism for catalysis, structure comparisons revealed many contain highly spatially conserved second-shell monovalent cations, whose precise function remains elusive. A recent high-resolution structure of the spliceosome, essential for pre-mRNA splicing in eukaryotes, revealed a potassium ion in the active site. Here, we employ biased quantum mechanics/ molecular mechanics molecular dynamics to elucidate the function of this monovalent ion in splicing. We discover that the K+ ion regulates the kinetics and thermodynamics of the first splicing step by rigidifying the active site and stabilizing the substrate in the pre- and post-catalytic state via formation of key hydrogen bonds. Our work supports a direct role for the K+ ion during catalysis and provides a mechanistic hypothesis likely shared by other nucleic acid processing enzymes.

Characterization of epitranscriptome reader proteins experimentally and in silico: Current knowledge and future perspectives beyond the YTH domain

To date, over 150 chemical modifications to the four canonical RNA bases have been discovered, known collectively as the epitranscriptome. Many of these modifications have been implicated in a variety of cellular processes and disease states. Additional work has been done to identify proteins known as "readers" that selectively interact with RNAs that contain specific chemical modifications. Protein interactomes with N6-methyladenosine (m⁶A), N1-methyladenosine (m¹A), N5-methylcytosine (m⁵C), and 8-oxo-7,8-dihydroguanosine (8-oxoG) have been determined, mainly through experimental advances in proteomics techniques. However, relatively few proteins have been confirmed to bind directly to RNA containing these modifications. Furthermore, for many of these protein readers, the exact binding mechanisms as well as the exclusivity for recognition of modified RNA species remain elusive, leading to questions regarding their roles within different cellular processes. In the case of the YT-521B homology (YTH) family of proteins, both experimental and in silico techniques have been leveraged to provide valuable biophysical insights into the mechanisms of m⁶A recognition at atomic resolution. To date, the YTH family is one of the best characterized classes of readers. Here, we review current knowledge about epitranscriptome recognition of the YTH domain proteins from previously published experimental and computational studies. We additionally outline knowledge gaps for proteins beyond the well-studied human YTH domains and the current in silico techniques and resources that can enable investigation of protein interactions with modified RNA outside of the YTH-m⁶A context.

RNA-protein complexes and force field polarizability

Molecular dynamic (MD) simulations offer a way to study biomolecular interactions and their dynamics at the atomistic level. There are only a few studies of RNA-protein complexes in MD simulations, and here we wanted to study how force fields differ when simulating RNA-protein complexes: 1) argonaute 2 with bound guide RNA and a target RNA, 2) CasPhi-2 bound to CRISPR RNA and 3) Retinoic acid-inducible gene I C268F variant in complex with double-stranded RNA. We tested three non-polarizable force fields: Amber protein force fields ff14SB and ff19SB with RNA force field OL3, and the all-atom OPLS4 force field. Due to the highly charged and polar nature of RNA, we also tested the polarizable AMOEBA force field and the ff19SB and OL3 force fields with a polarizable water model O3P. Our results show that the non-polarizable force fields lead to compact and stable complexes. The polarizability in the force field or in the water model allows significantly more movement from the complex, but in some cases, this results in the disintegration of the complex structure, especially if the protein contains longer loop regions. Thus, one should be cautious when running long-scale simulations with polarizability. As a conclusion, all the tested force fields can be used to simulate RNA-protein complexes and the choice of the optimal force field depends on the studied system and research question.

Targeted systematic evolution of an RNA platform neutralizing DNMT1 function and controlling DNA methylation

DNA methylation is a fundamental epigenetic modification regulating gene expression. Aberrant DNA methylation is the most common molecular lesion in cancer cells. However, medical intervention has been limited to the use of broadly acting, small molecule-based demethylating drugs with significant side-effects and toxicities. To allow for targeted DNA demethylation, we integrated two nucleic acid-based approaches: DNMT1 interacting RNA (DiR) and RNA aptamer strategy. By combining the RNA inherent capabilities of inhibiting DNMT1 with an aptamer platform, we generated a first-in-class DNMT1-targeted approach - aptaDiR. Molecular modelling of RNA-DNMT1 complexes coupled with biochemical and cellular assays enabled the identification and characterization of aptaDiR. This RNA bio-drug is able to block DNA methylation, impair cancer cell viability and inhibit tumour growth in vivo. Collectively, we present an innovative RNA-based approach to modulate DNMT1 activity in cancer or diseases characterized by aberrant DNA methylation and suggest the first alternative strategy to overcome the limitations of currently approved non-specific hypomethylating protocols, which will greatly improve clinical intervention on DNA methylation.

Uridylation of the histone mRNA stem-loop weakens binding interactions with SLBP while maintaining interactions with 3'hExo

Histone mRNA degradation is controlled by the unique 3' stem-loop of histone mRNA and the stem-loop binding protein (SLBP). As part of this process, the 3' stem-loop is trimmed by the histone-specific 3' exonuclease (3'hExo) and uridylated by the terminal uridylyl transferase 7 (TUT7), creating partially degraded intermediates with short uridylations. The role of these uridylations in degradation is not fully understood. Our work examines changes in the stability of the ternary complex created by trimming and uridylation of the stem-loop to better understand the role of this process in the histone mRNA life cycle. In this study, we used fluorescence polarization and electrophoretic mobility shift assays to demonstrate that both SLBP and 3'hExo can bind to uridylated and partially degraded stem-loop intermediates, although with lower affinity. We further characterized this complex by performing 1-µs molecular dynamics simulations using the AMBER force field and Nanoscale Molecular Dynamics (NAMD). These simulations show that while uridylation helps maintain the overall shape of the stem-loop, the combination of uridylation and dephosphorylation of the TPNK motif in SLBP disrupts key RNA-protein interactions. They also demonstrate that uridylation allows 3'hExo to maintain contact with the stem-loop after partial degradation and plays a role in disrupting key base pairs in partially degraded histone mRNA intermediates. Together, these experiments and simulations suggest that trimming by 3'hExo, uridylation, and SLBP dephosphorylation weakens both RNA-protein interactions and the stem-loop itself. Our results further elucidate the role of uridylation and SLBP dephosphorylation in the early stages of histone mRNA degradation.

