Reaction Coordinate and Thermodynamics of Base Flipping in RNA

Spontaneous base flipping helps drive Nsp15's preferences in double stranded RNA substrates

Coronaviruses evade detection by the host immune system with the help of the endoribonuclease Nsp15, which regulates levels of viral double stranded RNA by cleaving 3' of uridine (U). While prior structural data shows that to cleave double stranded RNA, Nsp15's target U must be flipped out of the helix, it is not yet understood whether Nsp15 initiates flipping or captures spontaneously flipped bases. We address this gap by designing fluorinated double stranded RNA substrates that allow us to directly relate a U's sequence context to both its tendency to spontaneously flip and its susceptibility to cleavage by Nsp15. Through a combination of nuclease assays, 19F NMR spectroscopy, mass spectrometry, and single particle cryo-EM, we determine that Nsp15 acts most efficiently on unpaired Us, particularly those that are already flipped. Across sequence contexts, we find Nsp15's cleavage efficiency to be directly related to that U's tendency to spontaneously flip. Overall, our findings unify previous characterizations of Nsp15's cleavage preferences, and suggest that activity of Nsp15 during infection is partially driven by bulged or otherwise relatively accessible Us that appear at strategic positions in the viral RNA.

Adenine Methylation Enhances the Conformational Flexibility of an RNA Hairpin Tetraloop

The N6-methyladenosine modification is one of the most abundant post-transcriptional modifications in ribonucleic acid (RNA) molecules. Using molecular dynamics simulations and alchemical free-energy calculations, we studied the structural and energetic implications of incorporating this modification in an adenine mononucleotide and an RNA hairpin structure. At the mononucleotide level, we found that the syn configuration is more favorable than the anti configuration by 2.05 ± 0.15 kcal/mol. The unfavorable effect of methylation was due to the steric overlap between the methyl group and a nitrogen atom in the purine ring. We then probed the effect of methylation in an RNA hairpin structure containing an AUCG tetraloop, which is recognized by a "reader" protein (YTHDC1) to promote transcriptional silencing of long noncoding RNAs. While methylation had no significant conformational effect on the hairpin stem, the methylated tetraloop showed enhanced conformational flexibility compared to the unmethylated tetraloop. The increased flexibility was associated with the outward flipping of two bases (A6 and U7) which formed stacking interactions with each other and with the C8 and G9 bases in the tetraloop, leading to a conformation similar to that in the RNA/reader protein complex. Therefore, methylation-induced conformational flexibility likely facilitates RNA recognition by the reader protein.

RNAapt3D: RNA aptamer 3D-structural modeling database

RNA aptamers are oligonucleotides with high binding affinity and specificity for target molecules and are expected to be a new generation of therapeutic molecules and targeted delivery materials. The tertiary structure of RNA molecules and RNA-protein interaction sites are increasingly important as potential targets for new drugs. The pathological mechanisms of diseases must be understood in detail to guide drug design. In developing RNA aptamers as drugs, information about the interaction mechanisms and structures of RNA aptamer-target protein complexes are useful. We constructed a database, RNA aptamer 3D-structural modeling (RNAapt3D), consisting of RNA aptamer data that are potential drug candidates. The database includes RNA sequences and computationally predicted RNA tertiary structures based on secondary structures and implements methods that can be used to predict unknown structures of RNA aptamer-target molecule complexes. RNAapt3D should enable the design of RNA aptamers for target molecules and improve the efficiency and productivity of candidate drug selection. RNAapt3D can be accessed at https://rnaapt3d.medals.jp.

Perspective: Path Sampling Methods Applied to Enzymatic Catalysis

This Perspective reviews the use of Transition Path Sampling methods to study enzymatically catalyzed chemical reactions. First applied by our group to an enzymatic reaction over 15 years ago, the method has uncovered basic principles in enzymatic catalysis such as the protein promoting vibration, and it has also helped harmonize such ideas as electrostatic preorganization with dynamic views of enzyme function. It is now being used to help uncover principles of protein design necessary to artificial enzyme creation.

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.

Gaussian Accelerated Molecular Dynamics in OpenMM

Gaussian accelerated molecular dynamics (GaMD) is a computational technique that provides both unconstrained enhanced sampling and free energy calculations of biomolecules. Here, we present the implementation of GaMD in the OpenMM simulation package and validate it on model systems of alanine dipeptide and RNA folding. For alanine dipeptide, 30 ns GaMD production simulations reproduced free energy profiles of 1000 ns conventional molecular dynamics (cMD) simulations. In addition, GaMD simulations captured the folding pathways of three hyperstable RNA tetraloops (UUCG, GCAA, and CUUG) and binding of the rbt203 ligand to the HIV-1 Tar RNA, both of which involved critical electrostatic interactions such as hydrogen bonding and base stacking. Together with previous implementations, GaMD in OpenMM will allow for wider applications in simulations of proteins, RNA, and other biomolecules.

