Refinement of the Cornell et al. Nucleic Acids Force Field Based on Reference Quantum Chemical Calculations of Glycosidic Torsion Profiles

Spatial arrangement of functional domains in OxyS stress response sRNA

Small noncoding RNAs are an important class of regulatory RNAs in bacteria, often regulating responses to changes in environmental conditions. OxyS is a 110 nt, stable, trans-encoded small RNA found in Escherichia coli and is induced by an increased concentration of hydrogen peroxide. OxyS has an important regulatory role in cell stress response, affecting the expression of multiple genes. In this work, we investigated the structure of OxyS and the interaction with fhlA mRNA using nuclear magnetic resonance spectroscopy, small-angle X-ray scattering, and unbiased molecular dynamics simulations. We determined the secondary structures of isolated stem-loops and confirmed their structural integrity in OxyS. Unexpectedly, stem-loop SL4 was identified in the region that was predicted to be unstructured. Three-dimensional models of OxyS demonstrate that OxyS adopts an extended structure with four solvent-exposed stem-loops, which are available for interaction with other RNAs and proteins. Furthermore, we provide evidence of base-pairing between OxyS and fhlA mRNA.

Delta SARS-CoV-2 s2m Structure, Dynamics, and Entropy: Consequences of the G15U Mutation

Bioinformatic analysis of the Delta SARS-CoV-2 genome reveals a single nucleotide mutation (G15U) in the stem-loop II motif (s2m) relative to ancestral SARS-CoV-2. Despite sequence similarity, unexpected differences between SARS-CoV-2 and Delta SARS-CoV-2 s2m homodimerization experiments require the discovery of unknown structural and thermodynamic changes necessary to rationalize the data. Using our reported SARS-CoV-2 s2m model, we induced the G15U substitution and performed 3.5 microseconds of unbiased molecular dynamics simulation at 283 and 310 K. The resultant Delta s2m adopted a secondary structure consistent with our reported NMR data, resulting in significant deviations in the tertiary structure and dynamics from our SARS-CoV-2 s2m model. First, we find differences in the overall three-dimensional structure, where the characteristic 90° L-shaped kink of the SARS-CoV-2 s2m did not form in the Delta s2m resulting in a "linear" hairpin with limited bending dynamics. Delta s2m helical parameters are calculated to align closely with A-form RNA, effectively eliminating a hinge point to form the L-shape kink by correcting an upper stem defect in SARS-CoV-2 induced by a noncanonical and dynamic G:A base pair. Ultimately, the shape difference rationalizes the migration differences in reported electrophoresis experiments. Second, increased fluctuation of the Delta s2m palindromic sequence, within the terminal loop, compared to SARS-CoV-2 s2m results in an estimated increase of entropy of 6.8 kcal/mol at 310 K relative to the SARS-CoV-2 s2m. The entropic difference offers a unique perspective on why the Delta s2m homodimerizes less spontaneously, forming fewer kissing dimers and extended duplexes compared to SARS-CoV-2. In this work, both the L-shape reduction and palindromic entropic penalty provides an explanation of our reported in vitro electrophoresis homodimerization results. Ultimately, the structural, dynamical, and entropic differences between the SARS-CoV-2 s2m and Delta s2m serve to establish a foundation for future studies of the s2m function in the viral lifecycle.

Structure of pre-miR-31 reveals an active role in Dicer-TRBP complex processing

As an essential posttranscriptional regulator of gene expression, microRNA (miRNA) levels must be strictly maintained. The biogenesis of many miRNAs is mediated by trans-acting protein partners through a variety of mechanisms, including remodeling of the RNA structure. miR-31 functions as an oncogene in numerous cancers, and interestingly, its biogenesis is not known to be regulated by protein-binding partners. Therefore, the intrinsic structural properties of the precursor element of miR-31 (pre-miR-31) can provide a mechanism by which its biogenesis is regulated. We determined the solution structure of pre-miR-31 to investigate the role of distinct structural elements in regulating processing by the Dicer-TRBP complex. We found that the presence or absence of mismatches within the helical stem does not strongly influence Dicer-TRBP processing of the pre-miRNAs. However, both the apical loop size and structure at the Dicing site are key elements for discrimination by the Dicer-TRBP complex. Interestingly, our NMR-derived structure reveals the presence of a triplet of base pairs that link the Dicer cleavage site and the apical loop. Mutational analysis in this region suggests that the stability of the junction region strongly influences processing by the Dicer-TRBP complex. Our results enrich our understanding of the active role that RNA structure plays in regulating miRNA biogenesis, which has direct implications for the control of gene expression.

Streamlining and Optimizing Strategies of Electrostatic Parameterization

Accurate characterization of electrostatic interactions is crucial in molecular simulation. Various methods and programs have been developed to obtain electrostatic parameters for additive or polarizable models to replicate electrostatic properties obtained from experimental measurements or theoretical calculations. Electrostatic potentials (ESPs), a set of physically well-defined observables from quantum mechanical (QM) calculations, are well suited for optimization efforts due to the ease of collecting a large amount of conformation-dependent data. However, a reliable set of QM ESP computed at an appropriate level of theory and atomic basis set is necessary. In addition, despite the recent development of the PyRESP program for electrostatic parameterizations of induced dipole-polarizable models, the time-consuming and error-prone input file preparation process has limited the widespread use of these protocols. This work aims to comprehensively evaluate the quality of QM ESPs derived by eight methods, including wave function methods such as Hartree-Fock (HF), second-order Møller-Plesset (MP2), and coupled cluster-singles and doubles (CCSD), as well as five hybrid density functional theory (DFT) methods, used in conjunction with 13 different basis sets. The highest theory levels CCSD/aug-cc-pV5Z (a5z) and MP2/aug-cc-pV5Z (a5z) were selected as benchmark data over two homemade data sets. The results show that the hybrid DFT method, ωB97X-D, combined with the aug-cc-pVTZ (a3z) basis set, performs well in reproducing ESPs while taking both accuracy and efficiency into consideration. Moreover, a flexible and user-friendly program called PyRESP_GEN was developed to streamline input file preparation. The restraining strengths, along with strategies for polarizable Gaussian multipole (pGM) model parameterizations, were also optimized. These findings and the program presented in this work facilitate the development and application of induced dipole-polarizable models, such as pGM models, for molecular simulations of both chemical and biological significance.

Assessment of an Electrostatic Energy-Based Charge Model for Modeling the Electrostatic Interactions in Water Solvent

The protein force field based on the restrained electrostatic potential (RESP) charges has limitations in accurately describing hydrogen bonding interactions in proteins. To address this issue, we propose an alternative approach called the electrostatic energy-based charges (EEC) model, which shows improved performance in describing electrostatic interactions (EIs) of hydrogen bonds in proteins. In this study, we further investigate the performance of the EEC model in modeling EIs in water solvent. Our findings demonstrate that the fixed EEC model can effectively reproduce the quantum mechanics/molecular mechanics (QM/MM)-calculated EIs between a water molecule and various water solvent environments. However, to achieve the same level of computational accuracy, the electrostatic potential (ESP) charge model needs to fluctuate according to the electrostatic environment. Our analysis indicates that the requirement for charge adjustments depends on the specific mathematical and physical representation of EIs as a function of the environment for deriving charges. By comparing with widely used empirical water models calibrated to reproduce experimental properties, we confirm that the performance of the EEC model in reproducing QM/MM EIs is similar to that of general purpose TIP4P-like water models such as TIP4P-Ew and TIP4P/2005. When comparing the computed 10,000 distinct EI values within the range of -40 to 0 kcal/mol with the QM/MM results calculated at the MP2/aug-cc-pVQZ/TIP3P level, we noticed that the mean unsigned error (MUE) for the EEC model is merely 0.487 kcal/mol, which is remarkably similar to the MUE values of the TIP4P-Ew (0.63 kcal/mol) and TIP4P/2005 (0.579 kcal/mol) models. However, both the RESP method and the TIP3P model exhibit a tendency to overestimate the EIs, as evidenced by their higher MUE values of 1.761 and 1.293 kcal/mol, respectively. EEC-based molecular dynamics simulations have demonstrated that, when combined with appropriate van der Waals parameters, the EEC model can closely reproduce oxygen-oxygen radial distribution function and density of water, showing a remarkable similarity to the well-established TIP4P-like empirical water models. Our results demonstrate that the EEC model has the potential to build force fields with comparable accuracy to more sophisticated empirical TIP4P-like water models.