Spontaneous binding of single-stranded RNAs to RRM proteins visualized by unbiased atomistic simulations with a rescaled RNA force field

Recognition of single-stranded RNA (ssRNA) by RNA recognition motif (RRM) domains is an important class of protein-RNA interactions. Many such complexes were characterized using nuclear magnetic resonance (NMR) and/or X-ray crystallography techniques, revealing ensemble-averaged pictures of the bound states. However, it is becoming widely accepted that better understanding of protein-RNA interactions would be obtained from ensemble descriptions. Indeed, earlier molecular dynamics simulations of bound states indicated visible dynamics at the RNA-RRM interfaces. Here, we report the first atomistic simulation study of spontaneous binding of short RNA sequences to RRM domains of HuR and SRSF1 proteins. Using a millisecond-scale aggregate ensemble of unbiased simulations, we were able to observe a few dozen binding events. HuR RRM3 utilizes a pre-binding state to navigate the RNA sequence to its partially disordered bound state and then to dynamically scan its different binding registers. SRSF1 RRM2 binding is more straightforward but still multiple-pathway. The present study necessitated development of a goal-specific force field modification, scaling down the intramolecular van der Waals interactions of the RNA which also improves description of the RNA-RRM bound state. Our study opens up a new avenue for large-scale atomistic investigations of binding landscapes of protein-RNA complexes, and future perspectives of such research are discussed.

Conformational Heterogeneity of RNA Stem-Loop Hairpins Bound to FUS-RNA Recognition Motif with Disordered RGG Tail Revealed by Unbiased Molecular Dynamics Simulations

RNA-protein complexes use diverse binding strategies, ranging from structurally well-defined interfaces to completely disordered regions. Experimental characterization of flexible segments is challenging and can be aided by atomistic molecular dynamics (MD) simulations. Here, we used an extended set of microsecond-scale MD trajectories (400 μs in total) to study two FUS-RNA constructs previously characterized by nuclear magnetic resonance (NMR) spectroscopy. The FUS protein contains a well-structured RNA recognition motif domain followed by a presumably disordered RGG tail that binds RNA stem-loop hairpins. Our simulations not only provide several suggestions complementing the experiments but also reveal major methodological difficulties in studies of such complex RNA-protein interfaces. Despite efforts to stabilize the binding via system-specific force-field adjustments, we have observed progressive distortions of the RNA-protein interface inconsistent with experimental data. We propose that the dynamics is so rich that its converged description is not achievable even upon stabilizing the system. Still, after careful analysis of the trajectories, we have made several suggestions regarding the binding. We identify substates in the RNA loops, which can explain the NMR data. The RGG tail localized in the minor groove remains disordered, sampling countless transient interactions with the RNA. There are long-range couplings among the different elements contributing to the recognition, which can lead to allosteric communication throughout the system. Overall, the RNA-FUS systems form dynamical ensembles that cannot be fully represented by single static structures. Thus, albeit imperfect, MD simulations represent a viable tool to investigate dynamic RNA-protein complexes.

Molecular Dynamics Simulations of Protein RNA Complexes by Using an Advanced Electrostatic Model

Protein-RNA interactions are integral to the biological functions of RNA. It is well recognized that molecular dynamics (MD) simulations of protein-RNA complexes are more challenging than those of each component. The difficulty arises from the strong electrostatic interactions and the delicate balance between various types of physical forces at the interface. Previously, MD simulations of protein-RNA complexes have predominantly employed fixed-charge force fields. Although force field modifications have been developed to address problems identified in the simulations, some protein-RNA structures are still hard to reproduce by simulations. Here, we present MD simulations of two representative protein-RNA complexes using the AMOEBA polarizable force field. The van der Waals parameters were refined to reproduce accurate quantum-mechanical data of base-base and base-amino acid interactions. It was found that the refined parameters produced a more stable hydrogen-bond network in the interface. One of the complexes remained stable during the short simulations, whereas it could quickly break down in previous simulations using fixed-charge force fields. There was reversible breaking and formation of hydrogen bonds that are observed in the crystal structure, which may indicate the difference in solution and crystal structures. While further improvement and validation of the force fields are still needed, this work demonstrates that polarizable force fields are promising for the study of protein-RNA complexes.

QM/MM Well-Tempered Metadynamics Study of the Mechanism of XBP1 mRNA Cleavage by Inositol Requiring Enzyme 1α RNase

A range of in silico methodologies were herein employed to study the unconventional XBP1 mRNA cleavage mechanism performed by the unfolded protein response (UPR) mediator Inositol Requiring Enzyme 1α (IRE1). Using Protein-RNA molecular docking along with a series of extensive restrained/unrestrained atomistic molecular dynamics (MD) simulations, the dynamical behavior of the system was evaluated and a reliable model of the IRE1/XBP1 mRNA complex was constructed. From a series of well-converged quantum mechanics molecular mechanics well-tempered metadynamics (QM/MM WT-MetaD) simulations using the Grimme dispersion interaction corrected semiempirical parametrization method 6 level of theory (PM6-D3) and the AMBER14SB-OL3 force field, the free energy profile of the cleavage mechanism was determined, along with intermediates and transition state structures. The results show two distinct reaction paths based on general acid-general base type mechanisms, with different activation energies that perfectly match observations from experimental mutagenesis data. The study brings unique atomistic insights into the cleavage mechanism of XBP1 mRNA by IRE1 and clarifies the roles of the catalytic residues H910 and Y892. Increased understanding of the details in UPR signaling can assist in the development of new therapeutic agents for its modulation.

Development of Force Field Parameters for the Simulation of Single- and Double-Stranded DNA Molecules and DNA-Protein Complexes

Although molecular dynamics (MD) simulations have been used extensively to study the structural dynamics of proteins, the role of MD simulation in studies of nucleic acid based systems has been more limited. One contributing factor to this disparity is the historically lower level of accuracy of the physical models used in such simulations to describe interactions involving nucleic acids. By modifying nonbonded and torsion parameters of a force field from the Amber family of models, we recently developed force field parameters for RNA that achieve a level of accuracy comparable to that of state-of-the-art protein force fields. Here we report force field parameters for DNA, which we developed by transferring nonbonded parameters from our recently reported RNA force field and making subsequent adjustments to torsion parameters. We have also modified the backbone charges in both the RNA and DNA parameter sets to make the treatment of electrostatics compatible with our recently developed variant of the Amber protein and ion force field. We name the force field resulting from the union of these three parameter sets (the new DNA parameters, the revised RNA parameters, and the existing protein and ion parameters) DES-Amber. Extensive testing of DES-Amber indicates that it can describe the thermal stability and conformational flexibility of single- and double-stranded DNA systems with a level of accuracy comparable to or, especially for disordered systems, exceeding that of state-of-the-art nucleic acid force fields. Finally, we show that, in certain favorable cases, DES-Amber can be used for long-timescale simulations of protein–nucleic acid complexes.

