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

Can We Ever Develop an Ideal RNA Force Field? Lessons Learned from Simulations of the UUCG RNA Tetraloop and Other Systems

Molecular dynamics (MD) simulations are an important and well-established tool for investigating RNA structural dynamics, but their accuracy relies heavily on the quality of the employed force field (ff). In this work, we present a comprehensive evaluation of widely used pair-additive and polarizable RNA ffs using the challenging UUCG tetraloop (TL) benchmark system. Extensive standard MD simulations, initiated from the NMR structure of the 14-mer UUCG TL, revealed that most ffs did not maintain the native state, instead favoring alternative loop conformations. Notably, three very recent variants of pair-additive ffs, OL3CP-gHBfix21, DES-Amber, and OL3R2.7, successfully preserved the native structure over a 10 × 20 μs time scale. To further assess these ffs, we performed enhanced sampling folding simulations of the shorter 8-mer UUCG TL, starting from the single-stranded conformation. Estimated folding free energies (ΔG°fold) varied significantly among these three ffs, with values of 0.0 ± 0.6, 2.4 ± 0.8, and 7.4 ± 0.2 kcal/mol for OL3CP-gHBfix21, DES-Amber, and OL3R2.7, respectively. The ΔG°fold value predicted by the OL3CP-gHBfix21 ff was closest to experimental estimates, ranging from -1.6 to -0.7 kcal/mol. In contrast, the higher ΔG°fold values obtained using DES-Amber and OL3R2.7 were unexpected, suggesting that key interactions are inaccurately described in the folded, unfolded, or misfolded ensembles. These discrepancies led us to further test DES-Amber and OL3R2.7 ffs on additional RNA and DNA systems, where further performance issues were observed. Our results emphasize the complexity of accurately modeling RNA dynamics and suggest that creating an RNA ff capable of reliably performing across a wide range of RNA systems remains extremely challenging. In conclusion, our study provides valuable insights into the capabilities of current RNA ffs and highlights key areas for future ff development.

Emerging Mechanisms of Metal-Catalyzed RNA and DNA Modifications

Metal ions play a critical role in various chemical, biological, and environmental processes. This review reports on emerging chemical mechanisms in the catalysis of DNA and RNA. We provide an overview of the metal-dependent mechanisms of DNA cleavage in CRISPR (clustered regularly interspaced short palindromic repeats)-Cas systems that are transforming life sciences through genome editing technologies, and showcase intriguing metal-dependent mechanisms of RNA cleavages. We show that newly discovered CRISPR-Cas complexes operate as protein-assisted ribozymes, highlighting RNA's versatility and the enhancement of CRISPR-Cas functions through strategic metal ion use. We demonstrate the power of computer simulations in observing chemical processes as they unfold and in advancing structural biology through innovative approaches for refining cryo-electron microscopy maps. Understanding metal ion involvement in nucleic acid catalysis is crucial for advancing genome editing, aiding therapeutic interventions for genetic disorders, and improving the editing tools' specificity and efficiency.

rCGMM: A Coarse-Grained Force Field Embedding Elastic Network for Studying Small Noncoding RNA Dynamics

Short noncoding RNA molecules play significant roles in catalysis, biological regulation, and disease pathways. Their assessment through sequence-based approaches has been a challenge, compounded by the significant structural flexibility accrued from six free backbone torsions per nucleotide. To efficiently study the structure and dynamics of an extensive repertoire of these molecules in a high throughput mode, we have built a coarse-grained force field using one, two, three, and four pseudoatoms to represent the phosphate, sugar, pyrimidines, and purines, respectively. The Boltzmann inversion method was applied to structures of 5 piRNA, 8 miRNA, and 13 siRNA from the Nucleic Acid Database (NDB) to estimate the initial force field parameters and iteratively optimized through 1 μs molecular dynamics run by comparing against an equivalent all-atom simulation using the CHARMM36 force field. We applied an elastic net to model the hydrogen bond network stabilizing the local structure for double-stranded cases. A spine using pseudoatoms was calculated for the same from the coarse-grain beads, and all beads within a threshold radial distance were constrained using soft distance potentials. Lennard-Jones and Coulomb's potential function modeled the nonbonded interaction. Benchmarks on 26 molecules compared through root-mean-square deviation graphs against all-atom simulation show close concurrence for single- and double-stranded small noncoding RNA molecules. The rCGMM force field is available for download at https://github.com/majumderS/rCGMM.