Decoding the dual recognition mechanism of the glucocorticoid receptor for DNA and RNA: sequence versus shape

Transcription factors (TFs) regulate eukaryotic transcription through selective DNA-binding, can also specifically interact with RNA, which may present another layer of transcriptional control. The mechanisms of the TFs-DNA recognition are often well-characterised, while the details of TFs-RNA complexation are less understood. Here we investigate the dual recognition mechanism of the glucocorticoid receptor (GR), which interacts with similar affinities with consensus DNA and diverse RNA hairpin motifs but discriminates against uniform dsRNA. Using atomic molecular dynamics simulations, we demonstrate that the GR binding to nucleic acids requires a wide and shallow groove pocket. The protein effectively moulds its binding site within DNA major groove, which enables base-specific interactions. Contrary, the GR binding has little effect on the grooves geometry of RNA systems, most notably in uniform dsRNA. Instead, a hairpin motif in RNA yields a wide and shallow major groove pocket, allowing the protein to anchor itself through nonspecific electrostatic contacts with RNA backbone. Addition of a bulge increases RNA hairpin flexibility, which leads to a greater number of GR-RNA contacts and, thus, higher affinity. Thus, the combination of structural motifs defines the GR-RNA selective binding: a recognition mechanism, which may be shared by other zinc finger TFs.

Terahertz waves regulate the mechanical unfolding of tau pre-mRNA hairpins

Intermolecular interactions, including hydrogen bonds, dominate the pairing and unpairing of nucleic acid chains in the transfer process of genetic information. The energy of THz waves just matches with the weak interactions, so THz waves may interact with biomolecules. Here, the dynamic effects of THz electromagnetic (EM) waves on the mechanical unfolding process of RNA hairpins (WT-30nt and its mutants, rHP, SARS-CoV-2, and SRV-1 SF206) are investigated using steered molecular dynamics (SMD) simulations. The results show that THz waves can either promote the unfolding of the double helix of the RNA hairpin during the initial unfolding phase (4-21.8 THz) or significantly enhance (23.8 and 25.5 THz) or weaken (37.4 and 41.2 THz) its structural stability during unfolding. Our findings have important implications for applying THz waves to regulate dynamic deconvolution processes, such as gene replication, transcription, and translation.

Dynamical characterization and multiple unbinding paths of two PreQ1 ligands in one pocket

Riboswitches naturally regulate gene expression in bacteria by binding to specific small molecules. Class 1 preQ1 riboswitch aptamer is an important model not only for RNA folding but also as a target for designing small molecule antibiotics due to its well-known minimal aptamer domain. Here, we ran a total of 62.4 μs conventional and enhanced-sampling molecular dynamics (MD) simulations to characterize the determinants underlying the binding of the preQ1-II riboswitch aptamer to two preQ1 ligands in one binding pocket. Decomposition of binding free energy suggested that preQ1 ligands at α and β sites interact with four nucleotides (G5, C17, C18, and A30) and two nucleotides (A12 and C31), respectively. Mg2+ ions play a crucial role in both stabilizing the binding pocket and facilitating ligand binding. The flexible preQ1 ligand at the β site leads to the top of the binding pocket loosening and thus pre-organizes the riboswitch for ligand entry. Enhanced sampling simulations further revealed that the preQ1 ligand at the α site unbinds through two orthogonal pathways, which are dependent on whether or not a β site preQ1 ligand is present. One of the two preQ1 ligands has been identified in the binding pocket, which will aid to identify the second preQ1 Ligand. Our work provides new information for designing robust ligands.

Comparative analysis of RNA secondary structure accuracy on predicted RNA 3D models

RNA structure is conformationally dynamic, and accurate all-atom tertiary (3D) structure modeling of RNA remains challenging with the prevailing tools. Secondary structure (2D) information is the standard prerequisite for most RNA 3D modeling. Despite several 2D and 3D structure prediction tools proposed in recent years, one of the challenges is to choose the best combination for accurate RNA 3D structure prediction. Here, we benchmarked seven small RNA PDB structures (40 to 90 nucleotides) with different topologies to understand the effects of different 2D structure predictions on the accuracy of 3D modeling. The current study explores the blind challenge of 2D to 3D conversions and highlights the performances of de novo RNA 3D modeling from their predicted 2D structure constraints. Our results show that conformational sampling-based methods such as SimRNA and IsRNA1 depend less on 2D accuracy, whereas motif-based methods account for 2D evidence. Our observations illustrate the disparities in available 3D and 2D prediction methods and may further offer insights into developing topology-specific or family-specific RNA structure prediction pipelines.

High-Fidelity, Hyper-Accurate, and Evolved Mutants Rewire Atomic Level Communication in CRISPR-Cas9

The Cas9-HF1, HypaCas9, and evoCas9 variants of the Cas9 endonuclease are critical tools to mitigate off-target effects in the application of CRISPR-Cas9 technology. The mechanisms by which mutations in the Rec3 domain mediate specificity in these variants are poorly understood. Here, solution NMR and molecular dynamics simulations establish the structural and dynamic effects of high-specificity mutations in Rec3, and how they propagate the allosteric signal of Cas9. We reveal conserved structural changes and peculiar dynamic differences at regions of Rec3 that interface with the RNA:DNA hybrid, transducing chemical signals from Rec3 to the catalytic HNH domain. The variants remodel the communication sourcing from the Rec3 α-helix 37, previously shown to sense target DNA complementarity, either directly or allosterically. This mechanism increases communication between the DNA mismatch recognition helix and the HNH active site, shedding light on the structure and dynamics underlying Cas9 specificity and providing insight for future engineering principles.

The Wild-Type tRNA Adenosine Deaminase Enzyme TadA Is Capable of Sequence-Specific DNA Base Editing

Base editors are genome editing tools that enable site-specific base conversions through the chemical modification of nucleobases in DNA. Adenine base editors (ABEs) convert A ⋅ T to G ⋅ C base pairs in DNA by using an adenosine deaminase enzyme to modify target adenosines to inosine intermediates. Due to the lack of a naturally occurring adenosine deaminase that can modify DNA, ABEs were evolved from a tRNA-deaminating enzyme, TadA. Previous experiments with an ABE comprising a wild-type (wt) TadA showed no detectable activity on DNA, and directed evolution was therefore required to enable this enzyme to accept DNA as a substrate. Here we show that wtTadA can perform base editing in DNA in both bacterial and mammalian cells, with a strict sequence motif requirement of TAC. We leveraged this discovery to optimize a reporter assay to detect base editing levels as low as 0.01 %. Finally, we used this assay along with molecular dynamics simulations of full ABE:DNA complexes to better understand how the sequence recognition of mutant TadA variants change as they accumulate mutations to better edit DNA substrates.