Mechanism of RNA recognition by a Musashi RNA-binding protein

The Musashi RNA-binding proteins (RBPs) regulate translation of target mRNAs and maintenance of cell stemness and tumorigenesis. Musashi-1 (MSI1), long considered as an intestinal and neural stem cell marker, has been more recently found to be over expressed in many cancers. It has served as an important drug target for treating acute myeloid leukemia and solid tumors such as ovarian, colorectal and bladder cancer. One of the reported binding targets of MSI1 is Numb, a negative regulator of the Notch signaling. However, the dynamic mechanism of Numb RNA binding to MSI1 remains unknown, largely hindering effective drug design targeting this critical interaction. Here, we have performed extensive all-atom microsecond-timescale simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method, which successfully captured multiple times of spontaneous and highly accurate binding of the Numb RNA from bulk solvent to the MSI1 protein target site. GaMD simulations revealed that Numb RNA binding to MSI1 involved largely induced fit in both the RNA and protein. The simulations also identified important low-energy intermediate conformational states during RNA binding, in which Numb interacted mainly with the β2-β3 loop and C terminus of MSI1. The mechanistic understanding of RNA binding obtained from our GaMD simulations is expected to facilitate rational structure-based drug design targeting MSI1 and other RBPs.

Molecular Dynamics Simulations of the Aptamer Domain of Guanidinium Ion Binding Riboswitch ykkC-III: Structural Insights into the Discrimination of Cognate and Alternate Ligands

Guanidinium ion is a toxic cellular metabolite. The ykkC-III riboswitch, an mRNA stretch, regulates the gene expression by undergoing a conformational change in response to the binding of a free guanidinium ion and thereby plays a potentially important role in alleviating guanidinium toxicity in cells. An experimental crystal structure of the guanidinium-bound aptamer domain of the riboswitch from Thermobifida Fusca revealed the overall RNA architecture and mapped the specific noncovalent interactions that stabilize the ligand within the binding pocket aptamer. However, details of how the aptamer domain discriminates the cognate ligand from its closest structurally analogous physiological metabolites (arginine and urea), and how the binding of cognate ligand arrays information from the aptamer domain to the expression platform for regulating the gene expression, are not well understood. To fill this void, we perform a cumulative of 2 μs all-atom explicit-solvent molecular dynamics (MD) simulations on the full aptamer domain, augmented with quantum-chemical calculations on the ligand-binding pocket, to compare the structural and dynamical details of the guanidinium-bound state with the arginine or urea bound states, as well as the unbound (open) state. Analysis of the ligand-binding pocket reveals that due to unfavorable interactions with the binding-pocket residues, urea cannot bind the aptamer domain and thereby cannot alter the gene expression. Although interaction of the guanidyl moiety of arginine within the binding pocket is either comparable or stronger than the guanidinium ion, additional non-native hydrogen-bonding networks, as well as differences in the dynamical details of the arginine-bound state, explain why arginine cannot transmit the information from the aptamer domain to the expression platform. Based on our simulations, we propose a mechanism of how the aptamer domain communicates with the expression platform. Overall, our work provides interesting insights into the ligand recognition by a specific class of riboswitches and may hopefully inspire future studies to further understand the gene regulation by riboswitches.

De novo ssRNA Aptamers against the SARS-CoV-2 Main Protease: In Silico Design and Molecular Dynamics Simulation

Herein, we have generated ssRNA aptamers to inhibit SARS-CoV-2 M^pro, a protease necessary for the SARS-CoV-2 coronavirus replication. Because there is no aptamer 3D structure currently available in the databanks for this protein, first, we modeled an ssRNA aptamer using an entropic fragment-based strategy. We refined the initial sequence and 3D structure by using two sequential approaches, consisting of an elitist genetic algorithm and an RNA inverse process. We identified three specific aptamers against SARS-CoV-2 M^pro, called MApta^pro, MApta^pro-IR1, and MApta^pro-IR2, with similar 3D conformations and that fall in the dimerization region of the SARS-CoV-2 M^pro necessary for the enzymatic activity. Through the molecular dynamic simulation and binding free energy calculation, the interaction between the MApta^pro-IR1 aptamer and the SARS-CoV-2 M^pro enzyme resulted in the strongest and the highest stable complex; therefore, the ssRNA MApta^pro-IR1 aptamer was selected as the best potential candidate for the inhibition of SARS-CoV-2 M^pro and a perspective therapeutic drug for the COVID-19 disease.

W-RESP: Well-Restrained Electrostatic Potential-Derived Charges. Revisiting the Charge Derivation Model

Representation of electrostatic interactions by a Coulombic pairwise potential between atom-centered partial charges is a fundamental and crucial part of empirical force fields used in classical molecular dynamics simulations. The broad success of the AMBER force-field family originates mainly from the restrained electrostatic potential (RESP) charge model, which derives partial charges to reproduce the electrostatic field around the molecules. However, the description of the electrostatic potential around molecules by standard RESP may be biased for some types of molecules. In this study, we modified the RESP charge derivation model to improve its description of the electrostatic potential around molecules and thus electrostatic interactions in the force field. In particular, we reoptimized the atomic radii for definition of the grid points around the molecule, redesigned the restraining scheme, and included extra point (EP) charges. The RESP fitting was significantly improved for aromatic heterocyclic molecules. Thus, the suggested W-RESP(-EP) charge derivation model shows some potential for improving the performance of the nucleic acid force fields, for which the poor description of nonbonded interactions, such as the underestimated stability of base pairing, is well-established. We also report some preliminary simulation tests (around 1 ms of simulation data) on A-RNA duplexes, tetranucleotides, and tetraloops. The simulations reveal no adverse effects, while the description of base-pairing interactions might be improved. The new charges can thus be used in future attempts to improve the nucleic acid simulation force fields, in combination with reparametrization of the other terms.