The Unpaved Road of Non-Coding RNA Structure-Function Relationships: Current Knowledge, Available Methodologies, and Future Trends

The genomes from complex eukaryotes are enriched in non-coding genes whose transcription products (non-coding RNAs) are involved in the regulation of genomic output at different levels. Non-coding RNA action is predominantly driven by sequence and structural motifs that interact with specific functional partners. Despite the exponential growth in primary RNA sequence data facilitated by next-generation sequencing studies, the availability of tridimensional RNA data is comparatively more limited. The subjacent reasons for this relative lack of information regarding RNA structure are related to the specific chemical nature of RNA molecules and the limitations of the currently available methods for structural characterization of biomolecules. In this review, we describe and analyze the different structural motifs involved in non-coding RNA function and the wet-lab and computational methods used to characterize their structure-function relationships, highlighting the current need for detailed structural studies to explore the molecular determinants of non-coding RNA function.

How Binding Site Flexibility Promotes RNA Scanning by TbRGG2 RRM: A Molecular Dynamics Simulation Study

RNA recognition motifs (RRMs) are a key class of proteins that primarily bind single-stranded RNAs. In this study, we applied standard atomistic molecular dynamics simulations to obtain insights into the intricate binding dynamics between uridine-rich RNAs and TbRGG2 RRM using the recently developed OL3-Stafix AMBER force field, which improves the description of single-stranded RNA molecules. Complementing structural experiments that unveil a primary binding mode with a single uridine bound, our simulations uncover two supplementary binding modes in which adjacent nucleotides encroach upon the binding pocket. This leads to a unique molecular mechanism through which the TbRGG2 RRM is capable of rapidly transitioning the U-rich sequence. In contrast, the presence of non-native cytidines induces stalling and destabilization of the complex. By leveraging extensive equilibrium dynamics and a large variety of binding states, TbRGG2 RRM effectively expedites diffusion along the RNA substrate while ensuring robust selectivity for U-rich sequences despite featuring a solitary binding pocket. We further substantiate our description of the complex dynamics by simulating the fully spontaneous association process of U-rich sequences to the TbRGG2 RRM. Our study highlights the critical role of dynamics and auxiliary binding states in interface dynamics employed by RNA-binding proteins, which is not readily apparent in traditional structural studies but could represent a general type of binding strategy employed by many RNA-binding proteins.

Comprehensive Assessment of Force-Field Performance in Molecular Dynamics Simulations of DNA/RNA Hybrid Duplexes

Mixed double helices formed by RNA and DNA strands, commonly referred to as hybrid duplexes or hybrids, are essential in biological processes like transcription and reverse transcription. They are also important for their applications in CRISPR gene editing and nanotechnology. Yet, despite their significance, the hybrid duplexes have been seldom modeled by atomistic molecular dynamics methodology, and there is no benchmark study systematically assessing the force-field performance. Here, we present an extensive benchmark study of polypurine tract (PPT) and Dickerson-Drew dodecamer hybrid duplexes using contemporary and commonly utilized pairwise additive and polarizable nucleic acid force fields. Our findings indicate that none of the available force-field choices accurately reproduces all the characteristic structural details of the hybrid duplexes. The AMBER force fields are unable to populate the C3'-endo (north) pucker of the DNA strand and underestimate inclination. The CHARMM force field accurately describes the C3'-endo pucker and inclination but shows base pair instability. The polarizable force fields struggle with accurately reproducing the helical parameters. Some force-field combinations even demonstrate a discernible conflict between the RNA and DNA parameters. In this work, we offer a candid assessment of the force-field performance for mixed DNA/RNA duplexes. We provide guidance on selecting utilizable force-field combinations and also highlight potential pitfalls and best practices for obtaining optimal performance.

