Catalytic mechanism of RNA backbone cleavage by ribonuclease H from quantum mechanics/molecular mechanics simulations

Electronic and Nuclear Quantum Effects on Proton Transfer Reactions of Guanine-Thymine (G-T) Mispairs Using Combined Quantum Mechanical/Molecular Mechanical and Machine Learning Potentials

Rare tautomeric forms of nucleobases can lead to Watson-Crick-like (WC-like) mispairs in DNA, but the process of proton transfer is fast and difficult to detect experimentally. NMR studies show evidence for the existence of short-time WC-like guanine-thymine (G-T) mispairs; however, the mechanism of proton transfer and the degree to which nuclear quantum effects play a role are unclear. We use a B-DNA helix exhibiting a wGT mispair as a model system to study tautomerization reactions. We perform ab initio (PBE0/6-31G*) quantum mechanical/molecular mechanical (QM/MM) simulations to examine the free energy surface for tautomerization. We demonstrate that while the ab initio QM/MM simulations are accurate, considerable sampling is required to achieve high precision in the free energy barriers. To address this problem, we develop a QM/MM machine learning potential correction (QM/MM-ΔMLP) that is able to improve the computational efficiency, greatly extend the accessible time scales of the simulations, and enable practical application of path integral molecular dynamics to examine nuclear quantum effects. We find that the inclusion of nuclear quantum effects has only a modest effect on the mechanistic pathway but leads to a considerable lowering of the free energy barrier for the GT*⇌G*T equilibrium. Our results enable a rationalization of observed experimental data and the prediction of populations of rare tautomeric forms of nucleobases and rates of their interconversion in B-DNA.

Encoding prior knowledge in ensemble refinement

The proper balancing of information from experiment and theory is a long-standing problem in the analysis of noisy and incomplete data. Viewed as a Pareto optimization problem, improved agreement with the experimental data comes at the expense of growing inconsistencies with the theoretical reference model. Here, we propose how to set the exchange rate a priori to properly balance this trade-off. We focus on gentle ensemble refinement, where the difference between the potential energy surfaces of the reference and refined models is small on a thermal scale. By relating the variance of this energy difference to the Kullback-Leibler divergence between the respective Boltzmann distributions, one can encode prior knowledge about energy uncertainties, i.e., force-field errors, in the exchange rate. The energy uncertainty is defined in the space of observables and depends on their type and number and on the thermodynamic state. We highlight the relation of gentle refinement to free energy perturbation theory. A balanced encoding of prior knowledge increases the quality and transparency of ensemble refinement. Our findings extend to non-Boltzmann distributions, where the uncertainty in energy becomes an uncertainty in information.

Elucidation of the catalytic mechanism of a single-metal dependent homing endonuclease using QM and QM/MM approaches: the case study of I-PpoI

Homing endonucleases (HEs) are highly specific DNA cleaving enzymes, with I-PpoI having been suggested to use a single metal to accelerate phosphodiester bond cleavage. Although an I-PpoI mechanism has been proposed based on experimental structural data, no consensus has been reached regarding the roles of the metal or key active site amino acids. This study uses QM cluster and QM/MM calculations to provide atomic-level details of the I-PpoI catalytic mechanism. Minimal QM cluster and large-scale QM/MM models demonstrate that the experimentally-proposed pathway involving direct Mg2+ coordination to the substrate coupled with leaving group protonation through a metal-activated water is not feasible due to an inconducive I-PpoI active site alignment. Despite QM cluster models of varying size uncovering a pathway involving leaving group protonation by a metal-activated water, indirect (water-mediated) metal coordination to the substrate is required to afford this pathway, which renders this mechanism energetically infeasible. Instead, QM cluster models reveal that the preferred pathway involves direct Mg2+-O3' coordination to stabilize the charged substrate and assist leaving group departure, while H98 activates the water nucleophile. These calculations also underscore that both catalytic residues that directly interact with the substrate and secondary amino acids that position or stabilize these residues are required for efficient catalysis. QM/MM calculations on the solvated enzyme-DNA complex verify the preferred mechanism, which is fully consistent with experimental kinetic, structural, and mutational data. The fundamental understanding of the I-PpoI mechanism of action, gained from the present work can be used to further explore potential uses of this enzyme in biotechnology and medicine, and direct future computational investigations of other members of the understudied HE family.

Surface-Accelerated String Method for Locating Minimum Free Energy Paths

We present a surface-accelerated string method (SASM) to efficiently optimize low-dimensional reaction pathways from the sampling performed with expensive quantum mechanical/molecular mechanical (QM/MM) Hamiltonians. The SASM accelerates the convergence of the path using the aggregate sampling obtained from the current and previous string iterations, whereas approaches like the string method in collective variables (SMCV) or the modified string method in collective variables (MSMCV) update the path only from the sampling obtained from the current iteration. Furthermore, the SASM decouples the number of images used to perform sampling from the number of synthetic images used to represent the path. The path is optimized on the current best estimate of the free energy surface obtained from all available sampling, and the proposed set of new simulations is not restricted to being located along the optimized path. Instead, the umbrella potential placement is chosen to extend the range of the free energy surface and improve the quality of the free energy estimates near the path. In this manner, the SASM is shown to improve the exploration for a minimum free energy pathway in regions where the free energy surface is relatively flat. Furthermore, it improves the quality of the free energy profile when the string is discretized with too few images. We compare the SASM, SMCV, and MSMCV using 3 QM/MM applications: a ribozyme methyltransferase reaction using 2 reaction coordinates, the 2'-O-transphosphorylation reaction of Hammerhead ribozyme using 3 reaction coordinates, and a tautomeric reaction in B-DNA using 5 reaction coordinates. We show that SASM converges the paths using roughly 3 times less sampling than the SMCV and MSMCV methods. All three algorithms have been implemented in the FE-ToolKit package made freely available.