Biomolecular Modeling and Simulation: A Prospering Multidisciplinary Field

We reassess progress in the field of biomolecular modeling and simulation, following up on our perspective published in 2011. By reviewing metrics for the field's productivity and providing examples of success, we underscore the productive phase of the field, whose short-term expectations were overestimated and long-term effects underestimated. Such successes include prediction of structures and mechanisms; generation of new insights into biomolecular activity; and thriving collaborations between modeling and experimentation, including experiments driven by modeling. We also discuss the impact of field exercises and web games on the field's progress. Overall, we note tremendous success by the biomolecular modeling community in utilization of computer power; improvement in force fields; and development and application of new algorithms, notably machine learning and artificial intelligence. The combined advances are enhancing the accuracy andscope of modeling and simulation, establishing an exemplary discipline where experiment and theory or simulations are full partners.

MD simulations reveal the basis for dynamic assembly of Hfq-RNA complexes

The conserved protein Hfq is a key factor in the RNA-mediated control of gene expression in most known bacteria. The transient intermediates Hfq forms with RNA support intricate and robust regulatory networks. In Pseudomonas, Hfq recognizes repeats of adenine–purine–any nucleotide (ARN) in target mRNAs via its distal binding side, and together with the catabolite repression control (Crc) protein, assembles into a translation–repression complex. Earlier experiments yielded static, ensemble-averaged structures of the complex, but details of its interface dynamics and assembly pathway remained elusive. Using explicit solvent atomistic molecular dynamics simulations, we modeled the extensive dynamics of the Hfq–RNA interface and found implications for the assembly of the complex. We predict that syn/anti flips of the adenine nucleotides in each ARN repeat contribute to a dynamic recognition mechanism between the Hfq distal side and mRNA targets. We identify a previously unknown binding pocket that can accept any nucleotide and propose that it may serve as a ‘status quo’ staging point, providing nonspecific binding affinity, until Crc engages the Hfq–RNA binary complex. The dynamical components of the Hfq–RNA recognition can speed up screening of the pool of the surrounding RNAs, participate in rapid accommodation of the RNA on the protein surface, and facilitate competition among different RNAs. The register of Crc in the ternary assembly could be defined by the recognition of a guanine-specific base–phosphate interaction between the first and last ARN repeats of the bound RNA. This dynamic substrate recognition provides structural rationale for the stepwise assembly of multicomponent ribonucleoprotein complexes nucleated by Hfq–RNA binding.

Residues flanking the ARKme3T/S motif allow binding of diverse targets to the HP1 chromodomain: Insights from molecular dynamics simulations

BACKGROUND

The chromodomain (CD) of HP1 proteins is an established H3K9^me3 reader that also binds H1, EHMT2 and H3K23 lysine-methylated targets. Structural experiments have provided atomistic pictures of its recognition of the conserved ARK^me3S/T motif, but structural dynamics' contribution to the recognition may have been masked by ensemble averaging.

METHODS

We acquired ~350 μs of explicit solvent molecular dynamics (MD) simulations of the CD domain interacting with several peptides using the latest AMBER force fields.

RESULTS

The simulations reproduced the experimentally observed static binding patterns well but also revealed visible structural dynamics at the interfaces. While the buried K₀^me3 and A_-2 target residues are tightly bound, several flanking sidechains sample diverse sites on the CD surface. Different amino acid positions of the targets can substitute for each other by forming mutually replaceable interactions with CD, thereby explaining the lack of strict requirement for cationic H3 target residues at the -3 position. The Q_-4 residue of H3 targets further stabilizes the binding. The recognition pattern of the H3K23 ATK^me3A motif, for which no structure is available, is predicted.

CONCLUSIONS

The CD reads a longer target segment than previously thought, ranging from positions -7 to +3. The CD anionic clamp can be neutralized not only by the -3 and -1 residues, but also by -7, -6, -5 and +3 residues.

GENERAL SIGNIFICANCE

Structural dynamics, not immediately apparent from the structural data, contribute to molecular recognition between the HP1 CD domain and its targets. Mutual replaceability of target residues increases target sequence flexibility.

Effect of 2'-5'/3'-5' phosphodiester linkage heterogeneity on RNA interference

We report on the synthesis of siRNAs containing both 2′-5′- and 3′-5′-internucleotide linkages and their effects on siRNA structure, function, and interaction with RNAi proteins. Screening of these siRNAs against their corresponding mRNA targets showed that 2′-5′ linkages were well tolerated in the sense strand, but only at a few positions in the antisense strand. Extensive modification of the antisense strand minimally affected 5′-phosphorylation of the siRNA by kinases, however, it negatively affected siRNA loading into human AGO2. Modelling and molecular dynamics simulations were fully consistent with these findings. Furthermore, our studies indicated that the presence of a single 5′p-rN₁-(2′-5′)-N₂ unit in the antisense strand does not alter the ‘clover leaf’ bend and sugar puckers that are critical for anchoring the 5′-phosphate to Ago 2 MID domain. Importantly, 2′-5′-linkages had the added benefit of abrogating immune-stimulatory activity of siRNAs. Together, these results demonstrate that 2′-5′/3′-5′-modified siRNAs, when properly designed, can offer an efficient new class of siRNAs with diminished immune-stimulatory responses.

Toward empirical force fields that match experimental observables

Biomolecular force fields have been traditionally derived based on a mixture of reference quantum chemistry data and experimental information obtained on small fragments. However, the possibility to run extensive molecular dynamics simulations on larger systems achieving ergodic sampling is paving the way to directly using such simulations along with solution experiments obtained on macromolecular systems. Recently, a number of methods have been introduced to automatize this approach. Here, we review these methods, highlight their relationship with machine learning methods, and discuss the open challenges in the field.

Flexible Binding of m6A Reader Protein YTHDC1 to Its Preferred RNA Motif

N⁶-Methyladenosine (m⁶A) is the most prevalent chemical modification in human mRNAs. Its recognition by reader proteins enables many cellular functions, including splicing and translation of mRNAs. However, the binding mechanisms of m⁶A-containing RNAs to their readers are still elusive due to the unclear roles of m⁶A-flanking ribonucleotides. Here, we use a model system, YTHDC1 with its RNA motif 5'-G_-2G_-1(m⁶A)C₊₁U₊₂-3', to investigate the binding mechanisms by atomistic simulations, X-ray crystallography, and isothermal titration calorimetry. The experimental data and simulation results show that m⁶A is captured by an aromatic cage of YTHDC1 and the 3' terminus nucleotides are stabilized by cation-π-π interactions, while the 5' terminus remains flexible. Notably, simulations of unbound RNA motifs reveal that the methyl group of m⁶A and the 5' terminus shift the conformational preferences of the oligoribonucleotide to the bound-like conformation, thereby facilitating the association process. The binding mechanisms may help in the discovery of chemical probes against m⁶A reader proteins.