Thermodynamic and functional changes of alpha-chymotrypsin after interaction with gallic acid

In the present study, the interaction mechanism between gallic acid (GA) and α-Chymotrypsin (α-CT) was investigated by employing a series ofspectroscopic methods, computational docking and molecular dynamic (MD) simulation. Fluorescence spectra analysis indicated the formation of a stable complex between GA and α-CT, where the quenching of the fluorescence emission was predominantly characterized by a static mechanism. TheCA obtained binding constants for the α-CT-GA complex were in the order of 103 M-1, indicating the moderate binding affinity of GA for α-CT. The corresponding CD findings showed that the interaction between GA and α-CT resulted in an alteration of the protein's secondary structure. The findings of the enzyme activity investigation clearly showed that the presence of GA led to a notable decline in the enzymatic activity of α-CT, highlighting GA's function as an effective inhibitor for α-CT. The molecular docking simulations revealed the optimal binding site for the GA molecule within the α-CT structure and MD simulations confirmed the stability of the α-CT-GA complex. This research expands our comprehension regarding the behavior of enzymes in the presence of small-molecule ligands and opens avenues for food safety.

Interaction between the antioxidant compound safranal and α-chymotrypsin in spectroscopic fields and molecular modeling approaches

Among various herbal plants, saffron has been the subject of study in various medical and food fields. Among the compounds of saffron, safranal is one of them. Safranal is a monoterpene aldehyde. The precursor of safranal is called picrocrocin, whose hydrolysis leads to the production of safranal. picrocrocin has two sugar components and aglycone. sugar component was separated during the drying process of saffron and safranal is produced. Saffron is the cause of the saffron aroma. Previous studies have shown that safranal offers many benefits such as antioxidants, blood pressure regulation and anti-tumor qualities. On the other hand, α-Chy is an enzyme secreted by the pancreas into the intestine and then acts as an efficient protease. In this study, various methods, such as molecular dynamics (MD) simulation and molecular binding, and different spectroscopic techniques, as well as protein stability techniques, were used to investigate the possible interactions between safranal and α-Chy. UV spectroscopic studies were showing that the existence of safranal decreased α-Chy absorption intensity. safranal caused the intrinsic fluorescence of α-Chy to be quenched too. According to the Stern-Volmer equation, the interaction between safranal and α-Chy was of the static type. In thermodynamic calculations, the interaction between safranal and α-Chy was stabilized by hydrophobic forces. And it was found that this interaction continued spontaneously. These results were, thus, consistent with the Docking data simulation (with the negative ΔG° number and positive changes in enthalpy and entropy). The thermal stability of α-Chy was also measured, showing that its melting point was shifted to a higher threshold as a result of the interaction. also, MD simulation indicated that α-Chy became more stable in the presence of safranal. In this paper, all the results of the laboratory techniques were confirmed by molecular dynamic simulations, so the correctness of the results was confirmed. From this research, we hope to carefully observe the possible changes in the behavior and structure of the enzyme in the presence of safranal.Communicated by Ramaswamy H. Sarma.

Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation

Non-coding RNAs (ncRNAs), generated from nonprotein coding DNA sequences, constitute 98-99% of the human genome. Non-coding RNAs encompass diverse functional classes, including microRNAs, small interfering RNAs, PIWI-interacting RNAs, small nuclear RNAs, small nucleolar RNAs, and long non-coding RNAs. With critical involvement in gene expression and regulation across various biological and physiopathological contexts, such as neuronal disorders, immune responses, cardiovascular diseases, and cancer, non-coding RNAs are emerging as disease biomarkers and therapeutic targets. In this review, after providing an overview of non-coding RNAs' role in cell homeostasis, we illustrate the potential and the challenges of state-of-the-art computational methods exploited to study non-coding RNAs biogenesis, function, and modulation. This can be done by directly targeting them with small molecules or by altering their expression by targeting the cellular engines underlying their biosynthesis. Drawing from applications, also taken from our work, we showcase the significance and role of computer simulations in uncovering fundamental facets of ncRNA mechanisms and modulation. This information may set the basis to advance gene modulation tools and therapeutic strategies to address unmet medical needs.