Probing Nonadiabaticity of Proton-Coupled Electron Transfer in Ribonucleotide Reductase

The enzyme ribonucleotide reductase, which is essential for DNA synthesis, initiates the conversion of ribonucleotides to deoxyribonucleotides via radical transfer over a 32 Å pathway composed of proton-coupled electron transfer (PCET) reactions. Previously, the first three PCET reactions in the α subunit were investigated with hybrid quantum mechanical/molecular mechanical (QM/MM) free energy simulations. Herein, the fourth PCET reaction in this subunit between C439 and guanosine diphosphate (GDP) is simulated and found to be slightly exoergic with a relatively high free energy barrier. To further elucidate the mechanisms of all four PCET reactions, we analyzed the vibronic and electron-proton nonadiabaticities. This analysis suggests that interfacial PCET between Y356 and Y731 is vibronically and electronically nonadiabatic, whereas PCET between Y731 and Y730 and between C439 and GDP is fully adiabatic and PCET between Y730 and C439 is in the intermediate regime. These insights provide guidance for selecting suitable rate constant expressions for these PCET reactions.

Is Metal Stabilization of the Leaving Group Required or Can Lysine Facilitate Phosphodiester Bond Cleavage in Nucleic Acids? A Computational Study of EndoV

Endonuclease V (EndoV) is a single-metal-dependent enzyme that repairs deaminated DNA nucleobases in cells by cleaving the phosphodiester bond, and this enzyme has proven to be a powerful tool in biotechnology and medicine. The catalytic mechanism used by EndoV must be understood to design new disease detection and therapeutic solutions and further exploit the enzyme in interdisciplinary applications. This study has used a mixed molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) approach to compare eight distinct catalytic pathways and provides the first proposed mechanism for bacterial EndoV. The calculations demonstrate that mechanisms involving either direct or indirect metal coordination to the leaving group of the substrate previously proposed for other nucleases are unlikely for EndoV, regardless of the general base (histidine, aspartate, and substrate phosphate moiety). Instead, distinct catalytic pathways are characterized for EndoV that involve K139 stabilizing the leaving group, a metal-coordinated water stabilizing the transition structure, and either H214 or a substrate phosphate group activating the water nucleophile. In silico K139A and H214A mutational results support the newly proposed roles of these residues. Although this is a previously unseen combination of general base, general acid, and metal-binding architecture for a one-metal-dependent endonuclease, our proposed catalytic mechanisms are fully consistent with experimental kinetic, structural, and mutational data. In addition to substantiating a growing body of literature, suggesting that one metal is enough to catalyze P-O bond cleavage in nucleic acids, this new fundamental understanding of the catalytic function will promote the exploration of new and improved applications of EndoV.

Minimum Free Energy Pathways of Reactive Processes with Nudged Elastic Bands

The determination of minimum free energy pathways (MFEP) is one of the most widely used strategies to study reactive processes. For chemical reactions in complex environments, the combination of quantum mechanics (QM) with a molecular mechanics (MM) representation is usually necessary in a hybrid QM/MM framework. However, even within the QM/MM approximation, the affordable sampling of the phase space is, in general, quite restricted. To reduce drastically the computational cost of the simulations, several methods such as umbrella sampling require performing a priori a selection of a reaction coordinate. The quality of the computed results, in an affordable computational time, is intimately related to the reaction coordinate election which is, in general, a nontrivial task. In this work, we provide an approach to model reactive processes in complex environments that does not require the a priori selection of a reaction coordinate. The proposed methodology combines QM/MM simulations with an extrapolation of the nudged elastic bands (NEB) method to the free energy surface (FENEB). We present and apply our own FENEB scheme to optimize MFEP in different reactive processes, using QM/MM frameworks at semiempirical and density functional theory levels. Our implementation is based on performing the FENEB optimization by uncoupling the optimization of the band in a perpendicular and tangential direction. In each step, a full optimization with the spring force is performed, which guarantees that the images remain evenly distributed. The robustness of the method and the influence of sampling on the quality of the optimized MFEP and its associated free energy barrier are studied. We show that the FENEB method provides a good estimation of the reaction barrier even with relatively short simulation times, supporting that its combination with QM/MM frameworks provides an adequate tool to study chemical processes in complex environments.

Investigating the Unbinding of Muscarinic Antagonists from the Muscarinic 3 Receptor

Patient symptom relief is often heavily influenced by the residence time of the inhibitor-target complex. For the human muscarinic receptor 3 (hMR3), tiotropium is a long-acting bronchodilator used in conditions such as asthma or chronic obstructive pulmonary disease (COPD). The mechanistic insights into this inhibitor remain unclear; specifically, the elucidation of the main factors determining the unbinding rates could help develop the next generation of antimuscarinic agents. Using our novel unbinding algorithm, we were able to investigate ligand dissociation from hMR3. The unbinding paths of tiotropium and two of its analogues, N-methylscopolamin and homatropine methylbromide, show a consistent qualitative mechanism and allow us to identify the structural bottleneck of the process. Furthermore, our machine learning-based analysis identified key roles of the ECL2/TM5 junction involved in the transition state. Additionally, our results point to relevant changes at the intracellular end of the TM6 helix leading to the ICL3 kinase domain, highlighting the closest residue L482. This residue is located right between two main protein binding sites involved in signal transduction for hMR3's activation and regulation. We also highlight key pharmacophores of tiotropium that play determining roles in the unbinding kinetics and could aid toward drug design and lead optimization.

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.

Exploring Proton-Coupled Electron Transfer at Multiple Scales

The coupling of electron and proton transfer is critical for chemical and biological processes spanning a wide range of length and time scales and often occurring in complex environments. Thus, diverse modeling strategies, including analytical theories, quantum chemistry, molecular dynamics, and kinetic modeling, are essential for a comprehensive understanding of such proton-coupled electron transfer reactions. Each of these computational methods provides one piece of the puzzle, and all these pieces must be viewed together to produce the full picture.

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.