DOX_BDW: Incorporating Solvation and Desolvation Effects of Cavity Water into Nonfitting Protein-Ligand Binding Affinity Prediction

Accurate prediction of the protein-ligand binding affinity (PLBA) with an affordable cost is one of the ultimate goals in the field of structure-based drug design (SBDD), as well as a great challenge in the computational and theoretical chemistry. Herein, we have systematically addressed the complicated solvation and desolvation effects on the PLBA brought by the difference of the explicit water in the protein cavity before and after ligands bind to the protein-binding site. Based on the new solvation model, a nonfitting method at the first-principles level for the PLBA prediction was developed by taking the bridging and displaced water (BDW) molecules into account simultaneously. The newly developed method, DOX_BDW, was validated against a total of 765 noncovalent and covalent protein-ligand binding pairs, including the CASF2016 core set, Cov_2022 covalent binding testing set, and six testing sets for the hit and lead compound optimization (HLO) simulation. In all of the testing sets, the DOX_BDW method was able to produce PLBA predictions that were strongly correlated with the corresponding experimental data (R = 0.66-0.85). The overall performance of DOX_BDW is better than the current empirical scoring functions that are heavily parameterized. DOX_BDW is particularly outstanding for the covalent binding situation, implying the need for considering an electronic structure in covalent drug design. Furthermore, the method is especially recommended to be used in the HLO scenario of SBDD, where hundreds of similar derivatives need to be screened and refined. The computational cost of DOX_BDW is affordable, and its accuracy is remarkable.

Hierarchical Hydration Dynamics of RNA with Nano-Water-Pool at Its Core

Many functional RNAs fold into a compact, roughly globular shape by minimizing the electrostatic repulsion between their negatively charged phosphodiester backbone. The fold of such close, compact RNA architecture is often so designed that its outer surface and complex core both are predominately populated by phosphate groups loosely sequestering bases in the intermediate layers. A number of helical junctions maintain the RNA core and its nano-water-pool. While the folding of RNA is manifested by its counterion environment composed of mixed mono- and divalent salts, the concerted role of ion and water in maintaining an RNA fold is yet to be explored. In this work, detailed atomistic simulations of SAM-I and Add Adenine riboswitch aptamers, and subgenomic flavivirus RNA (sfRNA) have been performed in a physiological mixed mono- and divalent salt environment. All three RNA systems have compact folds with a core diameter of range 1-1.7 nm. The spatiotemporal heterogeneity of RNA hydration was probed in a layer-wise manner by distinguishing the core, the intermediate, and the outer layers. The layer-wise decomposition of hydrogen bonds and collective single-particle reorientational dynamics reveal a nonmonotonic relaxation pattern with the slowest relaxation observed at the intermediate layers that involves functionally important tertiary motifs. The slowness of this intermediate layer is attributed to two types of long-resident water molecules: (i) water from ion-hydration layers and (ii) structurally trapped water (distant from ions). The relaxation kinetics of the core and the surface water essentially exposed to the phosphate groups show well-separated time scales from the intermediate layers. In the slow intermediate layers, site-specific ions and water control the functional dynamics of important RNA motifs like kink-turn, observed in different structure-probing experiments. Most interestingly, we find that as the size of the RNA core increases (SAM1 core < sfRNAcore < Add adenine core), its hydration tends to show faster relaxation. The hierarchical hydration and the layer-wise base-phosphate composition uniquely portray the globular RNA to act like a soft vesicle with a quasi-dynamic nano-water-pool at its core.

RNA folding pathways from all-atom simulations with a variationally improved history-dependent bias

Atomically detailed simulations of RNA folding have proven very challenging in view of the difficulties of developing realistic force fields and the intrinsic computational complexity of sampling rare conformational transitions. As a step forward in tackling these issues, we extend to RNA an enhanced path-sampling method previously successfully applied to proteins. In this scheme, the information about the RNA's native structure is harnessed by a soft history-dependent biasing force promoting the generation of productive folding trajectories in an all-atom force field with explicit solvent. A rigorous variational principle is then applied to minimize the effect of the bias. Here, we report on an application of this method to RNA molecules from 20 to 47 nucleotides long and increasing topological complexity. By comparison with analog simulations performed on small proteins with similar size and architecture, we show that the RNA folding landscape is significantly more frustrated, even for relatively small chains with a simple topology. The predicted RNA folding mechanisms are found to be consistent with the available experiments and some of the existing coarse-grained models. Due to its computational performance, this scheme provides a promising platform to efficiently gather atomistic RNA folding trajectories, thus retain the information about the chemical composition of the sequence.

Magnesium ions mediate ligand binding and conformational transition of the SAM/SAH riboswitch

The SAM/SAH riboswitch binds S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) with similar affinities. Mg2+ is generally known to stabilize RNA structures by neutralizing phosphates, but how it contributes to ligand binding and conformational transition is understudied. Here, extensive molecular dynamics simulations (totaling 120 μs) predicted over 10 inner-shell Mg2+ ions in the SAM/SAH riboswitch. Six of them line the two sides of a groove to widen it and thereby pre-organize the riboswitch for ligand entry. They also form outer-shell coordination with the ligands and stabilize an RNA-ligand hydrogen bond, which effectively diminishes the selectivity between SAM and SAH. One Mg2+ ion unique to the apo form maintains the Shine-Dalgarno sequence in an autonomous mode and thereby facilitates its release for ribosome binding. Mg2+ thus plays vital roles in SAM/SAH riboswitch function.

New design strategies for ultra-specific CRISPR-Cas13a-based RNA-diagnostic tools with single-nucleotide mismatch sensitivity

The pressing need for clinical diagnostics has required the development of novel nucleic acid-based detection technologies that are sensitive, fast, and inexpensive, and that can be deployed at point-of-care. Recently, the RNA-guided ribonuclease CRISPR-Cas13 has been successfully harnessed for such purposes. However, developing assays for detection of genetic variability, for example single-nucleotide polymorphisms, is still challenging and previously described design strategies are not always generalizable. Here, we expanded our characterization of LbuCas13a RNA-detection specificity by performing a combination of experimental RNA mismatch tolerance profiling, molecular dynamics simulations, protein, and crRNA engineering. We found certain positions in the crRNA-target-RNA duplex that are particularly sensitive to mismatches and establish the effect of RNA concentration in mismatch tolerance. Additionally, we determined that shortening the crRNA spacer or modifying the direct repeat of the crRNA leads to stricter specificities. Furthermore, we harnessed our understanding of LbuCas13a allosteric activation pathways through molecular dynamics and structure-guided engineering to develop novel Cas13a variants that display increased sensitivities to single-nucleotide mismatches. We deployed these Cas13a variants and crRNA design strategies to achieve superior discrimination of SARS-CoV-2 strains compared to wild-type LbuCas13a. Together, our work provides new design criteria and new Cas13a variants for easier-to-implement Cas13-based diagnostics.

KEY POINTS

Certain positions in the Cas13a crRNA-target-RNA duplex are particularly sensitive to mismatches.Understanding Cas13a's allosteric activation pathway allowed us to develop novel high-fidelity Cas13a variants.These Cas13a variants and crRNA design strategies achieve superior discrimination of SARS-CoV-2 strains.

GRAPHICAL ABSTRACT

RNA-mediated Allosteric Activation in CRISPR-Cas13a

Cas13a is a recent addition to the CRISPR-Cas toolkit that exclusively targets RNA, which makes it a promising tool for RNA detection. The protein uses a CRISPR RNA (crRNA) to target RNA sequences, which are cleaved by a composite active site formed by two 'Higher Eukaryotes and Prokaryotes Nucleotide' (HEPN) catalytic domains. In this system, an intriguing form of allosteric communication controls RNA cleavage activity, yet its molecular details are unknown. Here, multiple-microsecond molecular dynamics simulations are combined with graph theory and RNA cleavage assays to decipher this activation mechanism. We show that the binding of a target RNA acts as an allosteric effector of the spatially distant HEPN catalytic cleft, by amplifying the allosteric signals over the dynamical noise, that passes through the buried HEPN interface. Critical residues in this region - N378, R973, and R377 - rearrange their interactions upon target RNA binding, and alter allosteric signalling. Alanine mutation of these residues is experimentally shown to select target RNA over an extended complementary sequence beyond guide-target duplex, for RNA cleavage. Altogether, our findings offer a fundamental understanding of the Cas13a mechanism of action and pave new avenues for the development of more selective RNA-based cleavage and detection tools.