Binding Mechanism of Riboswitch to Natural Ligand Elucidated by McMD-Based Dynamic Docking Simulations

Flavin mononucleotide riboswitches are common among many pathogenic bacteria and are therefore considered to be an attractive target for antibiotics development. The riboswitch binds riboflavin (RBF, also known as vitamin B2), and although an experimental structure of their complex has been solved with the ligand bound deep inside the RNA molecule in a seemingly unreachable state, the binding mechanism between these molecules is not yet known. We have therefore used our Multicanonical Molecular Dynamics (McMD)-based dynamic docking protocol to analyze their binding mechanism by simulating the binding process between the riboswitch aptamer domain and the RBF, starting from the apo state of the riboswitch. Here, the refinement stage was crucial to identify the native binding configuration, as several other binding configurations were also found by McMD-based docking simulations. RBF initially binds the interface between P4 and P6 including U61 and G62, which forms a gateway where the ligand lingers until this gateway opens sufficiently to allow the ligand to pass through and slip into the hidden binding site including A48, A49, and A85.

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

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

Machines on Genes through the Computational Microscope

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

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.

NARall: a novel tool for reconstruction of the all-atom structure of nucleic acids from heavily coarse-grained model

Nucleic acids are one of the most important cellular components. These molecules have been studied both experimentally and theoretically. As all-atom simulations are still limited to short time scales, coarse-grain modeling allows to study of those molecules on a longer time scale. Nucleic-Acid united RESidue (NARES-2P) is a low-resolution coarse-grained model with two centers of interaction per repeating unit. It has been successfully applied to study DNA self-assembly and telomeric properties. This force field enables the study of nucleic acids Behavior on a long time scale but lacks atomistic details. In this article, we present new software to reconstruct atomistic details from the NARES-2P model. It has been applied to RNA pseudoknot, nucleic acid four-way junction, G-quadruplex and DNA duplex converted to NARES-2P model and back. Moreover, it was applied to DNA structure folded and self-assembled with NARES-2P.

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

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

Emerging Methods and Applications to Decrypt Allostery in Proteins and Nucleic Acids

Many large protein-nucleic acid complexes exhibit allosteric regulation. In these systems, the propagation of the allosteric signaling is strongly coupled to conformational dynamics and catalytic function, challenging state-of-the-art analytical methods. Here, we review established and innovative approaches used to elucidate allosteric mechanisms in these complexes. Specifically, we report network models derived from graph theory and centrality analyses in combination with molecular dynamics (MD) simulations, introducing novel schemes that implement the synergistic use of graph theory with enhanced simulations methods and ab-initio MD. Accelerated MD simulations are used to construct "enhanced network models", describing the allosteric response over long timescales and capturing the relation between allostery and conformational changes. "Ab-initio network models" combine graph theory with ab-initio MD and quantum mechanics/molecular mechanics (QM/MM) simulations to describe the allosteric regulation of catalysis by following the step-by-step dynamics of biochemical reactions. This approach characterizes how the allosteric regulation changes from reactants to products and how it affects the transition state, revealing a tense-to-relaxed allosteric regulation along the chemical step. Allosteric models and applications are showcased for three paradigmatic examples of allostery in protein-nucleic acid complexes: (i) the nucleosome core particle, (ii) the CRISPR-Cas9 genome editing system and (iii) the spliceosome. These methods and applications create innovative protocols to determine allosteric mechanisms in protein-nucleic acid complexes that show tremendous promise for medicine and bioengineering.

Accelerating the Ensemble Convergence of RNA Hairpin Simulations with a Replica Exchange Structure Reservoir

RNA is a key participant in many biological processes, but studies of RNA using computer simulations lag behind those of proteins, largely due to less-developed force fields and the slow dynamics of RNA. Generating converged RNA ensembles for force field development and other studies remains a challenge. In this study, we explore the ability of replica exchange molecular dynamics to obtain well-converged conformational ensembles for two RNA hairpin systems in an implicit solvent. Even for these small model systems, standard REMD remains computationally costly, but coupling to a pre-generated structure library using the reservoir REMD approach provides a dramatic acceleration of ensemble convergence for both model systems. Such precise ensembles could facilitate RNA force field development and validation and applications of simulation to more complex RNA systems. The advantages and remaining challenges of applying R-REMD to RNA are investigated in detail.