Direct Proton-Coupled Electron Transfer between Interfacial Tyrosines in Ribonucleotide Reductase

Ribonucleotide reductase (RNR) regulates DNA synthesis and repair in all organisms. The mechanism of Escherichia coli RNR requires radical transfer over a proton-coupled electron transfer (PCET) pathway spanning ∼32 Å across two protein subunits. A key step along this pathway is the interfacial PCET reaction between Y356 in the β subunit and Y731 in the α subunit. Herein, this PCET reaction between two tyrosines across an aqueous interface is explored with classical molecular dynamics and quantum mechanical/molecular mechanical (QM/MM) free energy simulations. The simulations suggest that the water-mediated mechanism involving double proton transfer through an intervening water molecule is thermodynamically and kinetically unfavorable. The direct PCET mechanism between Y356 and Y731 becomes feasible when Y731 is flipped toward the interface and is predicted to be approximately isoergic with a relatively low free energy barrier. This direct mechanism is facilitated by the hydrogen bonding of water to both Y356 and Y731. These simulations provide fundamental insights into radical transfer across aqueous interfaces.

Distal Mutations in the β-Clamp of DNA Polymerase III* Disrupt DNA Orientation and Affect Exonuclease Activity

DNA polymerases are responsible for the replication and repair of DNA found in all DNA-based organisms. DNA Polymerase III is the main replicative polymerase of E. coli and is composed of over 10 proteins. A subset of these proteins (Pol III*) includes the polymerase (α), exonuclease (ϵ), clamp (β), and accessory protein (θ). Mutations of residues in, or around the active site of the catalytic subunits (α and ϵ), can have a significant impact on catalysis. However, the effects of distal mutations in noncatalytic subunits on the activity of catalytic subunits are less well-characterized. Here, we investigate the effects of two Pol III* variants, β-L82E/L82'E and β-L82D/L82'D, on the proofreading reaction catalyzed by ϵ. MD simulations reveal major changes in the dynamics of Pol III*, which extend throughout the complex. These changes are mostly induced by a shift in the position of the DNA substrate inside the β-clamp, although no major structural changes are observed in the protein complex. Quantum mechanics/molecular mechanics (QM/MM) calculations indicate that the β-L82D/L82'D variant has reduced catalytic proficiency due to highly endoergic reaction energies resulting from structural changes in the active site and differences in the electric field at the active site arising from the protein and substrate. Conversely, the β-L82E/L82'E variant is predicted to maintain proofreading activity, exhibiting a similar reaction barrier for nucleotide excision compared with the WT system. However, significant differences in the reaction mechanism are obtained due to the changes induced by the mutations on the β-clamp.

Modeling Ensembles of Enzyme Reaction Pathways with Hi-MSM Reveals the Importance of Accounting for Pathway Diversity

Conventional quantum mechanical-molecular mechanics (QM/MM) simulation approaches for modeling enzyme reactions often assume that there is one dominant reaction pathway and that this pathway can be sampled starting from an X-ray structure of the enzyme. These assumptions reduce computational cost; however, their validity has not been extensively tested. This is due in part to the lack of a rigorous formalism for integrating disparate pathway information from dynamical QM/MM calculations. Here, we present a way to model ensembles of reaction pathways efficiently using a divide-and-conquer strategy through Hierarchical Markov State Modeling (Hi-MSM). This approach allows information on multiple, distinct pathways to be incorporated into a chemical kinetic model, and it allows us to test these two assumptions. Applying Hi-MSM to the reaction carried out by dihydrofolate reductase (DHFR) we find (i) there are multiple, distinct pathways significantly contributing to the overall flux of the reaction that the conventional approach does not identify and (ii) that the conventional approach does not identify the dominant reaction pathway. Thus, both assumptions underpinning the conventional approach are violated. Since DHFR is a relatively small enzyme, and configuration space scales exponentially with protein size, accounting for multiple reaction pathways is likely to be necessary for most enzymes.

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

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

Accelerating Ab Initio Quantum Mechanical and Molecular Mechanical (QM/MM) Molecular Dynamics Simulations with Multiple Time Step Integration and a Recalibrated Semiempirical QM/MM Hamiltonian

Molecular dynamics (MD) simulations employing ab initio quantum mechanical and molecular mechanical (ai-QM/MM) potentials are considered to be the state of the art, but the high computational cost associated with the ai-QM calculations remains a theoretical challenge for their routine application. Here, we present a modified protocol of the multiple time step (MTS) method for accelerating ai-QM/MM MD simulations of condensed-phase reactions. Within a previous MTS protocol [Nam J. Chem. Theory Comput. 2014, 10, 4175], reference forces are evaluated using a low-level (semiempirical QM/MM) Hamiltonian and employed at inner time steps to propagate the nuclear motions. Correction forces, which arise from the force differences between high-level (ai-QM/MM) and low-level Hamiltonians, are applied at outer time steps, where the MTS algorithm allows the time-reversible integration of the correction forces. To increase the outer step size, which is bound by the highest-frequency component in the correction forces, the semiempirical QM Hamiltonian is recalibrated in this work to minimize the magnitude of the correction forces. The remaining high-frequency modes, which are mainly bond stretches involving hydrogen atoms, are then removed from the correction forces. When combined with a Langevin or SIN(R) thermostat, the modified MTS-QM/MM scheme remains robust with an up to 8 (with Langevin) or 10 fs (with SIN(R)) outer time step (with 1 fs inner time steps) for the chorismate mutase system. This leads to an over 5-fold speedup over standard ai-QM/MM simulations, without sacrificing the accuracy in the predicted free energy profile of the reaction.

Role of Water in Proton-Coupled Electron Transfer between Tyrosine and Cysteine in Ribonucleotide Reductase

Ribonucleotide reductase (RNR) catalyzes the reduction of ribonucleotides to deoxyribonucleotides and is critical for DNA synthesis and repair in all organisms. Its mechanism requires radical transfer along a ∼32 Å pathway through a series of proton-coupled electron transfer (PCET) steps. Previous simulations suggested that a glutamate residue (E623) mediates the PCET reaction between two stacked tyrosine residues (Y730 and Y731) through a proton relay mechanism. This work focuses on the adjacent PCET reaction between Y730 and a cysteine residue (C439). Quantum mechanical/molecular mechanical free energy simulations illustrate that when Y730 and Y731 are stacked, E623 stabilizes the radical on C439 through hydrogen bonding with the Y730 hydroxyl group. When Y731 is flipped away from Y730, a water molecule stabilizes the radical on C439 through hydrogen bonding with Y730 and lowers the free energy barrier for radical transfer from Y730 to C439 through electrostatic interactions with the transferring hydrogen but does not directly accept the proton. These simulations indicate that the conformational motions and electrostatic interactions of the tyrosines, cysteine, glutamate, and water strongly impact the thermodynamics and kinetics of these two coupled PCET reactions. Such insights are important for protein engineering efforts aimed at altering radical transfer in RNR.

