Comprehensive Comparison and Critical Assessment of RNA-Specific Force Fields.

Molecular dynamics simulations play a pivotal role in elucidating the dynamic behaviors of RNA structures, offering a valuable complement to traditional methods such as nuclear magnetic resonance or X-ray. Despite this, the current precision of RNA force fields lags behind that of protein force fields. In this work, we systematically compared the performance of four RNA force fields (ff99bsc0χOL3, AMBERDES, ff99OL3_CMAP1, AMBERMaxEnt) across diverse RNA structures. Our findings highlight significant challenges in maintaining stability, particularly with regard to cross-strand and cross-loop hydrogen bonds. Furthermore, we observed the limitations in accurately describing the conformations of nonhelical structural motif, terminal nucleotides, and also base pairing and base stacking interactions by the tested RNA force fields. The identified deficiencies in existing RNA force fields provide valuable insights for subsequent force field development. Concurrently, these findings offer recommendations for selecting appropriate force fields in RNA simulations.

Accurate prediction of RNA secondary structure including pseudoknots through solving minimum-cost flow with learned potentials.

Pseudoknots are key structure motifs of RNA and pseudoknotted RNAs play important roles in a variety of biological processes. Here, we present KnotFold, an accurate approach to the prediction of RNA secondary structure including pseudoknots. The key elements of KnotFold include a learned potential function and a minimum-cost flow algorithm to find the secondary structure with the lowest potential. KnotFold learns the potential from the RNAs with known structures using an attention-based neural network, thus avoiding the inaccuracy of hand-crafted energy functions. The specially designed minimum-cost flow algorithm used by KnotFold considers all possible combinations of base pairs and selects from them the optimal combination. The algorithm breaks the restriction of nested base pairs required by the widely used dynamic programming algorithms, thus enabling the identification of pseudoknots. Using 1,009 pseudoknotted RNAs as representatives, we demonstrate the successful application of KnotFold in predicting RNA secondary structures including pseudoknots with accuracy higher than the state-of-the-art approaches. We anticipate that KnotFold, with its superior accuracy, will greatly facilitate the understanding of RNA structures and functionalities.

Odd-even disparity in the population of slipped hairpins in RNA repeat sequences with implications for phase separation.

Low-complexity nucleotide repeat sequences, which are implicated in several neurological disorders, undergo liquid-liquid phase separation (LLPS) provided the number of repeat units, n, exceeds a critical value. Here, we establish a link between the folding landscapes of the monomers of trinucleotide repeats and their propensity to self-associate. Simulations using a coarse-grained Self-Organized Polymer (SOP) model for (CAG)n repeats in monovalent salt solutions reproduce experimentally measured melting temperatures, which are available only for small n. By extending the simulations to large n, we show that the free-energy gap, ΔGS, between the ground state (GS) and slipped hairpin (SH) states is a predictor of aggregation propensity. The GS for even n is a perfect hairpin (PH), whereas it is a SH when n is odd. The value of ΔGS (zero for odd n) is larger for even n than for odd n. As a result, the rate of dimer formation is slower in (CAG)30 relative to (CAG)31, thus linking ΔGS to RNA-RNA association. The yield of the dimer decreases dramatically, compared to the wild type, in mutant sequences in which the population of the SH decreases substantially. Association between RNA chains is preceded by a transition to the SH even if the GS is a PH. The finding that the excitation spectrum-which depends on the exact sequence, n, and ionic conditions-is a predictor of self-association should also hold for other RNAs (mRNA for example) that undergo LLPS.

Equilibrium fluctuations of DNA plectonemes.