Molecular Dynamics Simulations of Reduced and Oxidized TFIIIA Zinc Fingers Free and Interacting with 5S RNA

Interactions of zinc finger (ZF) proteins with nucleic acids and proteins play an important role in DNA transcription and repair, biochemical recognition, and protein regulation. The release of Zn²⁺ through oxidation of cysteine thiolates is associated with disruption of gene expression and DNA repair, preventing tumor growth. Multi-microsecond molecular dynamics (MD) simulations were carried out to examine the effect of Cys oxidation on the ZF456 fragment of transcription factor III A (TFIIIA) and its complex with 5S RNA. In the absence of 5S RNA, the reduced ZF456 peptide undergoes conformational changes in the secondary structure due to the reorientation of the intact ZF domains. Upon oxidation, the individual ZF domains unfold to various degrees, yielding a globular ZF456 peptide with ZF4 and ZF6, responsible for base-specific hydrogen bonds with 5S RNA, losing their ββα-folds. ZF5, on the other hand, participates in nonspecific interactions through its α-helix that conditionally unravels early in the simulation. In the presence of RNA, oxidation of the ZF456 peptide disrupts the key hydrogen bonding interactions between ZF5/ZF6 and 5S RNA. However, interactions with ZF4 are dependent on the protonation state of His119.

Atomic-scale insights into allosteric inhibition and evolutional rescue mechanism of Streptococcus thermophilus Cas9 by the anti-CRISPR protein AcrIIA6

CRISPR-Cas systems are prokaryotic adaptive immunity against invading phages and plasmids. Phages have evolved diverse protein inhibitors of CRISPR-Cas systems, called anti-CRISPR (Acr) proteins, to neutralize this CRISPR machinery. In response, bacteria have co-evolved Cas variants to escape phage's anti-CRISPR strategies, called anti-anti-CRISPR systems. Here we explore the anti-CRISPR allosteric inhibition and anti-anti-CRISPR rescue mechanisms between Streptococcus thermophilus Cas9 (St1Cas9) and the anti-CRISPR protein AcrIIA6 at the atomic level, by generating mutants of key residues in St1Cas9. Extensive unbiased molecular dynamics simulations show that the functional motions of St1Cas9 in the presence of AcrIIA6 differ substantially from those of St1Cas9 alone. AcrIIA6 binding triggers a shift of St1Cas9 conformational ensemble towards a less catalytically competent state; this state significantly compromises protospacer adjacent motif (PAM) recognition and nuclease activity by altering interdependently conformational dynamics and allosteric signals among nuclease domains, PAM-interacting (PI) regions, and AcrIIA6 binding motifs. Via in vitro DNA cleavage assays, we further elucidate the rescue mechanism of efficiently escaping AcrIIA6 inhibition harboring St1Cas9 triple mutations (G993K/K1008M/K1010E) in the PI domain and identify the evolutionary landscape of such mutational escape within species. Our results provide mechanistic insights into Acr proteins as natural brakes for the CRISPR-Cas systems and a promising potential for the design of allosteric Acr peptidomimetics.

Binding free energy decomposition and multiple unbinding paths of buried ligands in a PreQ1 riboswitch

Riboswitches are naturally occurring RNA elements that control bacterial gene expression by binding to specific small molecules. They serve as important models for RNA-small molecule recognition and have also become a novel class of targets for developing antibiotics. Here, we carried out conventional and enhanced-sampling molecular dynamics (MD) simulations, totaling 153.5 μs, to characterize the determinants of binding free energies and unbinding paths for the cognate and synthetic ligands of a PreQ₁ riboswitch. Binding free energy analysis showed that two triplets of nucleotides, U6-C15-A29 and G5-G11-C16, contribute the most to the binding of the cognate ligands, by hydrogen bonding and by base stacking, respectively. Mg²⁺ ions are essential in stabilizing the binding pocket. For the synthetic ligands, the hydrogen-bonding contributions of the U6-C15-A29 triplet are significantly compromised, and the bound state resembles the apo state in several respects, including the disengagement of the C15-A14-A13 and A32-G33 base stacks. The bulkier synthetic ligands lead to significantly loosening of the binding pocket, including extrusion of the C15 nucleobase and a widening of the C15-C30 groove. Enhanced-sampling simulations further revealed that the cognate and synthetic ligands unbind in almost opposite directions. Our work offers new insight for designing riboswitch ligands.