Individual Contributions of Amido Acid Residues Tyr122, Ile168, and Asp173 to the Activity and Substrate Specificity of Human DNA Dioxygenase ABH2

Human Fe(II)/α-ketoglutarate-dependent dioxygenase ABH2 plays a crucial role in the direct reversal repair of nonbulky alkyl lesions in DNA nucleobases, e.g., N¹-methyladenine (m¹A), N³-methylcytosine (m³C), and some etheno derivatives. Moreover, ABH2 is capable of a less efficient oxidation of an epigenetic DNA mark called 5-methylcytosine (m⁵C), which typically is a specific target of DNA dioxygenases from the TET family. In this study, to elucidate the mechanism of the substrate specificity of ABH2, we investigated the role of several active-site amino acid residues. Functional mapping of the lesion-binding pocket was performed through the analysis of the functions of Tyr122, Ile168, and Asp173 in the damaged base recognition mechanism. Interactions of wild-type ABH2, or its mutants Y122A, I168A, or D173A, with damaged DNA containing the methylated base m¹A or m³C or the epigenetic marker m⁵C were analyzed by molecular dynamics simulations and kinetic assays. Comparative analysis of the enzymes revealed an effect of the substitutions on DNA binding and on catalytic activity. Obtained data clearly demonstrate the effect of the tested amino acid residues on the catalytic activity of the enzymes rather than the DNA-binding ability. Taken together, these data shed light on the molecular and kinetic consequences of the substitution of active-site residues for the mechanism of the substrate recognition.

Epigenetic CpG duplex marks probed by an evolved DNA reader via a well-tempered conformational plasticity

5-methylcytosine (mC) and its TET-oxidized derivatives exist in CpG dyads of mammalian DNA and regulate cell fate, but how their individual combinations in the two strands of a CpG act as distinct regulatory signals is poorly understood. Readers that selectively recognize such novel 'CpG duplex marks' could be versatile tools for studying their biological functions, but their design represents an unprecedented selectivity challenge. By mutational studies, NMR relaxation, and MD simulations, we here show that the selectivity of the first designer reader for an oxidized CpG duplex mark hinges on precisely tempered conformational plasticity of the scaffold adopted during directed evolution. Our observations reveal the critical aspect of defined motional features in this novel reader for affinity and specificity in the DNA/protein interaction, providing unexpected prospects for further design progress in this novel area of DNA recognition.

Toward a Molecular Mechanism of Complementary RNA Duplexes Denaturation

RNA duplexes are relatively rare but play very important biological roles. As an end-product of template-based RNA replication, they also have key implications for hypothetical primitive forms of life. Unless they are specifically separated by enzymes, these duplexes denature upon a temperature increase. However, mechanistic and kinetic aspects of RNA (and DNA) duplex thermal denaturation remain unclear at the microscopic level. We propose an in silico strategy that probes the thermal denaturation of RNA duplexes and allows for an extensive conformational space exploration along a wide temperature range with atomistic precision. We show that this approach first accounts for the strong sequence and length dependence of the duplexes melting temperature, reproducing the trends seen in the experiments and predicted by nearest-neighbor models. The simulations are then instrumental at providing a molecular picture of the temperature-induced strand separation. The textbook canonical "all-or-nothing" two-state model, very much inspired by the protein folding mechanism, can be nuanced. We demonstrate that a temperature increase leads to significantly distorted but stable structures with extensive base-fraying at the extremities, and that the fully formed duplexes typically do not form around melting. The duplex separation therefore appears as much more gradual than commonly thought.

Molecular Dynamics Simulations Elucidate the Molecular Basis of Pre-mRNA Translocation by the Prp2 Spliceosomal Helicase

The spliceosome machinery catalyzes precursor-messenger RNA (pre-mRNA) splicing by undergoing at each splicing cycle assembly, activation, catalysis, and disassembly processes, thanks to the concerted action of specific RNA-dependent ATPases/helicases. Prp2, a member of the DExH-box ATPase/helicase family, harnesses the energy of ATP hydrolysis to translocate a single pre-mRNA strand in the 5' to 3' direction, thus promoting spliceosome remodeling to its catalytic-competent state. Here, we established the functional coupling between ATPase and helicase activities of Prp2. Namely, extensive multi-μs molecular dynamics simulations allowed us to unlock how, after pre-mRNA selection, ATP binding, hydrolysis, and dissociation induce a functional typewriter-like rotation of the Prp2 C-terminal domain. This movement, endorsed by an iterative swing of interactions established between specific Prp2 residues with the nucleobases at 5'- and 3'-ends of pre-mRNA, promotes pre-mRNA translocation. Notably, some of these Prp2 residues are conserved in the DExH-box family, suggesting that the translocation mechanism elucidated here may be applicable to all DExH-box helicases.

Benchmarking Molecular Dynamics Force Fields for All-Atom Simulations of Biological Condensates

Proteins containing intrinsically disordered regions are integral parts of the cellular signaling pathways and common components of biological condensates. Point mutations in the protein sequence, genetic at birth or acquired through aging, can alter the properties of the condensates, marking the onset of neurodegenerative diseases such as ALS and dementia. While the all-atom molecular dynamics method can, in principle, elucidate the conformational changes that arise from point mutations, the applications of this method to protein condensate systems is conditioned upon the availability of molecular force fields that can accurately describe both structured and disordered regions of such proteins. Using the special-purpose Anton 2 supercomputer, we benchmarked the efficacy of nine presently available molecular force fields in describing the structure and dynamics of a Fused in sarcoma (FUS) protein. Five-microsecond simulations of the full-length FUS protein characterized the effect of the force field on the global conformation of the protein, self-interactions among its side chains, solvent accessible surface area, and the diffusion constant. Using the results of dynamic light scattering as a benchmark for the FUS radius of gyration, we identified several force fields that produced FUS conformations within the experimental range. Next, we used these force fields to perform ten-microsecond simulations of two structured RNA binding domains of FUS bound to their respective RNA targets, finding the choice of the force field to affect stability of the RNA-FUS complex. Taken together, our data suggest that a combination of protein and RNA force fields sharing a common four-point water model provides an optimal description of proteins containing both disordered and structured regions and RNA-protein interactions. To make simulations of such systems available beyond the Anton 2 machines, we describe and validate implementation of the best performing force fields in a publicly available molecular dynamics program NAMD. Our NAMD implementation enables simulations of large (tens of millions of atoms) biological condensate systems and makes such simulations accessible to a broader scientific community.