Combined Free-Energy Calculation and Machine Learning Methods for Understanding Ligand Unbinding Kinetics

The determination of drug residence times, which define the time an inhibitor is in complex with its target, is a fundamental part of the drug discovery process. Synthesis and experimental measurements of kinetic rate constants are, however, expensive and time consuming. In this work, we aimed to obtain drug residence times computationally. Furthermore, we propose a novel algorithm to identify molecular design objectives based on ligand unbinding kinetics. We designed an enhanced sampling technique to accurately predict the free-energy profiles of the ligand unbinding process, focusing on the free-energy barrier for unbinding. Our method first identifies unbinding paths determining a corresponding set of internal coordinates (ICs) that form contacts between the protein and the ligand; it then iteratively updates these interactions during a series of biased molecular dynamics (MD) simulations to reveal the ICs that are important for the whole of the unbinding process. Subsequently, we performed finite-temperature string simulations to obtain the free-energy barrier for unbinding using the set of ICs as a complex reaction coordinate. Importantly, we also aimed to enable the further design of drugs focusing on improved residence times. To this end, we developed a supervised machine learning (ML) approach with inputs from unbiased “downhill” trajectories initiated near the transition state (TS) ensemble of the string unbinding path. We demonstrate that our ML method can identify key ligand–protein interactions driving the system through the TS. Some of the most important drugs for cancer treatment are kinase inhibitors. One of these kinase targets is cyclin-dependent kinase 2 (CDK2), an appealing target for anticancer drug development. Here, we tested our method using two different CDK2 inhibitors for the potential further development of these compounds. We compared the free-energy barriers obtained from our calculations with those observed in available experimental data. We highlighted important interactions at the distal ends of the ligands that can be targeted for improved residence times. Our method provides a new tool to determine unbinding rates and to identify key structural features of the inhibitors that can be used as starting points for novel design strategies in drug discovery.

Machine-Learning-Assisted Free Energy Simulation of Solution-Phase and Enzyme Reactions

Despite recent advances in the development of machine learning potentials (MLPs) for biomolecular simulations, there has been limited effort on developing stable and accurate MLPs for enzymatic reactions. Here we report a protocol for performing machine-learning-assisted free energy simulation of solution-phase and enzyme reactions at the ab initio quantum-mechanical/molecular-mechanical (ai-QM/MM) level of accuracy. Within our protocol, the MLP is built to reproduce the ai-QM/MM energy and forces on both QM (reactive) and MM (solvent/enzyme) atoms. As an alternative strategy, a delta machine learning potential (ΔMLP) is trained to reproduce the differences between the ai-QM/MM and semiempirical (se) QM/MM energies and forces. To account for the effect of the condensed-phase environment in both MLP and ΔMLP, the DeePMD representation of a molecular system is extended to incorporate the external electrostatic potential and field on each QM atom. Using the Menshutkin and chorismate mutase reactions as examples, we show that the developed MLP and ΔMLP reproduce the ai-QM/MM energy and forces with errors that on average are less than 1.0 kcal/mol and 1.0 kcal mol^-1 Å^-1, respectively, for representative configurations along the reaction pathway. For both reactions, MLP/ΔMLP-based simulations yielded free energy profiles that differed by less than 1.0 kcal/mol from the reference ai-QM/MM results at only a fraction of the computational cost.

Controlled Trafficking of Multiple and Diverse Cations Prompts Nucleic Acid Hydrolysis

Recent in crystallo reaction intermediates have detailed how nucleic acid hydrolysis occurs in the RNA ribonuclease H1 (RNase H1), a fundamental metalloenzyme involved in maintaining the human genome. At odds with the previous characterization, these in crystallo structures unexpectedly captured multiple metal ions (K⁺ and Mg²⁺) transiently bound in the vicinity of the two-metal-ion active site. Using multi-microsecond all-atom molecular dynamics and free-energy simulations, we investigated the functional implications of the dynamic exchange of multiple K⁺ and Mg²⁺ ions at the RNase H1 reaction center. We found that such ions are timely positioned at non-overlapping locations near the active site, at different stages of catalysis, being crucial for both reactants' alignment and leaving group departure. We also found that this cation trafficking is tightly regulated by variations of the solution's ionic strength and is aided by two conserved second-shell residues, E188 and K196, suggesting a mechanism for the cations' recruitment during catalysis. These results indicate that controlled trafficking of multi-cation dynamics, opportunely prompted by second-shell residues, is functionally essential to the complex enzymatic machinery of the RNase H1. These findings revise the current knowledge on the RNase H1 catalysis and open new catalytic possibilities for other similar metalloenzymes including, but not limited to, CRISPR-Cas9, group II intron ribozyme and the human spliceosome.