Plectonemes are intertwined helically looped domains which form when a DNA molecule is supercoiled, i.e., over- or underwound. They are ubiquitous in cellular DNA, and their physical properties have attracted significant interest both from the experimental side and from the modeling side. In this paper, we investigate fluctuations of the end-point distance z of supercoiled linear DNA molecules subject to external stretching forces. Our analysis is based on a two-phase model, which describes the supercoiled DNA as composed of a stretched phase and a plectonemic phase. A variety of mechanisms are found to contribute to extension fluctuations, characterized by the variance 〈Δz^{2}〉. We find the dominant contribution to 〈Δz^{2}〉 to originate from phase-exchange fluctuations, the transient shrinking and expansion of plectonemes, which is accompanied by an exchange of molecular length between the two phases. We perform Monte Carlo simulations of the twistable wormlike chain and analyze the fluctuation of various quantities, the results of which are found to agree with the two-phase model predictions. Furthermore, we show that the extension and its variance at high forces are very well captured by the two-phase model, provided that one goes beyond quadratic approximations.

Simulations of DNA-Origami Self-Assembly Reveal Design-Dependent Nucleation Barriers.

Nucleation is the rate-determining step in the kinetics of many self-assembly processes. However, the importance of nucleation in the kinetics of DNA-origami self-assembly, which involves both the binding of staple strands and the folding of the scaffold strand, is unclear. Here, using Monte Carlo simulations of a lattice model of DNA origami, we find that some, but not all, designs can have a nucleation barrier and that this barrier disappears at lower temperatures, rationalizing the success of isothermal assembly. We show that the height of the nucleation barrier depends primarily on the coaxial stacking of staples that are adjacent on the same helix, a parameter that can be modified with staple design. Creating a nucleation barrier to DNA-origami assembly could be useful in optimizing assembly times and yields, while eliminating the barrier may allow for fast molecular sensors that can assemble/disassemble without hysteresis in response to changes in the environment.

Markov state models elucidate the stability of DNA influenced by the chiral 5S-Tg base.

The static and dynamic structures of DNA duplexes affected by 5S-Tg (Tg, Thymine glycol) epimers were studied using MD simulations and Markov State Models (MSMs) analysis. The results show that the 5S,6S-Tg base caused little perturbation to the helix, and the base-flipping barrier was determined to be 4.4 kcal mol-1 through the use of enhanced sampling meta-eABF calculations, comparable to 5.4 kcal mol-1 of the corresponding thymine flipping. Two conformations with the different hydrogen bond structures between 5S,6R-Tg and A19 were identified in several independent MD trajectories. The 5S,6R-Tg:O6HO6•••N1:A19 hydrogen bond is present in the high-energy conformation displaying a clear helical distortion, and near barrier-free Tg base flipping. The low-energy conformation always maintains Watson-Crick base pairing between 5S,6R-Tg and A19, and 5S-Tg base flipping is accompanied by a small barrier of ca. 2.0 KBT (T = 298 K). The same conformations are observed in the MSMs analysis. Moreover, the transition path and metastable structures of the damaged base flipping are for the first time verified through MSMs analysis. The data clearly show that the epimers have completely different influence on the stability of the DNA duplex, thus implying different enzymatic mechanisms for DNA repair.

Inhibition of the hexamerization of SARS-CoV-2 endoribonuclease and modeling of RNA structures bound to the hexamer.

Non-structural protein 15 (Nsp15) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) forms a homo hexamer and functions as an endoribonuclease. Here, we propose that Nsp15 activity may be inhibited by preventing its hexamerization through drug binding. We first explored the stable conformation of the Nsp15 monomer as the global free energy minimum conformation in the free energy landscape using a combination of parallel cascade selection molecular dynamics (PaCS-MD) and the Markov state model (MSM), and found that the Nsp15 monomer forms a more open conformation with larger druggable pockets on the surface. Targeting the pockets with high druggability scores, we conducted ligand docking and identified compounds that tightly bind to the Nsp15 monomer. The top poses with Nsp15 were subjected to binding free energy calculations by dissociation PaCS-MD and MSM (dPaCS-MD/MSM), indicating the stability of the complexes. One of the identified pockets, which is distinctively bound by inosine analogues, may be an alternative binding site to stabilize viral RNA binding and/or an alternative catalytic site. We constructed a stable RNA structure model bound to both UTP and alternative binding sites, providing a reasonable proposed model of the Nsp15/RNA complex.