Conformational dynamics of RNA G4C2 and G2C4 repeat expansions causing ALS/FTD using NMR and molecular dynamics studies

G4C2 and G2C4 repeat expansions in chromosome 9 open reading frame 72 (C9orf72) are the most common cause of genetically defined amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), or c9ALS/FTD. The gene is bidirectionally transcribed, producing G4C2 repeats [r(G4C2)exp] and G2C4 repeats [r(G2C4)exp]. The c9ALS/FTD repeat expansions are highly structured, and structural studies showed that r(G4C2)exp predominantly folds into a hairpin with a periodic array of 1 × 1 G/G internal loops and a G-quadruplex. A small molecule probe revealed that r(G4C2)exp also adopts a hairpin structure with 2 × 2 GG/GG internal loops. We studied the conformational dynamics adopted by 2 × 2 GG/GG loops using temperature replica exchange molecular dynamics (T-REMD) and further characterized the structure and underlying dynamics using traditional 2D NMR techniques. These studies showed that the loop's closing base pairs influence both structure and dynamics, particularly the configuration adopted around the glycosidic bond. Interestingly, r(G2C4) repeats, which fold into an array of 2 × 2 CC/CC internal loops, are not as dynamic. Collectively, these studies emphasize the unique sensitivity of r(G4C2)exp to small changes in stacking interactions, which is not observed in r(G2C4)exp, providing important considerations for further principles in structure-based drug design.

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.

Mutagenesis and structural studies reveal the basis for the specific binding of SARS-CoV-2 SL3 RNA element with human TIA1 protein

Viral RNA-host protein interactions are indispensable during RNA virus transcription and replication, but their detailed structural and dynamical features remain largely elusive. Here, we characterize the binding interface for the SARS-CoV-2 stem-loop 3 (SL3) cis-acting element to human TIA1 protein with a combined theoretical and experimental approaches. The highly structured SARS-CoV-2 SL3 has a high binding affinity to TIA1 protein, in which the aromatic stacking, hydrogen bonds, and hydrophobic interactions collectively direct this specific binding. Further mutagenesis studies validate our proposed 3D binding model and reveal two SL3 variants have enhanced binding affinities to TIA1. And disruptions of the identified RNA-protein interactions with designed antisense oligonucleotides dramatically reduce SARS-CoV-2 infection in cells. Finally, TIA1 protein could interact with conserved SL3 RNA elements within other betacoronavirus lineages. These findings open an avenue to explore the viral RNA-host protein interactions and provide a pioneering structural basis for RNA-targeting antiviral drug design.

The Effect of Ethanol on Lipid Nanoparticle Stabilization from a Molecular Dynamics Simulation Perspective

Lipid nanoparticles (LNPs) have emerged as a promising delivery system, particularly for genetic therapies and vaccines. LNP formation requires a specific mixture of nucleic acid in a buffered solution and lipid components in ethanol. Ethanol acts as a lipid solvent, aiding the formation of the nanoparticle's core, but its presence can also affect LNP stability. In this study, we used molecular dynamics (MD) simulations to investigate the physicochemical effect of ethanol on LNPs and gain a dynamic understanding of its impact on the overall structure and stability of LNPs. Our results demonstrate that ethanol destabilizes LNP structure over time, indicated by increased root mean square deviation (RMSD) values. Changes in the solvent-accessible surface area (SASA), electron density, and radial distribution function (RDF) also suggest that ethanol affects LNP stability. Furthermore, our H-bond profile analysis shows that ethanol penetrates the LNP earlier than water. These findings emphasize the importance of immediate ethanol removal in lipid-based systems during LNP production to ensure stability.

The PIWI-specific insertion module helps load longer piRNAs for translational activation essential for male fertility

PIWI-clade proteins harness piRNAs of 24-33 nt in length. Of great puzzles are how PIWI-clade proteins incorporate piRNAs of different sizes and whether the size matters to PIWI/piRNA function. Here we report that a PIWI-Ins module unique in PIWI-clade proteins helps define the length of piRNAs. Deletion of PIWI-Ins in Miwi shifts MIWI to load with shorter piRNAs and causes spermiogenic failure in mice, demonstrating the functional importance of this regulatory module. Mechanistically, we show that longer piRNAs provide additional complementarity to target mRNAs, thereby enhancing the assembly of the MIWI/eIF3f/HuR super-complex for translational activation. Importantly, we identify a c.1108C>T (p.R370W) mutation of HIWI (human PIWIL1) in infertile men and demonstrate in Miwi knock-in mice that this genetic mutation impairs male fertility by altering the property of PIWI-Ins in selecting longer piRNAs. These findings reveal a critical role of PIWI-Ins-ensured longer piRNAs in fine-tuning MIWI/piRNA targeting capacity, proven essential for spermatid development and male fertility.

Conformational dynamics and mechanical properties of biomimetic RNA, DNA, and RNA-DNA hybrid nanotubes: an atomistic molecular dynamics study

With the nanotechnology boom, artificially designed nucleic acid nanotubes have aroused interest due to their practical applications in nanorobotics, vaccine design, membrane channels, drug delivery, and force sensing. In this paper, computational study was performed to investigate the structural dynamics and mechanical properties of RNA nanotubes (RNTs), DNA nanotubes (DNTs), and RNA-DNA hybrid nanotubes (RDHNTs). So far, the structural and mechanical properties of RDHNTs have not been examined in experiments or theoretical calculations, and there is limited knowledge regarding these properties for RNTs. Here, the simulations were carried out using the equilibrium molecular dynamics (MD) and steered molecular dynamics (SMD) approaches. Using in-house scripting, we modeled hexagonal nanotubes composed of six double-stranded molecules connected by four-way Holliday junctions. Classical MD analyses were performed on the collected trajectory data to investigate structural properties. Analyses of the microscopic structural parameters of RDHNT indicated a structural transition from the A-form to a conformation between the A- and B-forms, which may be attributable to the increased rigidity of RNA scaffolds compared to DNA staples. Comprehensive research on the elastic mechanical properties was also conducted based on spontaneous thermal fluctuations of nanotubes and employing the equipartition theorem. The Young's modulus of RDHNT (E = 165 MPa) and RNT (E = 144 MPa) was found to be almost the same and nearly half of that found for DNT (E = 325 MPa). Furthermore, the results showed that RNT was more resistant to bending, torsional, and volumetric deformations than DNT and RDHNT. We also used non-equilibrium SMD simulations to acquire comprehensive knowledge of the mechanical response of nanotubes to tensile stress.

Structural and dynamic effects of pseudouridine modifications on noncanonical interactions in RNA

Pseudouridine is the most frequently naturally occurring RNA modification, found in all classes of biologically functional RNAs. Compared to uridine, pseudouridine contains an additional hydrogen bond donor group and is therefore widely regarded as a structure stabilizing modification. However, the effects of pseudouridine modifications on the structure and dynamics of RNAs have so far only been investigated in a limited number of different structural contexts. Here, we introduced pseudouridine modifications into the U-turn motif and the adjacent U:U closing base pair of the neomycin-sensing riboswitch (NSR)-an extensively characterized model system for RNA structure, ligand binding, and dynamics. We show that the effects of replacing specific uridines with pseudouridines on RNA dynamics crucially depend on the exact location of the replacement site and can range from destabilizing to locally or even globally stabilizing. By using a combination of NMR spectroscopy, MD simulations and QM calculations, we rationalize the observed effects on a structural and dynamical level. Our results will help to better understand and predict the consequences of pseudouridine modifications on the structure and function of biologically important RNAs.

Effect of Cas9 Protein on the Seed-Target Base Pair of the sgRNA/DNA Hybrid Duplex

CRISPR (clustered regularly interspaced short palindromic repeats)/CRISPR-associated protein (Cas9) has been widely used for gene editing. Not all guide RNAs can cleave the DNA efficiently remains a major challenge to CRISPR/Cas9-mediated genome engineering. Therefore, understanding how the Cas9 complex successfully and efficiently identifies specific functional targets through base-pairing has great implications for such applications. The 10-nt seed sequence at the 3' end of the guide RNA is critical to target recognition and cleavage. Here, through stretching molecular dynamics simulation, we studied the thermodynamics and kinetics of the binding-dissociation process of the seed base and the target DNA base with the Cas9 protein. The results showed that in the presence of Cas9 protein, the enthalpy change and entropy change in binding-dissociation of the seed base with the target are smaller than those without the Cas9 protein. The reduction of entropy penalty upon association with the protein resulted from the pre-organization of the seed base in an A-form helix, and the reduction of enthalpy change was due to the electrostatic attraction of the positively charged channel with the negative target DNA. The binding barrier coming from the entropy loss and the dissociation barrier resulting from the destruction of the base pair in the presence of Cas9 protein were lower than those without protein, which indicates that the seed region is crucial for efficiently searching the correct target by accelerating the binding rate and dissociating fast from the wrong target.