Riboswitches are bacterial RNA elements that change structures upon binding a cognate ligand. They are of great interest not only for understanding gene regulation but also as targets for designing small-molecule antibiotics and chemical tools. Understanding the molecular determinants for ligand affinity and selectivity is thus crucial for designing synthetic ligands. Here we carried out extensive molecular dynamics simulations of a PreQ₁ riboswitch bound to either cognate or synthetic ligands. By comparing and contrasting these two groups of ligands, we learn how the chemical (e.g., number of hydrogen bond donors and acceptors) and physical (e.g., molecular size) features of ligands affect binding affinity and ligand exit paths. While the number of hydrogen bond donors and acceptors is a key determinant for RNA binding affinity, the ligand size affects the rigidity of the binding pocket and thereby regulates the unbinding of the ligand. These lessons provide guidance for designing riboswitch ligands.

Allosteric Control of Structural Mimicry and Mutational Escape in the SARS-CoV-2 Spike Protein Complexes with the ACE2 Decoys and Miniprotein Inhibitors: A Network-Based Approach for Mutational Profiling of Binding and Signaling

We developed a computational framework for comprehensive and rapid mutational scanning of binding energetics and residue interaction networks in the SARS-CoV-2 spike protein complexes. Using this approach, we integrated atomistic simulations and conformational landscaping of the SARS-CoV-2 spike protein complexes with ensemble-based mutational screening and network modeling to characterize mechanisms of structure-functional mimicry and resilience toward mutational escape by the ACE2 protein decoy and de novo designed miniprotein inhibitors. A detailed analysis of structural plasticity of the SARS-CoV-2 spike proteins obtained from atomistic simulations of conformational landscapes and sequence-based profiling of the disorder propensities revealed the intrinsically flexible regions that harbor key functional sites targeted by circulating variants. The conservation of collective dynamics in the SARS-CoV-2 spike protein complexes showed that mutational escape positions are important for modulation of functional motions and that mutational changes in these sites can alter allosteric interaction networks. Through mutational profiling of binding and allosteric propensities in the SARS-CoV-2 spike protein complexes, we identified the key binding and regulatory hotspots that collectively determine functional response and resilience of miniproteins to mutational variants. The results suggest that binding affinities and allosteric signatures of the SARS-CoV-2 complexes can be determined by dynamic crosstalk between structurally stable regulatory centers and conformationally adaptable allosteric hotspots that collectively control the resilience toward mutational escape. This may underlie a mechanism in which moderate perturbations in the mutational escape positions can induce global allosteric changes and alter functional protein response by modulating signaling in the residue interaction networks.

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.

Comparative Perturbation-Based Modeling of the SARS-CoV-2 Spike Protein Binding with Host Receptor and Neutralizing Antibodies: Structurally Adaptable Allosteric Communication Hotspots Define Spike Sites Targeted by Global Circulating Mutations

In this study, we used an integrative computational approach to examine molecular mechanisms and determine functional signatures underlying the role of functional residues in the SARS-CoV-2 spike protein that are targeted by novel mutational variants and antibody-escaping mutations. Atomistic simulations and functional dynamics analysis are combined with alanine scanning and mutational sensitivity profiling of the SARS-CoV-2 spike protein complexes with the ACE2 host receptor and the REGN-COV2 antibody cocktail(REG10987+REG10933). Using alanine scanning and mutational sensitivity analysis, we have shown that K417, E484, and N501 residues correspond to key interacting centers with a significant degree of structural and energetic plasticity that allow mutants in these positions to afford the improved binding affinity with ACE2. Through perturbation-based network modeling and community analysis of the SARS-CoV-2 spike protein complexes with ACE2, we demonstrate that E406, N439, K417, and N501 residues serve as effector centers of allosteric interactions and anchor major intermolecular communities that mediate long-range communication in the complexes. The results provide support to a model according to which mutational variants and antibody-escaping mutations constrained by the requirements for host receptor binding and preservation of stability may preferentially select structurally plastic and energetically adaptable allosteric centers to differentially modulate collective motions and allosteric interactions in the complexes with the ACE2 enzyme and REGN-COV2 antibody combination. This study suggests that the SARS-CoV-2 spike protein may function as a versatile and functionally adaptable allosteric machine that exploits the plasticity of allosteric regulatory centers to fine-tune response to antibody binding without compromising the activity of the spike protein.