Extension of the Variational Free Energy Profile and Multistate Bennett Acceptance Ratio Methods for High-Dimensional Potential of Mean Force Profile Analysis

We redevelop the variational free energy profile (vFEP) method using a cardinal B-spline basis to extend the method for analyzing free energy surfaces (FESs) involving three or more reaction coordinates. We also implemented software for evaluating high-dimensional profiles based on the multistate Bennett acceptance ratio (MBAR) method which constructs an unbiased probability density from global reweighting of the observed samples. The MBAR method takes advantage of a fast algorithm for solving the unbinned weighted histogram (UWHAM)/MBAR equations which replaces the solution of simultaneous equations with a nonlinear optimization of a convex function. We make use of cardinal B-splines and multiquadric radial basis functions to obtain smooth, differentiable MBAR profiles in arbitrary high dimensions. The cardinal B-spline vFEP and MBAR methods are compared using three example systems that examine 1D, 2D, and 3D profiles. Both methods are found to be useful and produce nearly indistinguishable results. The vFEP method is found to be 150 times faster than MBAR when applied to periodic 2D profiles, but the MBAR method is 4.5 times faster than vFEP when evaluating unbounded 3D profiles. In agreement with previous comparisons, we find the vFEP method produces superior FESs when the overlap between umbrella window simulations decreases. Finally, the associative reaction mechanism of hammerhead ribozyme is characterized using 3D, 4D, and 6D profiles, and the higher-dimensional profiles are found to have smaller reaction barriers by as much as 1.5 kcal/mol. The methods presented here have been implemented into the FE-ToolKit software package along with new methods for network-wide free energy analysis in drug discovery.

Exploring the Minimum-Energy Pathways and Free-Energy Profiles of Enzymatic Reactions with QM/MM Calculations

Understanding molecular mechanisms of enzymatic reactions is of vital importance in biochemistry and biophysics. Here, we introduce new functions of hybrid quantum mechanical/molecular mechanical (QM/MM) calculations in the GENESIS program to compute the minimum-energy pathways (MEPs) and free-energy profiles of enzymatic reactions. For this purpose, an interface in GENESIS is developed to utilize a highly parallel electronic structure program, QSimulate-QM (https://qsimulate.com), calling it as a shared library from GENESIS. Second, algorithms to search the MEP are implemented, combining the string method (E et al. J. Chem. Phys. 2007, 126, 164103) with the energy minimization of the buffer MM region. The method implemented in GENESIS is applied to an enzyme, triosephosphate isomerase, which converts dihyroxyacetone phosphate to glyceraldehyde 3-phosphate in four proton-transfer processes. QM/MM-molecular dynamics simulations show performances of greater than 1 ns/day with the density functional tight binding (DFTB), and 10-30 ps/day with the hybrid density functional theory, B3LYP-D3. These performances allow us to compute not only MEP but also the potential of mean force (PMF) of the enzymatic reactions using the QM/MM calculations. The barrier height obtained as 13 kcal mol-1 with B3LYP-D3 in the QM/MM calculation is in agreement with the experimental results. The impact of conformational sampling in PMF calculations and the level of electronic structure calculations (DFTB vs B3LYP-D3) suggests reliable computational protocols for enzymatic reactions without high computational costs.

Establishing the allosteric mechanism in CRISPR-Cas9

Allostery is a fundamental property of proteins, which regulates biochemical information transfer between spatially distant sites. Here, we report on the critical role of molecular dynamics (MD) simulations in discovering the mechanism of allosteric communication within CRISPR-Cas9, a leading genome editing machinery with enormous promises for medicine and biotechnology. MD revealed how allostery intervenes during at least three steps of the CRISPR-Cas9 function: affecting DNA recognition, mediating the cleavage and interfering with the off-target activity. An allosteric communication that activates concerted DNA cleavages was found to led through the L1/L2 loops, which connect the HNH and RuvC catalytic domains. The identification of these "allosteric transducers" inspired the development of novel variants of the Cas9 protein with improved specificity, opening a new avenue for controlling the CRISPR-Cas9 activity. Discussed studies also highlight the critical role of the recognition lobe in the conformational activation of the catalytic HNH domain. Specifically, the REC3 region was found to modulate the dynamics of HNH by sensing the formation of the RNA:DNA hybrid. The role of REC3 was revealed to be particularly relevant in the presence of DNA mismatches. Indeed, interference of REC3 with the RNA:DNA hybrid containing mismatched pairs at specific positions resulted in locking HNH in an inactive "conformational checkpoint" conformation, thereby hampering off-target cleavages. Overall, MD simulations established the fundamental mechanisms underlying the allosterism of CRISPR-Cas9, aiding engineering strategies to develop new CRISPR-Cas9 variants for improved genome editing.

Identification of the ternary complex of ribonuclease HI:RNA/DNA hybrid:metal ions by ESI mass spectrometry

Ribonuclease HI, an endoribonuclease, catalyzes the hydrolysis of the RNA strand of an RNA/DNA hybrid and requires divalent metal ions for its enzymatic activity. However, the mechanistic details of the activity of ribonuclease HI and its interaction with divalent metal ions remain unclear. In this study, we performed real-time monitoring of the enzyme–substrate complex in the presence of divalent metal ions (Mn²⁺ or Zn²⁺) using electrospray ionization–mass spectrometry (ESI-MS). The findings provide clear evidence that the enzymatic activity of the ternary complex requires the binding of two divalent metal ions. The Zn²⁺ ions bind to both the enzyme itself and the enzyme:substrate complex more strongly than Mn²⁺ ions, and gives, in part, the ternary complex, [RNase HI:nicked RNA/DNA hybrid:2Zn²⁺], suggesting that the ternary complex is retained, even after the hydrolysis of the substrate. The collective results presented herein shed new light on the essential role of divalent metal ions in the activity of ribonuclease HI and demonstrate how Zn²⁺ ions confer inhibitory properties on the activity of this enzyme by forming a highly stable complex with the substrate.

Investigating the folding mechanism of the N-terminal domain of ribosomal protein L9

Protein folding is a popular topic in the life science. However, due to the limited sampling ability of experiments and simulations, the general folding mechanism is not yet clear to us. In this work, we study the folding of the N-terminal domain of ribosomal protein L9 (NTL9) in detail by a mixing replica exchange molecular dynamics method. The simulation results are close to previous experimental observations. According to the Markov state model, the folding of the protein follows a nucleation-condensation path. Moreover, after the comparison to its 39-residue β-α-β motif, we find that the helix at the C-terminal has a great influence on the folding process of the intact protein, including the nucleation of the key residues in the transition state ensemble and the packing of the hydrophobic residues in the native state.

Biomolecular QM/MM Simulations: What Are Some of the "Burning Issues"?