Explaining reaction coordinates of alanine dipeptide isomerization obtained from deep neural networks using Explainable Artificial Intelligence (XAI)

A method for obtaining appropriate reaction coordinates is required to identify transition states distinguishing product and reactant in complex molecular systems. Recently, abundant research has been devoted to obtaining reaction coordinates using artificial neural networks from deep learning literature, where many collective variables are typically utilized in the input layer. However, it is difficult to explain the details of which collective variables contribute to the predicted reaction coordinates owing to the complexity of the nonlinear functions in deep neural networks. To overcome this limitation, we used Explainable Artificial Intelligence (XAI) methods of the Local Interpretable Model-agnostic Explanation (LIME) and the game theory-based framework known as Shapley Additive exPlanations (SHAP). We demonstrated that XAI enables us to obtain the degree of contribution of each collective variable to reaction coordinates that is determined by nonlinear regressions with deep learning for the committor of the alanine dipeptide isomerization in vacuum. In particular, both LIME and SHAP provide important features to the predicted reaction coordinates, which are characterized by appropriate dihedral angles consistent with those previously reported from the committor test analysis. The present study offers an AI-aided framework to explain the appropriate reaction coordinates, which acquires considerable significance when the number of degrees of freedom increases.

Nonlinear Reaction Coordinate of an Enzyme Catalyzed Proton Transfer Reaction

We present an in-depth study on the theoretical calculation of an optimum reaction coordinate as a linear or nonlinear combination of important collective variables (CVs) sampled from an ensemble of reactive transition paths for an intramolecular proton transfer reaction catalyzed by the enzyme human carbonic anhydrase (HCA) II. The linear models are optimized by likelihood maximization for a given number of CVs. The nonlinear models are based on an artificial neural network with the same number of CVs and optimized by minimizing the root-mean-square error in comparison to a training set of committor estimators generated for the given transition. The nonlinear reaction coordinate thus obtained yields the free energy of activation and rate constant as 9.46 kcal mol^-1 and 1.25 × 10⁶ s^-1, respectively. These estimates are found to be in quantitative agreement with the known experimental results. We have also used an extended autoencoder model to show that a similar analysis can be carried out using a single CV only. The resultant free energies and kinetics of the reaction slightly overestimate the experimental data. The implications of these results are discussed using a detailed microkinetic scheme of the proton transfer reaction catalyzed by HCA II.

Dynamics of 5R-Tg Base Flipping in DNA Duplexes Based on Simulations─Agreement with Experiments and Beyond

Damaged or mismatched DNA bases are normally thought to be able to flip out of the helical stack, providing enzymes with access to the faulty genetic information otherwise hidden inside the helix. Thymine glycol (Tg) is one of the most common products of nucleic acid damage. However, the static and dynamic structures of DNA duplexes affected by 5R-Tg epimers are still not clearly understood, including the ability of these to undergo spontaneous base flipping. Structural effects of the 5R-Tg epimers on the duplex DNA are herein studied using molecular dynamics together with reliable DFT based calculations. In comparison with the corresponding intact DNA, the cis-5R,6S-Tg epimer base causes little perturbation to the duplex DNA, and a barrier of 4.9 kcal mol^–1 is obtained by meta-eABF for cis-5R,6S-Tg base flipping out of the duplex DNA, comparable to the 5.4 kcal mol^–1 obtained for the corresponding thymine flipping in intact DNA. For the trans-5R,6R-Tg epimer, three stable local structures were identified, of which the most stable disrupts the Watson–Crick hydrogen-bonded G5/C20 base pair, leading to conformational distortion of the duplex. Interestingly, the relative barrier height of the 5R-Tg flipping is only 1.0 kcal mol^–1 for one of these trans-5R,6R-Tg epimers. Water bridge interactions were identified to be essential for 5R-Tg flipping. The study clearly demonstrates the occurrence of partial trans-5R,6R-Tg epimer flipping in solution.

Analysis of Charged Peptide Loop-Flipping across a Lipid Bilayer Using the String Method with Swarms of Trajectories

The hydrophobic core of the lipid bilayer is conventionally considered a barrier to the translocation of charged species such that the translocation of even single ions occurs on long time scales. In contrast, experiments have revealed that some materials, including peptides, proteins, and nanoparticles, can translocate multiple charged moieties across the bilayer on experimentally relevant time scales. Understanding the molecular mechanisms underlying this behavior is challenging because resolving corresponding free-energy landscapes with molecular simulation techniques is computationally expensive. To address this challenge, we use atomistic molecular dynamics simulations with the swarms-of-trajectories (SOT) string method to analyze charge translocation pathways across single-component lipid bilayers as a function of multiple collective variables. We first demonstrate that the SOT string method can reproduce the free-energy barrier for the translocation of a charged lysine amino acid analogue in good agreement with the literature. We then obtain minimum free-energy pathways for the translocation, or flipping, of charged peptide loops across the lipid bilayer by utilizing trajectories from prior temperature-accelerated molecular dynamics (TAMD) simulations as initial configurations. The corresponding potential of mean force calculations reveal that the protonation of a central membrane-exposed aspartate residue substantially reduces the free-energy barrier for flipping charged loops by modulating the water content of the bilayer. These results provide new insight into the thermodynamics underlying loop-flipping processes and highlight how the combination of TAMD and the SOT string method can be used to understand complex charge translocation mechanisms.