Disclosing the Impact of Carcinogenic SF3b Mutations on Pre-mRNA Recognition Via All-Atom Simulations

The spliceosome accurately promotes precursor messenger-RNA splicing by recognizing specific noncoding intronic tracts including the branch point sequence (BPS) and the 3'-splice-site (3'SS). Mutations of Hsh155 (yeast)/SF3B1 (human), which is a protein of the SF3b factor involved in BPS recognition and induces altered BPS binding and 3'SS selection, lead to mis-spliced mRNA transcripts. Although these mutations recur in hematologic malignancies, the mechanism by which they change gene expression remains unclear. In this study, multi-microsecond-long molecular-dynamics simulations of eighth distinct ∼700,000 atom models of the spliceosome Bact complex, and gene sequencing of SF3B1, disclose that these carcinogenic isoforms destabilize intron binding and/or affect the functional dynamics of Hsh155/SF3B1 only when binding non-consensus BPSs, as opposed to the non-pathogenic variants newly annotated here. This pinpoints a cross-talk between the distal Hsh155 mutation and BPS recognition sites. Our outcomes unprecedentedly contribute to elucidating the principles of pre-mRNA recognition, which provides critical insights on the mechanism underlying constitutive/alternative/aberrant splicing.

RuvC uses dynamic probing of the Holliday junction to achieve sequence specificity and efficient resolution

Holliday junctions (HJs) are four-way DNA structures that occur in DNA repair by homologous recombination. Specialized nucleases, termed resolvases, remove (i.e., resolve) HJs. The bacterial protein RuvC is a canonical resolvase that introduces two symmetric cuts into the HJ. For complete resolution of the HJ, the two cuts need to be tightly coordinated. They are also specific for cognate DNA sequences. Using a combination of structural biology, biochemistry, and a computational approach, here we show that correct positioning of the substrate for cleavage requires conformational changes within the bound DNA. These changes involve rare high-energy states with protein-assisted base flipping that are readily accessible for the cognate DNA sequence but not for non-cognate sequences. These conformational changes and the relief of protein-induced structural tension of the DNA facilitate coordination between the two cuts. The unique DNA cleavage mechanism of RuvC demonstrates the importance of high-energy conformational states in nucleic acid readouts.

Understanding the mechanistic basis of non-coding RNA through molecular dynamics simulations

Noncoding RNA (ncRNA) has a key role in regulating gene expression, mediating fundamental processes and diseases via a variety of yet unknown mechanisms. Here, we review recent applications of conventional and enhanced Molecular Dynamics (MD) simulations methods to address the mechanistic function of large biomolecular systems that are tightly involved in the ncRNA function and that are of key importance in life sciences. This compendium focuses of three biomolecular systems, namely the CRISPR-Cas9 genome editing machinery, group II intron ribozyme and the ribonucleoprotein complex of the spliceosome, which edit and process ncRNA. We show how the application of a novel accelerated MD simulations method has been key in disclosing the conformational transitions underlying RNA binding in the CRISPR-Cas9 complex, suggesting a mechanism for RNA recruitment and clarifying the conformational changes required for attaining genome editing. As well, we discuss the use of mixed quantum-classical MD simulations in deciphering the catalytic mechanism of RNA splicing as operated by group II intron ribozyme, one of the largest ncRNA structures crystallized so far. Finally, we debate the future challenges and opportunities in the field, discussing the recent application of MD simulations for unraveling the functional biophysics of the spliceosome, a multi-mega Dalton complex of proteins and small nuclear RNAs that performs RNA splicing in humans. This showcase of applications highlights the current talent of MD simulations to dissect atomic-level details of complex biomolecular systems instrumental for the design of finely engineered genome editing machines. As well, this review aims at inspiring future investigations of several other ncRNA regulatory systems, such as micro and small interfering RNAs, which achieve their function and specificity using RNA-based recognition and targeting strategies.

Determinants of Oligonucleotide Selectivity of APOBEC3B

APOBEC3B (A3B) is a prominent source of mutation in many cancers. To date, it has been difficult to capture the native protein-DNA interactions that confer A3B's substrate specificity by crystallography due to the highly dynamic nature of wild-type A3B active site. We use computational tools to restore a recent crystal structure of a DNA-bound A3B C-terminal domain mutant construct to its wild type sequence, and run molecular dynamics simulations to study its substrate recognition mechanisms. Analysis of these simulations reveal dynamics of the native A3Bctd-oligonucleotide interactions, including the experimentally inaccessible loop 1-oligonucleotide interactions. A second series of simulations in which the target cytosine nucleotide was computationally mutated from a deoxyribose to a ribose show a change in sugar ring pucker, leading to a rearrangement of the binding site and revealing a potential intermediate in the binding pathway. Finally, apo simulations of A3B, starting from the DNA-bound open state, experience a rapid and consistent closure of the binding site, reaching conformations incompatible with substrate binding. This study reveals a more realistic and dynamic view of the wild type A3B binding site and provides novel insights for structure-guided design efforts for A3B.

Improving the Performance of the Amber RNA Force Field by Tuning the Hydrogen-Bonding Interactions

Molecular dynamics (MD) simulations became a leading tool for investigation of structural dynamics of nucleic acids. Despite recent efforts to improve the empirical potentials (force fields, ffs), RNA ffs have persisting deficiencies, which hamper their utilization in quantitatively accurate simulations. Previous studies have shown that at least two salient problems contribute to difficulties in the description of free-energy landscapes of small RNA motifs: (i) excessive stabilization of the unfolded single-stranded RNA ensemble by intramolecular base-phosphate and sugar-phosphate interactions and (ii) destabilization of the native folded state by underestimation of stability of base pairing. Here, we introduce a general ff term (gHBfix) that can selectively fine-tune nonbonding interaction terms in RNA ffs, in particular, the H bonds. The gHBfix potential affects the pairwise interactions between all possible pairs of the specific atom types, while all other interactions remain intact; i.e., it is not a structure-based model. In order to probe the ability of the gHBfix potential to refine the ff nonbonded terms, we performed an extensive set of folding simulations of RNA tetranucleotides and tetraloops. On the basis of these data, we propose particular gHBfix parameters to modify the AMBER RNA ff. The suggested parametrization significantly improves the agreement between experimental data and the simulation conformational ensembles, although our current ff version still remains far from being flawless. While attempts to tune the RNA ffs by conventional reparametrizations of dihedral potentials or nonbonded terms can lead to major undesired side effects, as we demonstrate for some recently published ffs, gHBfix has a clear promising potential to improve the ff performance while avoiding introduction of major new imbalances.