QM/MM simulations have become an indispensable tool in many chemical and biochemical investigations. Considering the tremendous degree of success, including recognition by a 2013 Nobel Prize in Chemistry, are there still "burning challenges" in QM/MM methods, especially for biomolecular systems? In this short Perspective, we discuss several issues that we believe greatly impact the robustness and quantitative applicability of QM/MM simulations to many, if not all, biomolecules. We highlight these issues with observations and relevant advances from recent studies in our group and others in the field. Despite such limited scope, we hope the discussions are of general interest and will stimulate additional developments that help push the field forward in meaningful directions.

What Does the Brønsted Slope Measure in the Phosphoryl Transfer Transition State?

The structural and energetic features of phosphate and phosphonate hydrolysis in Protein Phosphatase-1 (PP1) and water are studied using quantum mechanical (QM) cluster models. The calculations are able to reproduce observed kinetic isotope effects and capture several key trends in the experimental Brønsted plots: the β l g values are rather different for phosphate and phosphonate ester hydrolysis in solution but are similar in PP1. Detailed analyses of structure, charge distribution and bond order of computed transition states support the general conclusion from experimental study that phosphoryl transfer transition states are different for the two classes of substrates in solution but similar in PP1. On the other hand, the microscopic models also highlight notable differences between the phosphate and phosphonate transition states, which are manifested in not only structure but also kinetic isotope effects. Overall, we find that while β l g / β E Q , l g generally correlates with the partial charge on leaving group oxygen and the fractional bond order of the breaking P- O l g bond, the precise mapping between β l g / β E Q , l g and P- O l g bond order in the transition state is difficult due largely to the cross talk between breaking and forming P-O bonds. Therefore, further supporting previous analyses of limitations of free energy relations, our results suggest that while free energy relation is a valuable tool for probing the nature of transition state, a quantitative mapping of β l g and β l g / β E Q , l g values to structure or charge in the transition state should be conducted with great care.

Catalytic Mechanism of Non-Target DNA Cleavage in CRISPR-Cas9 Revealed by Ab Initio Molecular Dynamics

CRISPR-Cas9 is a cutting-edge genome editing technology, which uses the endonuclease Cas9 to introduce mutations at desired sites of the genome. This revolutionary tool is promising to treat a myriad of human genetic diseases. Nevertheless, the molecular basis of DNA cleavage, which is a fundamental step for genome editing, has not been established. Here, quantum-classical molecular dynamics (MD) and free energy methods are used to disclose the two-metal-dependent mechanism of phosphodiester bond cleavage in CRISPR-Cas9. Ab initio MD reveals a conformational rearrangement of the Mg2+-bound RuvC active site, which entails the relocation of H983 to act as a general base. Then, the DNA cleavage proceeds through a concerted associative pathway fundamentally assisted by the joint dynamics of the two Mg2+ ions. This clarifies previous controversial experimental evidence, which could not fully establish the catalytic role of the conserved H983 and the metal cluster conformation. The comparison with other two-metal-dependent enzymes supports the identified mechanism and suggests a common catalytic strategy for genome editing and recombination. Overall, the non-target DNA cleavage catalysis described here resolves a fundamental open question in the CRISPR-Cas9 biology and provides valuable insights for improving the catalytic efficiency and the metal-dependent function of the Cas9 enzyme, which are at the basis of the development of genome editing tools.

Intact RNA structurome reveals mRNA structure-mediated regulation of miRNA cleavage in vivo

MicroRNA (miRNA)-mediated cleavage is involved in numerous essential cellular pathways. miRNAs recognize target RNAs via sequence complementarity. In addition to complementarity, in vitro and in silico studies have suggested that RNA structure may influence the accessibility of mRNAs to miRNA-induced silencing complexes (miRISCs), thereby affecting RNA silencing. However, the regulatory mechanism of mRNA structure in miRNA cleavage remains elusive. We investigated the role of in vivo RNA secondary structure in miRNA cleavage by developing the new CAP-STRUCTURE-seq method to capture the intact mRNA structurome in Arabidopsis thaliana. This approach revealed that miRNA target sites were not structurally accessible for miRISC binding prior to cleavage in vivo. Instead, we found that the unfolding of the target site structure plays a key role in miRISC activity in vivo. We found that the single-strandedness of the two nucleotides immediately downstream of the target site, named Target Adjacent nucleotide Motif, can promote miRNA cleavage but not miRNA binding, thus decoupling target site binding from cleavage. Our findings demonstrate that mRNA structure in vivo can modulate miRNA cleavage, providing evidence of mRNA structure-dependent regulation of biological processes.

Environmental Effects on Guanine-Thymine Mispair Tautomerization Explored with Quantum Mechanical/Molecular Mechanical Free Energy Simulations

DNA bases can adopt energetically unfavorable tautomeric forms that enable the formation of Watson-Crick-like (WC-like) mispairs, which have been proposed to give rise to spontaneous mutations in DNA and misincorporation errors in DNA replication and translation. Previous NMR and computational studies have indicated that the population of WC-like guanine-thymine (G-T) mispairs depends on the environment, such as the local nucleic acid sequence and solvation. To investigate these environmental effects, herein G-T mispair tautomerization processes are studied computationally in aqueous solution, in A-form and B-form DNA duplexes, and within the active site of a DNA polymerase λ variant. The wobble G-T (wG-T), WC-like G-T*, and WC-like G*-T forms are considered, where * indicates the enol tautomer of the base. The minimum free energy paths for the tautomerization from the wG-T to the WC-like G-T* and from the WC-like G-T* to the WC-like G*-T are computed with mixed quantum mechanical/molecular mechanical (QM/MM) free energy simulations. The reaction free energies and free energy barriers are found to be significantly influenced by the environment. The wG-T→G-T* tautomerization is predicted to be endoergic in aqueous solution and the DNA duplexes but slightly exoergic in the polymerase, with Arg517 and Asn513 providing electrostatic stabilization of G-T*. The G-T*→G*-T tautomerization is also predicted to be slightly more thermodynamically favorable in the polymerase relative to these DNA duplexes. These simulations are consistent with an experimentally driven kinetic misincorporation model suggesting that G-T mispair tautomerization occurs in the ajar polymerase conformation or concertedly with the transition from the ajar to the closed polymerase conformation. Furthermore, the order of the associated two proton transfer reactions is predicted to be different in the polymerase than in aqueous solution and the DNA duplexes. These studies highlight the impact of the environment on the thermodynamics, kinetics, and fundamental mechanisms of G-T mispair tautomerization, which plays a role in a wide range of biochemically important processes.