DNA damage modeled with Geant4-DNA: effects of plasmid DNA conformation and experimental conditions.

The chemical stage of the Monte Carlo track-structure (MCTS) code Geant4-DNA was extended for its use in DNA strand break (SB) simulations and compared against published experimental data. Geant4-DNA simulations were performed using pUC19 plasmids (2686 base pairs) in a buffered solution of DMSO irradiated by60Co or137Csγ-rays. A comprehensive evaluation of SSB yields was performed considering DMSO, DNA concentration, dose and plasmid supercoiling. The latter was measured using the super helix density value used in a Brownian dynamics plasmid generation algorithm. The Geant4-DNA implementation of the independent reaction times method (IRT), developed to simulate the reaction kinetics of radiochemical species, allowed to score the fraction of supercoiled, relaxed and linearized plasmid fractions as a function of the absorbed dose. The percentage of the number of SB after •OH + DNA and H• + DNA reactions, referred as SSB efficiency, obtained using MCTS were 13.77% and 0.74% respectively. This is in reasonable agreement with published values of 12% and 0.8%. The SSB yields as a function of DMSO concentration, DNA concentration and super helix density recreated the expected published experimental behaviors within 5%, one standard deviation. The dose response of SSB and DSB yields agreed with published measurements within 5%, one standard deviation. We demonstrated that the developed extension of IRT in Geant4-DNA, facilitated the reproduction of experimental conditions. Furthermore, its calculations were strongly in agreement with experimental data. These two facts will facilitate the use of this extension in future radiobiological applications, aiding the study of DNA damage mechanisms with a high level of detail.

The kinetic landscape of nucleosome assembly: A coarse-grained molecular dynamics study.

The organization of nucleosomes along the Eukaryotic genome is maintained over time despite disruptive events such as replication. During this complex process, histones and DNA can form a variety of non-canonical nucleosome conformations, but their precise molecular details and roles during nucleosome assembly remain unclear. In this study, employing coarse-grained molecular dynamics simulations and Markov state modeling, we characterized the complete kinetics of nucleosome assembly. On the nucleosome-positioning 601 DNA sequence, we observe a rich transition network among various canonical and non-canonical tetrasome, hexasome, and nucleosome conformations. A low salt environment makes nucleosomes stable, but the kinetic landscape becomes more rugged, so that the system is more likely to be trapped in off-pathway partially assembled intermediates. Finally, we find that the co-operativity between DNA bending and histone association enables positioning sequence motifs to direct the assembly process, with potential implications for the dynamic organization of nucleosomes on real genomic sequences.

Discovery of 17 conserved structural RNAs in fungi.

Many non-coding RNAs with known functions are structurally conserved: their intramolecular secondary and tertiary interactions are maintained across evolutionary time. Consequently, the presence of conserved structure in multiple sequence alignments can be used to identify candidate functional non-coding RNAs. Here, we present a bioinformatics method that couples iterative homology search with covariation analysis to assess whether a genomic region has evidence of conserved RNA structure. We used this method to examine all unannotated regions of five well-studied fungal genomes (Saccharomyces cerevisiae, Candida albicans, Neurospora crassa, Aspergillus fumigatus, and Schizosaccharomyces pombe). We identified 17 novel structurally conserved non-coding RNA candidates, which include four H/ACA box small nucleolar RNAs, four intergenic RNAs and nine RNA structures located within the introns and untranslated regions (UTRs) of mRNAs. For the two structures in the 3' UTRs of the metabolic genes GLY1 and MET13, we performed experiments that provide evidence against them being eukaryotic riboswitches.

Investigating the anticancer properties of the two new platinum complexes with iso- and tert-pentylglycine by the DFT, molecular docking, and ADMET assessment and experimental confirmations.