Structural basis of substrate recognition by human tRNA splicing endonuclease TSEN

Heterotetrameric human transfer RNA (tRNA) splicing endonuclease TSEN catalyzes intron excision from precursor tRNAs (pre-tRNAs), utilizing two composite active sites. Mutations in TSEN and its associated RNA kinase CLP1 are linked to the neurodegenerative disease pontocerebellar hypoplasia (PCH). Despite the essential function of TSEN, the three-dimensional assembly of TSEN-CLP1, the mechanism of substrate recognition, and the structural consequences of disease mutations are not understood in molecular detail. Here, we present single-particle cryogenic electron microscopy reconstructions of human TSEN with intron-containing pre-tRNAs. TSEN recognizes the body of pre-tRNAs and pre-positions the 3' splice site for cleavage by an intricate protein-RNA interaction network. TSEN subunits exhibit large unstructured regions flexibly tethering CLP1. Disease mutations localize far from the substrate-binding interface and destabilize TSEN. Our work delineates molecular principles of pre-tRNA recognition and cleavage by human TSEN and rationalizes mutations associated with PCH.

Catalytic mechanism and pH dependence of a methyltransferase ribozyme (MTR1) from computational enzymology

A methyltransferase ribozyme (MTR1) was selected in vitro to catalyze alkyl transfer from exogenous O6-methylguanine (O6mG) to a target adenine N1, and recently, high-resolution crystal structures have become available. We use a combination of classical molecular dynamics, ab initio quantum mechanical/molecular mechanical (QM/MM) and alchemical free energy (AFE) simulations to elucidate the atomic-level solution mechanism of MTR1. Simulations identify an active reactant state involving protonation of C10 that hydrogen bonds with O6mG:N1. The deduced mechanism involves a stepwise mechanism with two transition states corresponding to proton transfer from C10:N3 to O6mG:N1 and rate-controlling methyl transfer (19.4  kcal·mol-1 barrier). AFE simulations predict the pKa for C10 to be 6.3, close to the experimental apparent pKa of 6.2, further implicating it as a critical general acid. The intrinsic rate derived from QM/MM simulations, together with pKa calculations, enables us to predict an activity-pH profile that agrees well with experiment. The insights gained provide further support for a putative RNA world and establish new design principles for RNA-based biochemical tools.

The Activity of Natural Polymorphic Variants of Human DNA Polymerase β Having an Amino Acid Substitution in the Transferase Domain

To maintain the integrity of the genome, there is a set of enzymatic systems, one of which is base excision repair (BER), which includes sequential action of DNA glycosylases, apurinic/apyrimidinic endonucleases, DNA polymerases, and DNA ligases. Normally, BER works efficiently, but the enzymes themselves (whose primary function is the recognition and removal of damaged bases) are subject to amino acid substitutions owing to natural single-nucleotide polymorphisms (SNPs). One of the enzymes in BER is DNA polymerase β (Polβ), whose function is to fill gaps in DNA with complementary dNMPs. It is known that many SNPs can cause an amino acid substitution in this enzyme and a significant decrease in the enzymatic activity. In this study, the activity of four natural variants of Polβ, containing substitution E154A, G189D, M236T, or R254I in the transferase domain, was analyzed using molecular dynamics simulations and pre-steady-state kinetic analyses. It was shown that all tested substitutions lead to a significant reduction in the ability to form a complex with DNA and with incoming dNTP. The G189D substitution also diminished Polβ catalytic activity. Thus, a decrease in the activity of studied mutant forms may be associated with an increased risk of damage to the genome.

Monovalent Ionic Atmosphere Modulates the Selection of Suboptimal RNA Sequences by Splicing Factors' RNA Recognition Motifs

The U2AF2 splicing factor is involved in the RNA recognition of the pre-mRNA poly-pyrimidine signaling sequence. This protein contains two RRM domains connected by a flexible linker, which ensure the preferential selection of a poly-uridine sequence over a poly-cytosine one. In this work, all-atom simulations provide insights into the U2AF2 recognition mechanism and on the features underlying its selectivity. Our outcomes show that U2AF2's RNA recognition is driven by cooperative events modulated by RNA-protein and RNA-ion interactions. Stunningly, monovalent ions contribute to mediating the binding of the weakly binding polyC strand, thus contributing to the selection of suboptimal poly-pyrimidine tracts. This finding broadens our understanding of the diverse traits tuning splicing factors' selectivity and adaptability to precisely handle and process diverse pre-mRNA sequences.

The Catalytic Mechanism of Acetoacetate Decarboxylase: A Detailed Study of Schiff Base Formation, Protonation States, and Their Impact on Catalysis

The enzyme acetoacetate decarboxylase (AAD) has a crucial function in the process of decarboxylating the substrate acetoacetate (AA). It has been extensively studied over the years, but its exact catalytic mechanism has remained partly unsolved due to the difficulty in assessing reaction intermediates. In this study, we combine molecular dynamics and electronic structure calculations to rediscover its catalytic mechanism. Our results show that the presence of the substrate, the acetoacetate, significantly influences the electrostatic potential of the active site. Furthermore, our simulations show that the decarboxylation reaction can take place by means of a direct proton transfer instead of via an enamine intermediate, which is thought to be strictly necessary. This work provides new insights into the role of the electrostatic interactions on the catalytic activity of AAD and for the first time connects it to the catalytic mechanism of other decarboxylases.

Binding to the conserved and stably folded guide RNA pseudoknot induces Cas12a conformational changes during ribonucleoprotein assembly

Ribonucleoproteins (RNPs) comprise one or more RNA and protein molecules that interact to form a stable complex, which commonly involves conformational changes in the more flexible RNA components. Here, we propose that Cas12a RNP assembly with its cognate CRISPR RNA (crRNA) guide instead proceeds primarily through Cas12a conformational changes during binding to more stable, prefolded crRNA 5' pseudoknot handles. Phylogenetic reconstructions and sequence and structure alignments revealed that the Cas12a proteins are divergent in sequence and structure while the crRNA 5' repeat region, which folds into a pseudoknot and anchors binding to Cas12a, is highly conserved. Molecular dynamics simulations of three Cas12a proteins and their cognate guides revealed substantial flexibility for unbound apo-Cas12a. In contrast, crRNA 5' pseudoknots were predicted to be stable and independently folded. Limited trypsin hydrolysis, differential scanning fluorimetry, thermal denaturation, and CD analyses supported conformational changes of Cas12a during RNP assembly and an independently folded crRNA 5' pseudoknot. This RNP assembly mechanism may be rationalized by evolutionary pressure to conserve CRISPR loci repeat sequence, and therefore guide RNA structure, to maintain function across all phases of the CRISPR defense mechanism.

Molecular mechanism of binding between a therapeutic RNA aptamer and its protein target VEGF: A molecular dynamics study

Macugen is a therapeutic RNA aptamer against vascular endothelial growth factor (VEGF)-165, the VEGF isoform primarily responsible for angiogenesis. It has been reported that Macugen inhibits angiogenesis by specifically binding to the heparin binding domain (HBD) of VEGF165. The mechanism of the molecular recognition between HBD and Macugen is investigated here using all-atom molecular dynamics simulations. We find that Macugen recognizes HBD by an induced-fit mechanism with major conformational changes in Macugen and almost no changes in the structure of HBD, whereas HBD recognizes Macugen by a conformational selection mechanism.