Quantifying Protein-Protein Interactions in Molecular Simulations

Interactions among proteins, nucleic acids, and other macromolecules are essential for their biological functions and shape the physicochemcial properties of the crowded environments inside living cells. Binding interactions are commonly quantified by dissociation constants K_d, and both binding and nonbinding interactions are quantified by second osmotic virial coefficients B₂. As a measure of nonspecific binding and stickiness, B₂ is receiving renewed attention in the context of so-called liquid–liquid phase separation in protein and nucleic acid solutions. We show that K_d is fully determined by B₂ and the fraction of the dimer observed in molecular simulations of two proteins in a box. We derive two methods to calculate B₂. From molecular dynamics or Monte Carlo simulations using implicit solvents, we can determine B₂ from insertion and removal energies by applying Bennett’s acceptance ratio (BAR) method or the (binless) weighted histogram analysis method (WHAM). From simulations using implicit or explicit solvents, one can estimate B₂ from the probability that the two molecules are within a volume large enough to cover their range of interactions. We validate these methods for coarse-grained Monte Carlo simulations of three weakly binding proteins. Our estimates for K_d and B₂ allow us to separate out the contributions of nonbinding interactions to B₂. Comparison of calculated and measured values of K_d and B₂ can be used to (re-)parameterize and improve molecular force fields by calibrating specific affinities, overall stickiness, and nonbinding interactions. The accuracy and efficiency of K_d and B₂ calculations make them well suited for high-throughput studies of large interactomes.

Cations in motion: QM/MM studies of the dynamic and electrostatic roles of H+ and Mg2+ ions in enzyme reactions

Here we discuss current trends in the simulations of enzymatic reactions focusing on phosphate catalysis. The mechanistic details of the proton transfers coupled to the phosphate cleavage is one of the key challenges in QM/MM calculations of these and other enzyme catalyzed reactions. The lack of experimental information offers both an opportunity for computations as well as often unresolved controversies. We discuss the example of small GTPases including the important human Ras protein. The high dimensionality and chemical complexity of these reactions demand carefully chosen computational techniques both in terms of the underlying quantum chemical theory and the sampling of the conformational ensemble. We also point out the important role of Mg²⁺ ions, and recent advances in their transient involvement in the catalytic mechanisms.

Examining the Mechanism of Phosphite Dehydrogenase with Quantum Mechanical/Molecular Mechanical Free Energy Simulations

The projected decline of available phosphorus necessitates alternative methods to derive usable phosphate for fertilizer and other applications. Phosphite dehydrogenase oxidizes phosphite to phosphate with the cofactor NAD⁺ serving as the hydride acceptor. In addition to producing phosphate, this enzyme plays an important role in NADH cofactor regeneration processes. Mixed quantum mechanical/molecular mechanical free energy simulations were performed to elucidate the mechanism of this enzyme and to identify the protonation states of the substrate and product. Specifically, the finite temperature string method with umbrella sampling was used to generate the free energy surfaces and determine the minimum free energy paths for six different initial conditions that varied in the protonation state of the substrate and the position of the nucleophilic water molecule. In contrast to previous studies, the mechanism predicted by all six independent strings is a concerted but asynchronous dissociative mechanism in which hydride transfer from the phosphite substrate to NAD⁺ occurs prior to attack by the nucleophilic water molecule. His292 is identified as the most likely general base that deprotonates the attacking water molecule. However, Arg237 could also serve as this base if it were deprotonated and His292 were protonated prior to the main chemical transformation, although this scenario is less probable. The simulations indicate that the phosphite substrate is monoanionic in its active form and that the most likely product is dihydrogen phosphate. These mechanistic insights may be helpful for designing mutant enzymes or artificial constructs that convert phosphite to phosphate and NAD⁺ to NADH more effectively.

Study of the role of Mg2+ in dsRNA processing mechanism by bacterial RNase III through QM/MM simulations

The ribonuclease III (RNase III) cleaves dsRNA in specific positions generating mature RNAs. RNase III enzymes play important roles in RNA processing, post-transcriptional gene expression, and defense against viral infection. The enzyme's active site contains Mg²⁺ ions bound by a network of acidic residues and water molecules, but there is a lack of information about their specific roles. In this work, multiple steered molecular dynamics simulations at QM/MM level were performed to explore the hydrolysis reaction carried out by the enzyme. Free energy profiles modifying the features of the active site are obtained and the role of Mg²⁺ ions, the solvent molecules and the residues of the active site are discussed in detail. Our results show that Mg²⁺ ions carry out different roles in the hydrolysis process positioning the substrate for the attack from a coordinated nucleophile and activating it to perform hydrolysis reaction, cleaving the dsRNA backbone in a S_N2 substitution. In addition, water molecules present in the active site lower the energy barrier of the process. RNase III hydrolyzes dsRNA to generate mature RNAs. For this purpose, its active site contains Mg²⁺ which has an important role during the reaction. Results show that the Mg²⁺ activates the solvent molecule that produces the nucleophilic attack and the surrounding waters contribute significantly to the hydrolysis process.