Long Time-Scale Atomistic Simulations of the Structure and Dynamics of Transcription Factor-DNA Recognition

Recent years have witnessed an explosion of interest in computational studies of DNA binding proteins, including both coarse-grained and atomistic simulations of transcription factor-DNA recognition, to understand how these transcription factors recognize their binding sites on the DNA with such exquisite specificity. The present study performs microsecond time scale all-atom simulations of the dimeric form of the lactose repressor (LacI), both in the absence of any DNA and in the presence of both specific and nonspecific complexes, considering three different DNA sequences. We examine, specifically, the conformational differences between specific and nonspecific protein-DNA interactions, as well as the behavior of the helix-turn-helix motif of LacI when interacting with the DNA. Our simulations suggest that stable LacI binding occurs primarily to bent A-form DNA, with a loss of LacI conformational entropy and optimization of correlated conformational equilibria across the protein. In addition, binding to the specific operator sequence involves a slightly larger number of stabilizing DNA-protein hydrogen bonds (in comparison to nonspecific complexes), which may account for the experimentally observed specificity for this operator. In doing so, our simulations provide a detailed atomistic description of potential structural drivers for LacI selectivity.

Can All-Atom Molecular Dynamics Simulations Quantitatively Describe Homeodomain-DNA Binding Equilibria?

We systematically investigate the applicability of a molecular dynamics-based setup for the calculations of standard binding free energies of biologically relevant protein-DNA complexes. The free energies are extracted from a potential of mean force calculated using umbrella sampling simulations. Two protein-DNA systems derived from a homeodomain transcription factor complex are studied in order to investigate the binding of both disordered and globular proteins. Free energies and trajectories obtained using two modern molecular mechanical force fields are compared to each other and to experimental data. The temperature dependence of the calculated standard binding free energies is investigated by performing all simulations over a range of temperatures. We show that the values of standard binding free energies obtained from these simulations are overestimated compared to experimental results. Significant differences are observed between the two protein-DNA systems and between the two force fields, which are explained by different propensities to form inter- and intramolecular contacts. The number of protein-DNA contacts increases with increasing temperature, in agreement with the experimentally known temperature dependence of enthalpies of binding. However, conclusions about the temperature dependence of the standard binding free energies cannot be made with confidence, as the differences among the values are on the order of statistical uncertainty.

Mechanism of protein-RNA recognition: analysis based on the statistical mechanics of hydration

We investigate the RBD1-r(GUAGU) binding as a case study using all-atom models for the biomolecules, molecular models for water, and the currently most reliable statistical-mechanical method. RBD1 is one of the RNA-binding domains of mammalian Musashi1 (Msi1), and r(GUAGU) contains the minimum recognition sequence for Msi1, r(GUAG). We show that the binding is driven by a large gain of configurational entropy of water in the entire system. It is larger than the sum of conformational-entropy losses for RBD1 and r(GUAGU). The decrease in RBD1-r(GUAGU) interaction energy upon binding is largely cancelled out by the increase in the sum of RBD1-water, r(GUAGU)-water, and water-water interaction energies. We refer to this increase as "energetic dehydration". The decrease is larger than the increase for the van der Waals component, whereas the opposite is true for the electrostatic component. We give a novel reason for the empirically known fact that protein residues possessing side chains with positive charges and with flat moieties frequently appear within protein-RNA binding interfaces. A physical picture of the general protein-RNA binding mechanism is then presented. To achieve a sufficiently large water-entropy gain, shape complementarity at the atomic level needs to be constructed by utilizing the stacking and sandwiching of flat moieties (aromatic rings of the protein and nucleobases of RNA) as fundamental motifs. To compensate for electrostatic energetic dehydration, charge complementarity becomes crucial within the binding interface. We argue the reason why the RNA recognition motif (RRM) is the most ubiquitous RNA binding domain.

Combining NMR Spectroscopy and Molecular Dynamic Simulations to Solve and Analyze the Structure of Protein-RNA Complexes

Understanding the RNA binding specificity of protein is of primary interest to decipher their function in the cell. Here, we review the methodology used to solve the structures of protein-RNA complexes using solution-state NMR spectroscopy: from sample preparation to structure calculation procedures. We also describe how molecular dynamics simulations can help providing additional information on the role of key amino acid side chains and of water molecules in protein-RNA recognition.

Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study

The RNA recognition motif (RRM) is the most common RNA binding domain across eukaryotic proteins. It is therefore of great value to engineer its specificity to target RNAs of arbitrary sequence. This was recently achieved for the RRM in Rbfox protein, where four mutations R118D, E147R, N151S, and E152T were designed to target the precursor to the oncogenic miRNA 21. Here, we used a variety of molecular dynamics-based approaches to predict specific interactions at the binding interface. Overall, we have run approximately 50 microseconds of enhanced sampling and plain molecular dynamics simulations on the engineered complex as well as on the wild-type Rbfox·pre-miRNA 20b from which the mutated systems were designed. Comparison with the available NMR data on the wild type molecules (protein, RNA, and their complex) served to establish the accuracy of the calculations.

Free energy calculations suggest that further improvements in affinity and selectivity are achieved by the S151T replacement.

RNA is an outstanding target for oncological intervention. Engineering the most common RNA binding motif in human proteins (called RRM) so as to bind to a specific RNA has an enormous pharmacological potential. Yet, it is highly non trivial to design RRM-bearing protein variants with RNA selectivity and affinity sufficiently high for clinical applications. Here we present an extensive molecular simulation study which shed light on the exquisite molecular recognition of the empirically-engineered complex between the RRM-bearing protein Rbfox and its RNA target pre-miR21. The simulations allow predicting a variant, the S151T, which may lead to further enhancement of selectivity and affinity for pre-miR21.