In this study, two new anticancer platinum complexes formulated as [Pt(bpy)(L)]NO3 were synthesized using the iso and tert-pentylglycine ligands, two structural isomer ligands, to investigate side branches effect on the complex-DNA interaction. According to the comparative results of the ADMET assessment, these compounds can be considered as the drug-like molecules and oral medication. Mechanism of tumor inhibition and DNA binding parameters indicated the higher ability of the tert-isomer and also, both complexes acted through the disruption of the base pairs and stacks of helicity by the endothermic process. Fluorescence spectroscopy showed that the quenching mechanism is static for both drugs with large binding constant and high binding affinity towards the DNA. Also, the amount of binding constant of the tert -isomer was about 14 times of another structural isomerous complex. CD spectra indicated the conversion of the B-DNA into A-DNA form via electrostatic interaction for positively charged complexes. The cytotoxic data showed that both compounds have antiproliferative effects against the MCF-7 cell line and the inhibitory effect of the iso-derivative was better than the tert-one. Docking studies showed that the desolvation energy and hydrogen bond are more effective between the other interactions. The torsional free energy for both complexes mainly provided the groove binding along with partially electrostatic and intercalate binding. According to the density-functional theory data and because of positive electron density on the surface of complexes and facilitating of the metal drug to DNA phosphate groups approaching, both complexes may be good candidates for the anticancer drugs. Two new anticancer Pt(II) complexes were synthesized with glycine derivatives. In vitro cytotoxicity effects were tested against the human breast cancer cell line of MCF-7. Moreover, the modes of DNA binding with synthesized compounds were investigated using ADME prediction, DFT, molecular docking and spectroscopic methods.

A critical role for linker DNA in higher-order folding of chromatin fibers.

Nucleosome-nucleosome interactions drive the folding of nucleosomal arrays into dense chromatin fibers. A better physical account of the folding of chromatin fibers is necessary to understand the role of chromatin in regulating DNA transactions. Here, we studied the unfolding pathway of regular chromatin fibers as a function of single base pair increments in linker length, using both rigid base-pair Monte Carlo simulations and single-molecule force spectroscopy. Both computational and experimental results reveal a periodic variation of the folding energies due to the limited flexibility of the linker DNA. We show that twist is more restrictive for nucleosome stacking than bend, and find the most stable stacking interactions for linker lengths of multiples of 10 bp. We analyzed nucleosomes stacking in both 1- and 2-start topologies and show that stacking preferences are determined by the length of the linker DNA. Moreover, we present evidence that the sequence of the linker DNA also modulates nucleosome stacking and that the effect of the deletion of the H4 tail depends on the linker length. Importantly, these results imply that nucleosome positioning in vivo not only affects the phasing of nucleosomes relative to DNA but also directs the higher-order structure of chromatin.

DNA Looping and DNA Conformational Fluctuations Can Accelerate Protein Target Search.

Protein searching and binding to specific sites on DNA is a fundamentally important process that marks the beginning of all major cellular transformations. While the dynamics of protein-DNA interactions in in vitro settings is well investigated, the situation is much more complex for in vivo conditions because the DNA molecules in live cells are packed into chromosomal structures where they are undergoing strong dynamic and conformational fluctuations. In this work, we present a theoretical investigation on the role of DNA looping and DNA conformational fluctuations in the protein target search. It is based on a discrete-state stochastic analysis that allows for explicit calculations of dynamic properties, which is also supplemented by Monte Carlo computer simulations. It is found that for stronger nonspecific interactions between DNA and proteins the search occurs faster on the DNA looped conformation in comparison with the unlooped conformation, and the fastest search is observed when the loop is formed near the target site. It is also shown that DNA fluctuations between the looped and unlooped conformations influence the search dynamics, and this depends on the magnitude of conformational transition rates and on which conformation is more energetically stable. Physical-chemical arguments explaining these observations are presented. Our theoretical study suggests that the geometry and conformational changes in DNA are additional factors that might efficiently control the gene regulation processes.

Single-molecule stretching experiments of flexible (wormlike) chain molecules in different ensembles: Theory and a potential application of finite chain length effects to nick-counting in DNA.