Accelerated computation of free energy profile at ab initio quantum mechanical/molecular mechanical accuracy via a semi-empirical reference potential. II. Recalibrating semi-empirical parameters with force matching

An efficient and accurate reference potential simulation protocol is proposed for producing ab initio quantum mechanical/molecular mechanical (AI-QM/MM) quality free energy profiles for chemical reactions in a solvent or macromolecular environment. This protocol involves three stages: (a) using force matching to recalibrate a semi-empirical quantum mechanical (SE-QM) Hamiltonian for the specific reaction under study; (b) employing the recalibrated SE-QM Hamiltonian (in combination with molecular mechanical force fields) as the reference potential to drive umbrella samplings along the reaction pathway; and (c) computing AI-QM/MM energy values for collected configurations from the sampling and performing weighted thermodynamic perturbation to acquire an AI-QM/MM corrected reaction free energy profile. For three model reactions (identity SN2 reaction, Menshutkin reaction, and glycine proton transfer reaction) in aqueous solution and one enzyme reaction (Claisen arrangement in chorismate mutase), our simulations using recalibrated PM3 SE-QM Hamiltonians well reproduced QM/MM free energy profiles at the B3LYP/6-31G* level of theory all within 1 kcal mol-1 with a 20 to 45 fold reduction in the computer time.

Combining the biased and unbiased sampling strategy into one convenient free energy calculation method

Constructing a free energy landscape for a large molecule is difficult. One has to use either a high temperature or a strong driving force to enhance the sampling on the free energy barriers. In this work, we propose a mixed method that combines these two kinds of acceleration strategies into one simulation. First, it applies an adaptive biasing potential to some replicas of the molecule. These replicas are particularly accelerated in a collective variable space. Second, it places some unbiased and exchangeable replicas at various temperature levels. These replicas generate unbiased sampling data in the canonical ensemble. To improve the sampling efficiency, biased replicas transfer their state variables to the unbiased replicas after equilibrium by Monte Carlo trial moves. In comparison to previous integrated methods, it is more convenient for users. It does not need an initial reference biasing potential to guide the sampling of the molecule. And it is also unnecessary to insert many replicas for the requirement of passing the free energy barriers. The free energy calculation is accomplished in a single stage. It samples the data as fast as a biased simulation and it processes the data as simple as an unbiased simulation. The method provides a minimalist approach to the construction of the free energy landscape. © 2019 Wiley Periodicals, Inc.

RNases H: Structure and mechanism

RNases H are a family of endonucleases that hydrolyze RNA residues in various nucleic acids. These enzymes are present in all branches of life, and their counterpart domains are also found in reverse transcriptases (RTs) from retroviruses and retroelements. RNases H are divided into two main classes (RNases H1 and H2 or type 1 and type 2 enzymes) with common structural features of the catalytic domain but different range of substrates for enzymatic cleavage. Additionally, a third class is found in some Archaea and bacteria. Besides distinct cellular functions specific for each type of RNases H, this family of proteins is generally involved in the maintenance of genome stability with overlapping and cooperative role in removal of R-loops thus preventing their accumulation. Extensive biochemical and structural studies of RNases H provided not only a comprehensive and complete picture of their mechanism but also revealed key basic principles of nucleic acid recognition and processing. RNase H1 is present in prokaryotes and eukaryotes and cleaves RNA in RNA/DNA hybrids. Its main function is hybrid removal, notably in the context of R-loops. RNase H2, which is also present in all branches of life, can play a similar role but it also has a specialized function in the cleavage of single ribonucleotides embedded in the DNA. RNase H3 is present in Archaea and bacteria and is closely related to RNase H2 in sequence and structure but has RNase H1-like biochemical properties. This review summarizes the mechanisms of substrate recognition and enzymatic cleavage by different classes of RNases H with particular insights into structural features of nucleic acid binding, specificity towards RNA and/or DNA strands and catalysis.

GTP Hydrolysis Without an Active Site Base: A Unifying Mechanism for Ras and Related GTPases

GTP hydrolysis is a biologically crucial reaction, being involved in regulating almost all cellular processes. As a result, the enzymes that catalyze this reaction are among the most important drug targets. Despite their vital importance and decades of substantial research effort, the fundamental mechanism of enzyme-catalyzed GTP hydrolysis by GTPases remains highly controversial. Specifically, how do these regulatory proteins hydrolyze GTP without an obvious general base in the active site to activate the water molecule for nucleophilic attack? To answer this question, we perform empirical valence bond simulations of GTPase-catalyzed GTP hydrolysis, comparing solvent- and substrate-assisted pathways in three distinct GTPases, Ras, Rab, and the G_αi subunit of a heterotrimeric G-protein, both in the presence and in the absence of the corresponding GTPase activating proteins. Our results demonstrate that a general base is not needed in the active site, as the preferred mechanism for GTP hydrolysis is a conserved solvent-assisted pathway. This pathway involves the rate-limiting nucleophilic attack of a water molecule, leading to a short-lived intermediate that tautomerizes to form H₂PO₄^- and GDP as the final products. Our fundamental biochemical insight into the enzymatic regulation of GTP hydrolysis not only resolves a decades-old mechanistic controversy but also has high relevance for drug discovery efforts. That is, revisiting the role of oncogenic mutants with respect to our mechanistic findings would pave the way for a new starting point to discover drugs for (so far) "undruggable" GTPases like Ras.

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

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

Efficient Ensemble Refinement by Reweighting

Ensemble refinement produces structural ensembles of flexible and dynamic biomolecules by integrating experimental data and molecular simulations. Here we present two efficient numerical methods to solve the computationally challenging maximum-entropy problem arising from a Bayesian formulation of ensemble refinement. Recasting the resulting constrained weight optimization problem into an unconstrained form enables the use of gradient-based algorithms. In two complementary formulations that differ in their dimensionality, we optimize either the log-weights directly or the generalized forces appearing in the explicit analytical form of the solution. We first demonstrate the robustness, accuracy, and efficiency of the two methods using synthetic data. We then use NMR J-couplings to reweight an all-atom molecular dynamics simulation ensemble of the disordered peptide Ala-5 simulated with the AMBER99SB*-ildn-q force field. After reweighting, we find a consistent increase in the population of the polyproline-II conformations and a decrease of α-helical-like conformations. Ensemble refinement makes it possible to infer detailed structural models for biomolecules exhibiting significant dynamics, such as intrinsically disordered proteins, by combining input from experiment and simulation in a balanced manner.