Chemically Accurate Relative Folding Stability of RNA Hairpins from Molecular Simulations

To benchmark RNA force fields, we compared the folding stabilities of three 12-nucleotide hairpin stem loops estimated by simulation to stabilities determined by experiment. We used umbrella sampling and a reaction coordinate of end-to-end (5' to 3' hydroxyl oxygen) distance to estimate the free energy change of the transition from the native conformation to a fully extended conformation with no hydrogen bonds between non-neighboring bases. Each simulation was performed four times using the AMBER FF99+bsc0+χ_OL3 force field, and each window, spaced at 1 Å intervals, was sampled for 1 μs, for a total of 552 μs of simulation. We compared differences in the simulated free energy changes to analogous differences in free energies from optical melting experiments using thermodynamic cycles where the free energy change between stretched and random coil sequences is assumed to be sequence-independent. The differences between experimental and simulated ΔΔ G° are, on average, 0.98 ± 0.66 kcal/mol, which is chemically accurate and suggests that analogous simulations could be used predictively. We also report a novel method to identify where replica free energies diverge along a reaction coordinate, thus indicating where additional sampling would most improve convergence. We conclude by discussing methods to more economically perform these simulations.

QM/MM Calculations on Protein-RNA Complexes: Understanding Limitations of Classical MD Simulations and Search for Reliable Cost-Effective QM Methods

Although atomistic explicit-solvent Molecular Dynamics (MD) is a popular tool to study protein-RNA recognition, satisfactory MD description of protein-RNA complexes is not always achieved. Unfortunately, it is often difficult to separate MD simulation instabilities primarily caused by the simple point-charge molecular mechanics (MM) force fields from problems related to the notorious uncertainties in the starting structures. Herein, we report a series of large-scale QM/MM calculations on the U1A protein-RNA complex. This experimentally well-characterized system has an intricate protein-RNA interface, which is very unstable in MD simulations. The QM/MM calculations identify several H-bonds poorly described by the MM method and thus indicate the sources of instabilities of the U1A interface in MD simulations. The results suggest that advanced QM/MM computations could be used to indirectly rationalize problems seen in MM-based MD simulations of protein-RNA complexes. As the most accurate QM method, we employ the computationally demanding meta-GGA density functional TPSS-D3(BJ)/def2-TZVP level of theory. Because considerably faster methods would be needed to extend sampling and to study even larger protein-RNA interfaces, a set of low-cost QM/MM methods is compared to the TPSS-D3(BJ)/def2-TZVP data. The PBEh-3c and B97-3c density functional composite methods appear to be suitable for protein-RNA interfaces. In contrast, HF-3c and the tight-binding Hamiltonians DFTB3-D3 and GFN-xTB perform unsatisfactorily and do not provide any advantage over the MM description. These conclusions are supported also by similar analysis of a simple HutP protein-RNA interface, which is well-described by MD with the exception of just one H-bond. Some other methodological aspects of QM/MM calculations on protein-RNA interfaces are discussed.

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.

Aromatic side-chain conformational switch on the surface of the RNA Recognition Motif enables RNA discrimination

The cyclooxygenase-2 is a pro-inflammatory and cancer marker, whose mRNA stability and translation is regulated by the CUG-binding protein 2 interacting with AU-rich sequences in the 3' untranslated region. Here, we present the solution NMR structure of CUG-binding protein 2 RRM3 in complex with 5'-UUUAA-3' originating from the COX-2 3'-UTR. We show that RRM3 uses the same binding surface and protein moieties to interact with AU- and UG-rich RNA motifs, binding with low and high affinity, respectively. Using NMR spectroscopy, isothermal titration calorimetry and molecular dynamics simulations, we demonstrate that distinct sub-states characterized by different aromatic side-chain conformations at the RNA-binding surface allow for high- or low-affinity binding with functional implications. This study highlights a mechanism for RNA discrimination possibly common to multiple RRMs as several prominent members display a similar rearrangement of aromatic residues upon binding their targets.The RNA Recognition Motif (RRM) is the most ubiquitous RNA binding domain. Here the authors combined NMR and molecular dynamics simulations and show that the RRM RNA binding surface exists in different states and that a conformational switch of aromatic side-chains fine-tunes sequence specific binding affinities.

Coordination between the polymerase and RNase H activity of HIV-1 reverse transcriptase

Replication of human immunodeficiency virus 1 (HIV-1) involves conversion of its single-stranded RNA genome to double-stranded DNA, which is integrated into the genome of the host. This conversion is catalyzed by reverse transcriptase (RT), which possesses DNA polymerase and RNase H domains. The available crystal structures suggest that at any given time the RNA/DNA substrate interacts with only one active site of the two domains of HIV-1 RT. Unknown is whether a simultaneous interaction of the substrate with polymerase and RNase H active sites is possible. Therefore, the mechanism of the coordination of the two activities is not fully understood. We performed molecular dynamics simulations to obtain a conformation of the complex in which the unwound RNA/DNA substrate simultaneously interacts with the polymerase and RNase H active sites. When the RNA/DNA hybrid was immobilized at the polymerase active site, RNase H cleavage occurred, experimentally verifying that the substrate can simultaneously interact with both active sites. These findings demonstrate the existence of a transient conformation of the HIV-1 RT substrate complex, which is important for modulating and coordinating the enzymatic activities of HIV-1 RT.

Structural study of the Fox-1 RRM protein hydration reveals a role for key water molecules in RRM-RNA recognition

The Fox-1 RNA recognition motif (RRM) domain is an important member of the RRM protein family. We report a 1.8 Å X-ray structure of the free Fox-1 containing six distinct monomers. We use this and the nuclear magnetic resonance (NMR) structure of the Fox-1 protein/RNA complex for molecular dynamics (MD) analyses of the structured hydration. The individual monomers of the X-ray structure show diverse hydration patterns, however, MD excellently reproduces the most occupied hydration sites. Simulations of the protein/RNA complex show hydration consistent with the isolated protein complemented by hydration sites specific to the protein/RNA interface. MD predicts intricate hydration sites with water-binding times extending up to hundreds of nanoseconds. We characterize two of them using NMR spectroscopy, RNA binding with switchSENSE and free-energy calculations of mutant proteins. Both hydration sites are experimentally confirmed and their abolishment reduces the binding free-energy. A quantitative agreement between theory and experiment is achieved for the S155A substitution but not for the S122A mutant. The S155 hydration site is evolutionarily conserved within the RRM domains. In conclusion, MD is an effective tool for predicting and interpreting the hydration patterns of protein/RNA complexes. Hydration is not easily detectable in NMR experiments but can affect stability of protein/RNA complexes.