Synthesis, antiviral activity, and computational study of β-d-xylofuranosyl nucleoside phosphonates

Molecular dynamics (MD) simulations provided insights into the favorable interactions between xylose nucleosides bearing a phosphonate moiety at their 3'-position and specific residues at the active site of the archetypal RNA-dependent RNA-polymerase (RdRp) of Enterovirus 71. Therefore, a series of xylosyl nucleoside phosphonates with adenine, uracil, cytosine, guanosine, and hypoxanthine as nucleobases were synthesized through multistep sequences starting from a single common precursor. Following antiviral activity evaluation, the adenine containing analogue was found to possess good antiviral activity against RNA viruses displaying an EC₅₀ of 12 and 16 μM against measles virus (MeV) and enterovirus-68 (EV-68), respectively, whereas lacking cytotoxicity.

Machines on Genes through the Computational Microscope

Macromolecular machines acting on genes are at the core of life's fundamental processes, including DNA replication and repair, gene transcription and regulation, chromatin packaging, RNA splicing, and genome editing. Here, we report the increasing role of computational biophysics in characterizing the mechanisms of "machines on genes", focusing on innovative applications of computational methods and their integration with structural and biophysical experiments. We showcase how state-of-the-art computational methods, including classical and ab initio molecular dynamics to enhanced sampling techniques, and coarse-grained approaches are used for understanding and exploring gene machines for real-world applications. As this review unfolds, advanced computational methods describe the biophysical function that is unseen through experimental techniques, accomplishing the power of the "computational microscope", an expression coined by Klaus Schulten to highlight the extraordinary capability of computer simulations. Pushing the frontiers of computational biophysics toward a pragmatic representation of large multimegadalton biomolecular complexes is instrumental in bridging the gap between experimentally obtained macroscopic observables and the molecular principles playing at the microscopic level. This understanding will help harness molecular machines for medical, pharmaceutical, and biotechnological purposes.

Sensitivity of the RNA Structure to Ion Conditions as Probed by Molecular Dynamics Simulations of Common Canonical RNA Duplexes

RNA molecules play a key role in countless biochemical processes. RNA interactions, which are of highly diverse nature, are determined by the fact that RNA is a highly negatively charged polyelectrolyte, which leads to intimate interactions with an ion atmosphere. Although RNA molecules are formally single-stranded, canonical (Watson-Crick) duplexes are key components of folded RNAs. A double-stranded (ds) RNA is also important for the design of RNA-based nanostructures and assemblies. Despite the fact that the description of canonical dsRNA is considered the least problematic part of RNA modeling, the imperfect shape and flexibility of dsRNA can lead to imbalances in the simulations of larger RNAs and RNA-containing assemblies. We present a comprehensive set of molecular dynamics (MD) simulations of four canonical A-RNA duplexes. Our focus was directed toward the characterization of the influence of varying ion concentrations and of the size of the solvation box. We compared several water models and four RNA force fields. The simulations showed that the A-RNA shape was most sensitive to the RNA force field, with some force fields leading to a reduced inclination of the A-RNA duplexes. The ions and water models played a minor role. The effect of the box size was negligible, and even boxes with a small fraction of the bulk solvent outside the RNA hydration sphere were sufficient for the simulation of the dsRNA.

Force-dependent elasticity of nucleic acids

The functioning of double-stranded (ds) nucleic acids (NAs) in cellular processes is strongly mediated by their elastic response. These processes involve proteins that interact with dsDNA or dsRNA and distort their structures. The perturbation of the elasticity of NAs arising from these deformations is not properly considered by most theoretical frameworks. In this work, we introduce a novel method to assess the impact of mechanical stress on the elastic response of dsDNA and dsRNA through the analysis of the fluctuations of the double helix. Application of this approach to atomistic simulations reveals qualitative differences in the force dependence of the mechanical properties of dsDNA with respect to those of dsRNA, which we relate to structural features of these molecules by means of physically-sound minimalistic models.

The effects of RNA.DNA-DNA triple helices on nucleosome structures and dynamics

Noncoding RNAs (ncRNAs) are an emerging epigenetic factor and have been recognized as playing a key role in many gene expression pathways. Structurally, binding of ncRNAs to isolated DNA is strongly dependent on sequence complementary and results in the formation of an RNA.DNA-DNA (RDD) triple helix. However, in vivo DNA is not isolated but is rather packed in chromatin fibers, the fundamental unit of which is the nucleosome. Biochemical experiments have shown that ncRNA binding to nucleosomal DNA is elevated at DNA entry and exit sites and is dependent on the presence of the H3 N-terminal tails. However, the structural and dynamical bases for these mechanisms remain unknown. Here, we have examined the mechanisms and effects of RDD formation in the context of the nucleosome using a series of all-atom molecular dynamics simulations. Results highlight the importance of DNA sequence on complex stability, elucidate the effects of the H3 tails on RDD structures, show how RDD formation impacts the structure and dynamics of the H3 tails, and show how RNA alters the local and global DNA double-helical structure. Together, our results suggest ncRNAs can modify nucleosome, and potentially higher-order chromatin, structures and dynamics as a means of exerting epigenetic control.

Recognizing the power of machine learning and other computational methods to accelerate progress in small molecule targeting of RNA

RNA structures regulate a wide range of processes in biology and disease, yet small molecule chemical probes or drugs that can modulate these functions are rare. Machine learning and other computational methods are well poised to fill gaps in knowledge and overcome the inherent challenges in RNA targeting, such as the dynamic nature of RNA and the difficulty of obtaining RNA high-resolution structures. Successful tools to date include principal component analysis, linear discriminate analysis, k-nearest neighbor, artificial neural networks, multiple linear regression, and many others. Employment of these tools has revealed critical factors for selective recognition in RNA:small molecule complexes, predictable differences in RNA- and protein-binding ligands, and quantitative structure activity relationships that allow the rational design of small molecules for a given RNA target. Herein we present our perspective on the value of using machine learning and other computation methods to advance RNA:small molecule targeting, including select examples and their validation as well as necessary and promising future directions that will be key to accelerate discoveries in this important field.

A riboswitch separated from its ribosome-binding site still regulates translation

Riboswitches regulate downstream gene expression by binding cellular metabolites. Regulation of translation initiation by riboswitches is posited to occur by metabolite-mediated sequestration of the Shine-Dalgarno sequence (SDS), causing bypass by the ribosome. Recently, we solved a co-crystal structure of a prequeuosine1-sensing riboswitch from Carnobacterium antarcticum that binds two metabolites in a single pocket. The structure revealed that the second nucleotide within the gene-regulatory SDS, G34, engages in a crystal contact, obscuring the molecular basis of gene regulation. Here, we report a co-crystal structure wherein C10 pairs with G34. However, molecular dynamics simulations reveal quick dissolution of the pair, which fails to reform. Functional and chemical probing assays inside live bacterial cells corroborate the dispensability of the C10-G34 pair in gene regulation, leading to the hypothesis that the compact pseudoknot fold is sufficient for translation attenuation. Remarkably, the C. antarcticum aptamer retained significant gene-regulatory activity when uncoupled from the SDS using unstructured spacers up to 10 nucleotides away from the riboswitch-akin to steric-blocking employed by sRNAs. Accordingly, our work reveals that the RNA fold regulates translation without SDS sequestration, expanding known riboswitch-mediated gene-regulatory mechanisms. The results infer that riboswitches exist wherein the SDS is not embedded inside a stable fold.