We propose a formalism for deriving force-elongation and elongation-force relations for flexible chain molecules from analytical expressions for their radial distribution function, which provides insight into the factors controlling the asymptotic behavior and finite chain length corrections. In particular, we apply this formalism to our previously developed interpolation formula for the wormlike chain end-to-end distance distribution. The resulting expression for the asymptotic limit of infinite chain length is of similar quality to the numerical evaluation of Marko and Siggia's variational theory and considerably more precise than their interpolation formula. A comparison to numerical data suggests that our analytical finite chain length corrections achieve a comparable accuracy. As an application of our results, we discuss the possibility of inferring the time-dependent number of nicks in single-molecule stretching experiments on double-stranded DNA from the accompanying changes in the effective chain length.

Assessment of AMBER Force Fields for Simulations of ssDNA.

Single-stranded DNA (ssDNA) plays an important role in biological processes and is used in DNA nanotechnology and other novel applications. Many important research questions can be addressed with molecular simulations of ssDNA molecules; however, no dedicated force field for ssDNA has been developed, and there is limited experimental information about ssDNA structures. This study assesses the accuracy and applicability of existing Amber force fields for all-atom simulations of ssDNA, such as ff99, bsc0, bsc1, and OL15, in implicit and explicit solvents via comparison to available experimental data, such as Forster resonance energy transfer and small angle X-ray scattering. We observed that some force fields agree better with experiments than others mainly due to the difference in parameterization of the propensity for hydrogen bonding and base stacking. Overall, the Amber ff99 force field in the IGB5 or IGB8 implicit solvent and the bsc1 force field in the explicit TIP3P solvent had the best agreement with experiment.

CD-NuSS: A Web Server for the Automated Secondary Structural Characterization of the Nucleic Acids from Circular Dichroism Spectra Using Extreme Gradient Boosting Decision-Tree, Neural Network and Kohonen Algorithms.

Nucleic acids exhibit a repertoire of conformational preference depending on the sequence and environment. Circular dichroism (CD) is an essential and valuable tool for monitoring such secondary structural conformations of nucleic acids. Nonetheless, the CD spectral diversity associated with these structures poses a challenge in obtaining the quantitative information about the secondary structural content of a given CD spectrum. To this end, the competence of the extreme gradient boosting decision-tree (XGBoost), Kohonen and neural network (nnet) algorithms have been exploited here to predict the diverse secondary structures of nucleic acids. A curated library of 450 CD spectra corresponding to 16 different secondary structures of nucleic acids has been created and used as a training dataset. The hyper-parameters corresponding to the aforementioned algorithms have been optimized using holdout and k-fold (here, k = 5) cross-validation methods. For a test dataset of 150 CD spectra, both the nnet and XGBoost algorithms have exhibited nearly similar prediction accuracy in the range of 85% and 87% (the latter exhibited a slightly higher prediction accuracy). Thus, the nnet and XGBoost algorithms tested here can be employed for predicting the hybrid nucleic acid topologies in future. For the sake of accessibility, the entire process has been automated and implemented as a webserver, called CD-NuSS (CD to nucleic acids secondary structure) and is freely accessible at https://project.iith.ac.in/cdnuss/.

Computational assessment of thermostability in miRNA:CNT system using molecular dynamics simulations.

BACKGROUND: Carbon nanotubes (CNTs) show great promise as theranostic agents due to their drug delivery properties, intrinsic near-infrared radiation-responsiveness, and magnetic functionalization. However, temperature elevation caused by these external stimuli during drug delivery should be considered for the evaluation of CNT-based systems loaded with temperature-sensitive biomolecules. METHODS: We examine the thermal stability of a 33 nucleotides long hairpin miRNA encapsulated in (20,20) CNT using all-atom molecular dynamics simulations in explicit water. We systematically increase the temperature as 298, 310, 327, and 343 K, reaching the melting temperature of miRNA. To emphasize the effect of the aromatic confined space, we compare the dynamics of miRNA inside the CNT to its dynamics free in the solution at the same temperatures, reaching a total simulation time of 7.9 µs. RESULTS: miRNA hairpin mostly maintains its double-stranded structure in the confined CNT, even at elevated temperatures. Binding free energies and potential of mean force calculations also underline the strong π-π interactions between the biomolecule and the CNT for 298-343 K. CONCLUSION: The let-7 miRNA mimic, which represents a wide family of RNAi-based therapeutics, can be transported in the CNT under medically applied hyperthermic conditions. GENERAL SIGNIFICANCE: This study shows how the structure and dynamics of miRNA hairpin are affected when encapsulated in an aromatic tube, during a systematic increase of temperature. It also indicates the high potential of CNT-based systems for the delivery of oligonucleotide therapeutics while simultaneous imaging/magnetic field guiding to the target tissue is achieved.