Protein-RNA complexation driven by the charge regulation mechanism

Electrostatic interactions play a pivotal role in many (bio)molecular association processes. The molecular organization and function in biological systems are largely determined by these interactions from pure Coulombic contributions to more peculiar mesoscopic forces due to ion-ion correlation and proton fluctuations. The latter is a general electrostatic mechanism that gives attraction particularly at low electrolyte concentrations. This charge regulation mechanism due to titrating amino acid and nucleotides residues is discussed here in a purely electrostatic framework. By means of constant-pH Monte Carlo simulations based on a fast coarse-grained titration proton scheme, a new computer molecular model was devised to study protein-RNA interactions. The complexation between the RNA silencing suppressor p19 viral protein and the 19-bp small interfering RNA was investigated at different solution pH and salt conditions. The outcomes illustrate the importance of the charge regulation mechanism that enhances the association between these macromolecules in a similar way as observed for other protein-polyelectrolyte systems typically found in colloidal science. Due to the highly negative charge of RNA, the effect is more pronounced in this system as predicted by the Kirkwood-Shumaker theory. Our results contribute to the general physico-chemical understanding of macromolecular complexation and shed light on the extensive role of RNA in the cell's life.

Designing synthetic RNA for delivery by nanoparticles

The rapid development of synthetic biology and nanobiotechnology has led to the construction of various synthetic RNA nanoparticles of different functionalities and potential applications. As they occur naturally, nucleic acids are an attractive construction material for biocompatible nanoscaffold and nanomachine design. In this review, we provide an overview of the types of RNA and nucleic acid's nanoparticle design, with the focus on relevant nanostructures utilized for gene-expression regulation in cellular models. Structural analysis and modeling is addressed along with the tools available for RNA structural prediction. The functionalization of RNA-based nanoparticles leading to prospective applications of such constructs in potential therapies is shown. The route from the nanoparticle design and modeling through synthesis and functionalization to cellular application is also described. For a better understanding of the fate of targeted RNA after delivery, an overview of RNA processing inside the cell is also provided.

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.

Folding of guanine quadruplex molecules-funnel-like mechanism or kinetic partitioning? An overview from MD simulation studies

BACKGROUND

Guanine quadruplexes (GQs) play vital roles in many cellular processes and are of much interest as drug targets. In contrast to the availability of many structural studies, there is still limited knowledge on GQ folding.

SCOPE OF REVIEW

We review recent molecular dynamics (MD) simulation studies of the folding of GQs, with an emphasis paid to the human telomeric DNA GQ. We explain the basic principles and limitations of all types of MD methods used to study unfolding and folding in a way accessible to non-specialists. We discuss the potential role of G-hairpin, G-triplex and alternative GQ intermediates in the folding process. We argue that, in general, folding of GQs is fundamentally different from funneled folding of small fast-folding proteins, and can be best described by a kinetic partitioning (KP) mechanism. KP is a competition between at least two (but often many) well-separated and structurally different conformational ensembles.

MAJOR CONCLUSIONS

The KP mechanism is the only plausible way to explain experiments reporting long time-scales of GQ folding and the existence of long-lived sub-states. A significant part of the natural partitioning of the free energy landscape of GQs comes from the ability of the GQ-forming sequences to populate a large number of syn-anti patterns in their G-tracts. The extreme complexity of the KP of GQs typically prevents an appropriate description of the folding landscape using just a few order parameters or collective variables.

GENERAL SIGNIFICANCE

We reconcile available computational and experimental studies of GQ folding and formulate basic principles characterizing GQ folding landscapes. This article is part of a Special Issue entitled "G-quadruplex" Guest Editor: Dr. Concetta Giancola and Dr. Daniela Montesarchio.

How to understand atomistic molecular dynamics simulations of RNA and protein-RNA complexes?

We provide a critical assessment of explicit-solvent atomistic molecular dynamics (MD) simulations of RNA and protein/RNA complexes, written primarily for non-specialists with an emphasis to explain the limitations of MD. MD simulations can be likened to hypothetical single-molecule experiments starting from single atomistic conformations and investigating genuine thermal sampling of the biomolecules. The main advantage of MD is the unlimited temporal and spatial resolution of positions of all atoms in the simulated systems. Fundamental limitations are the short physical time-scale of simulations, which can be partially alleviated by enhanced-sampling techniques, and the highly approximate atomistic force fields describing the simulated molecules. The applicability and present limitations of MD are demonstrated on studies of tetranucleotides, tetraloops, ribozymes, riboswitches and protein/RNA complexes. Wisely applied simulations respecting the approximations of the model can successfully complement structural and biochemical experiments. WIREs RNA 2017, 8:e1405. doi: 10.1002/wrna.1405 For further resources related to this article, please visit the WIREs website.

NMR solution structure determination of large RNA-protein complexes

Structure determination of RNA-protein complexes is essential for our understanding of the multiple layers of RNA-mediated posttranscriptional regulation of gene expression. Over the past 20years, NMR spectroscopy became a key tool for structural studies of RNA-protein interactions. Here, we review the progress being made in NMR structure determination of large ribonucleoprotein assemblies. We discuss approaches for the design of RNA-protein complexes for NMR structural studies, established and emerging isotope and segmental labeling schemes suitable for large RNPs and how to gain distance restraints from NOEs, PREs and EPR and orientational information from RDCs and SAXS/SANS in such systems. The new combination of NMR measurements with MD simulations and its potential will also be discussed. Application and combination of these various methods for structure determination of large RNPs will be illustrated with three large RNA-protein complexes (>40kDa) and other interesting complexes determined in the past six and a half years.

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.

RNA folding pathways in stop motion

We introduce a method for predicting RNA folding pathways, with an application to the most important RNA tetraloops. The method is based on the idea that ensembles of three-dimensional fragments extracted from high-resolution crystal structures are heterogeneous enough to describe metastable as well as intermediate states. These ensembles are first validated by performing a quantitative comparison against available solution nuclear magnetic resonance (NMR) data of a set of RNA tetranucleotides. Notably, the agreement is better with respect to the one obtained by comparing NMR with extensive all-atom molecular dynamics simulations. We then propose a procedure based on diffusion maps and Markov models that makes it possible to obtain reaction pathways and their relative probabilities from fragment ensembles. This approach is applied to study the helix-to-loop folding pathway of all the tetraloops from the GNRA and UNCG families. The results give detailed insights into the folding mechanism that are compatible with available experimental data and clarify the role of intermediate states observed in previous simulation studies. The method is computationally inexpensive and can be used to study arbitrary conformational transitions.