Human Polβ Natural Polymorphic Variants G118V and R149I Affects Substate Binding and Catalysis

DNA polymerase β (Polβ) expression is essential for the cell's response to DNA damage that occurs during natural cellular processes. Polβ is considered the main reparative DNA polymerase, whose role is to fill the DNA gaps arising in the base excision repair pathway. Mutations in Polβ can lead to cancer, neurodegenerative diseases, or premature aging. Many single-nucleotide polymorphisms have been identified in the POLB gene, but the consequences of these polymorphisms are not always clear. It is known that some polymorphic variants in the Polβ sequence reduce the efficiency of DNA repair, thereby raising the frequency of mutations in the genome. In the current work, we studied two polymorphic variants (G118V and R149I separately) of human Polβ that affect its DNA-binding region. It was found that each amino acid substitution alters Polβ's affinity for gapped DNA. Each polymorphic variant also weakens its binding affinity for dATP. The G118V variant was found to greatly affect Polβ's ability to fill gapped DNA and slowed the catalytic rate as compared to the wild-type enzyme. Thus, these polymorphic variants seem to decrease the ability of Polβ to maintain base excision repair efficiency.

Molecular dynamics and Raman optical activity spectra reveal nucleotide conformation ratios in solution

Nucleotide conformational flexibility affects their biological functions. Although the spectroscopy of Raman optical activity (ROA) is well suited to structural analyses in aqueous solutions, the link between the spectral shape and the nucleotide geometry is not fully understood. We recorded the Raman and ROA spectra of model nucleotides (rAMP, rGMP, rCMP, and dTMP) and interpreted them on the basis of molecular dynamics (MD) combined with density functional theory (DFT). The relation between the sugar puckering, base conformation and spectral intensities is discussed. Hydrogen bonds between the sugar's C3' hydroxyl and the phosphate groups were found to be important for the sugar puckering. The simulated spectra correlated well with the experimental data and provided an understanding of the dependence of the spectral shapes on conformational dynamics. Most of the strongest spectral bands could be assigned to vibrational molecular motions. Decomposition of the experimental spectra into calculated subspectra based on arbitrary maps of free energies provided experimental conformer populations, which could be used to verify and improve the MD predictions. The analyses indicate some flaws of common MD force fields, such as being unable to describe the fine conformer distribution. Also the accuracy of conformer populations obtained from the spectroscopic data depends on the simulations, improvement of which is desirable for gaining a more detailed insight in the future. Improvement of the spectroscopic and computational methodology for nucleotides also provides opportunities for its application to larger nucleic acids.

Therapeutic phosphorodiamidate morpholino oligonucleotides: Physical properties, solution structures, and folding thermodynamics

Elucidating the structure-function relationships for therapeutic RNA mimicking phosphorodiamidate morpholino oligonucleotides (PMOs) is challenging due to the lack of information about their structures. While PMOs have been approved by the US Food and Drug Administration for treatment of Duchenne muscular dystrophy, no structural information on these unique, charge-neutral, and stable molecules is available. We performed circular dichroism and solution viscosity measurements combined with molecular dynamics simulations and machine learning to resolve solution structures of 22-mer, 25-mer, and 30-mer length PMOs. The PMO conformational dynamics are defined by the competition between non-polar nucleobases and uncharged phosphorodiamidate groups for shielding from solvent exposure. PMO molecules form non-canonical, partially helical, stable folded structures with a small 1.4- to 1.7-nm radius of gyration, low count of three to six base pairs and six to nine base stacks, characterized by -34 to -51 kcal/mol free energy, -57 to -103 kcal/mol enthalpy, and -23 to -53 kcal/mol entropy for folding. The 4.5- to 6.2-cm³/g intrinsic viscosity and Huggins constant of 4.5-9.9 are indicative of extended and aggregating systems. The results obtained highlight the importance of the conformational ensemble view of PMO solution structures, thermodynamic stability of their non-canonical structures, and concentration-dependent viscosity properties. These principles form a paradigm to understand the structure-properties-function relationship for therapeutic PMOs to advance the design of new RNA-mimic-based drugs.

Magnesium ions mediate ligand binding and conformational transition of the SAM/SAH riboswitch

The SAM/SAH riboswitch binds S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) with similar affinities. Mg 2+ is generally known to stabilize RNA structures by neutralizing phosphates, but how it contributes to ligand binding and conformational transition is understudied. Here, extensive molecular dynamics simulations (totaling 120 μs) identified over 10 inner-shell Mg 2+ ions in the SAM/SAH riboswitch. Six of them line the two sides of a groove to widen it and thereby pre-organize the riboswitch for ligand entry. They also form outer-shell coordination with the ligands and stabilize an RNA-ligand hydrogen bond, which effectively diminish the selectivity between SAM and SAH. One Mg 2+ ion unique to the apo form maintains the Shine-Dalgarno sequence in an autonomous mode and thereby facilitates its release for ribosome binding. Mg 2+ thus plays vital roles in SAM/SAH riboswitch function.

Mechanism of Chiral-Selective Aminoacylation of an RNA Minihelix Explored by QM/MM Free-Energy Simulations

Aminoacylation of a primordial RNA minihelix composed of D-ribose shows L-amino acid preference over D-amino acid without any ribozymes or enzymes. This preference in the amino acylation reaction likely plays an important role in the establishment of homochirality in L-amino acid in modern proteins. However, molecular mechanisms of the chiral selective reaction remain unsolved mainly because of difficulty in direct observation of the reaction at the molecular scale by experiments. For seeking a possible mechanism of the chiral selectivity, quantum mechanics/molecular mechanics (QM/MM) umbrella sampling molecular dynamics (MD) simulations of the aminoacylation reactions in a modeled RNA were performed to investigate differences in their free-energy profiles along the reactions for L- and D-alanine and its physicochemical origin. The reaction is initiated by approaching a 3′-oxygen of the RNA minihelix to the carbonyl carbon of an aminoacyl phosphate oligonucleotide. The QM/MM umbrella sampling MD calculations showed that the height of the free-energy barrier for L-alanine aminoacylation reaction was 17 kcal/mol, which was 9 kcal/mol lower than that for the D-alanine system. At the transition state, the distance between the negatively charged 3′-oxygen and the positively charged amino group of L-alanine was shorter than that of D-alanine, which was caused by the chirality difference of the amino acid. These results indicate that the transition state for L-alanine is more electrostatically stabilized than that for D-alanine, which would be a plausible mechanism previously unexplained for chiral selectivity in the RNA minihelix aminoacylation.

The Electronic Structure of Genome Editors from the First Principles

Genome editing based on the CRISPR-Cas9 system has paved new avenues for medicine, pharmaceutics, biotechnology, and beyond. This article reports the role of first-principles (ab-initio) molecular dynamics (MD) in the CRISPR-Cas9 revolution, achieving a profound understanding of the enzymatic function and offering valuable insights for enzyme engineering. We introduce the methodologies and explain the use of ab-initio MD simulations to characterize the two-metal dependent mechanism of DNA cleavage in the RuvC domain of the Cas9 enzyme, and how a second catalytic domain, HNH, cleaves the target DNA with the aid of a single metal ion. A detailed description of how ab-initio MD is combined with free-energy methods - i.e., thermodynamic integration and metadynamics - to break and form chemical bonds is given, explaining the use of these methods to determine the chemical landscape and establish the catalytic mechanism in CRISPR-Cas9. The critical role of classical methods is also discussed, explaining theory and application of constant pH MD simulations, used to accurately predict the catalytic residues' protonation states. Overall, first-principles methods are shown to unravel the electronic structure of the Cas9 enzyme, providing valuable insights that can serve for the design of genome editing tools with improved catalytic efficiency or controllable activity.