Deep learning predicts short non-coding RNA functions from only raw sequence data.

Small non-coding RNAs (ncRNAs) are short non-coding sequences involved in gene regulation in many biological processes and diseases. The lack of a complete comprehension of their biological functionality, especially in a genome-wide scenario, has demanded new computational approaches to annotate their roles. It is widely known that secondary structure is determinant to know RNA function and machine learning based approaches have been successfully proven to predict RNA function from secondary structure information. Here we show that RNA function can be predicted with good accuracy from a lightweight representation of sequence information without the necessity of computing secondary structure features which is computationally expensive. This finding appears to go against the dogma of secondary structure being a key determinant of function in RNA. Compared to recent secondary structure based methods, the proposed solution is more robust to sequence boundary noise and reduces drastically the computational cost allowing for large data volume annotations. Scripts and datasets to reproduce the results of experiments proposed in this study are available at: https://github.com/bioinformatics-sannio/ncrna-deep.

Contributions and competition of Mg2+ and K+ in folding and stabilization of the Twister ribozyme.

Native folded and compact intermediate states of RNA typically involve tertiary structures in the presence of divalent ions such as Mg2+ in a background of monovalent ions. In a recent study, we have shown how the presence of Mg2+ impacts the transition from partially unfolded to folded states through a "push-pull" mechanism where the ion both favors and disfavors the sampling of specific phosphate-phosphate interactions. To further understand the ion atmosphere of RNA in folded and partially folded states results from atomistic umbrella sampling and oscillating chemical potential grand canonical Monte Carlo/molecular dynamics (GCMC/MD) simulations are used to obtain atomic-level details of the distributions of Mg2+ and K+ ions around Twister RNA. Results show the presence of 100 mM Mg2+ to lead to increased charge neutralization over that predicted by counterion condensation theory. Upon going from partially unfolded to folded states, overall charge neutralization increases at all studied ion concentrations that, while associated with an increase in the number of direct ion-phosphate interactions, is fully accounted for by the monovalent K+ ions. Furthermore, K+ preferentially interacts with purine N7 atoms of helical regions in partially unfolded states, thereby potentially stabilizing the helical regions. Thus, both secondary helical structures and formation of tertiary structures leads to increased counterion condensation, thereby stabilizing those structural features of Twister. Notably, it is shown that K+ can act as a surrogate for Mg2+ by participating in specific interactions with nonsequential phosphate pairs that occur in the folded state, explaining the ability of Twister to self-cleave at submillimolar Mg2+ concentrations.

Inequality in the Frequency of the Open States Occurrence Depends on Single 2H/1H Replacement in DNA.

In the present study, the effect of 2H/1H isotopic exchange in hydrogen bonds between nitrogenous base pairs on occurrence and open states zones dynamics is investigated. These processes are studied using mathematical modeling, taking into account the number of open states between base pairs. The calculations of the probability of occurrence of open states in different parts of the gene were done depending on the localization of the deuterium atom. The mathematical modeling study demonstrated significant inequality (dependent on single 2H/1H replacement in DNA) among three parts of the gene similar in length of the frequency of occurrence of the open states. In this paper, the new convenient approach of the analysis of the abnormal frequency of open states in different parts of the gene encoding interferon alpha 17 was presented, which took into account both rising and decreasing of them that allowed to make a prediction of the functional instability of the specific DNA regions. One advantage of the new algorithm is diminishing the number of both false positive and false negative results in data filtered by this approach compared to the pure fractile methods, such as deciles or quartiles.