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.

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

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

Combining Virtual Reality Visualization with Ensemble Molecular Dynamics to Study Complex Protein Conformational Changes

Molecular dynamics (MD) simulations are increasingly used to elucidate relationships between protein structure, dynamics, and their biological function. Currently, it is extremely challenging to perform MD simulations of large-scale structural rearrangements in proteins that occur on millisecond timescales or beyond, as this requires very significant computational resources, or the use of cumbersome "collective variable" enhanced sampling protocols. Here, we describe a framework that combines ensemble MD simulations and virtual reality visualization (eMD-VR) to enable users to interactively generate realistic descriptions of large amplitude, millisecond timescale protein conformational changes in proteins. Detailed tests demonstrate that eMD-VR substantially decreases the computational cost of folding simulations of a WW domain, without the need to define collective variables a priori. We further show that eMD-VR generated pathways can be combined with Markov state models to describe the thermodynamics and kinetics of large-scale loop motions in the enzyme cyclophilin A. Our results suggest eMD-VR is a powerful tool for exploring protein energy landscapes in bioengineering efforts.

Frontiers of metal-coordinating drug design

Introduction: The occurrence of metal ions in biomolecules is required to exert vital cellular functions. Metal-containing biomolecules can be modulated by small-molecule inhibitors targeting their metal-moiety. As well, the discovery of cisplatin ushered the rational discovery of metal-containing-drugs. The use of both drug types exploiting metal-ligand interactions is well established to treat distinct pathologies. Therefore, characterizing and leveraging metal-coordinating drugs is a pivotal, yet challenging, part of medicinal chemistry.Area covered: Atomic-level simulations are increasingly employed to overcome the challenges met by traditional drug-discovery approaches and to complement wet-lab experiments in elucidating the mechanisms of drugs' action. Multiscale simulations, allow deciphering the mechanism of metal-binding inhibitors and metallo-containing-drugs, enabling a reliable description of metal-complexes in their biological environment. In this compendium, the authors review selected applications exploiting the metal-ligand interactions by focusing on understanding the mechanism and design of (i) inhibitors targeting iron and zinc-enzymes, and (ii) ruthenium and gold-based anticancer agents targeting the nucleosome and aquaporin protein, respectively.Expert opinion: The showcased applications exemplify the current role and the potential of atomic-level simulations and reveal how their synergic use with experiments can contribute to uncover fundamental mechanistic facets and exploit metal-ligand interactions in medicinal chemistry.

Visualizing group II intron dynamics between the first and second steps of splicing

Group II introns are ubiquitous self-splicing ribozymes and retrotransposable elements evolutionarily and chemically related to the eukaryotic spliceosome, with potential applications as gene-editing tools. Recent biochemical and structural data have captured the intron in multiple conformations at different stages of catalysis. Here, we employ enzymatic assays, X-ray crystallography, and molecular simulations to resolve the spatiotemporal location and function of conformational changes occurring between the first and the second step of splicing. We show that the first residue of the highly-conserved catalytic triad is protonated upon 5’-splice-site scission, promoting a reversible structural rearrangement of the active site (toggling). Protonation and active site dynamics induced by the first step of splicing facilitate the progression to the second step. Our insights into the mechanism of group II intron splicing parallels functional data on the spliceosome, thus reinforcing the notion that these evolutionarily-related molecular machines share the same enzymatic strategy.

Group II introns are self-splicing ribozymes. Here, the authors employ enzymatic assay, X-ray crystallography and molecular dynamics simulations to show that protonation of the group II intron catalytic triad plays an important role for the transition from the first to the second step of splicing.

Decrypting the Information Exchange Pathways across the Spliceosome Machinery

Intron splicing of a nascent mRNA transcript by spliceosome (SPL) is a hallmark of gene regulation in eukaryotes. SPL is a majestic molecular machine composed of an entangled network of proteins and RNAs that meticulously promotes intron splicing through the formation of eight intermediate complexes. Cross-communication among the critical distal proteins of the SPL assembly is pivotal for fast and accurate directing of the compositional and conformational readjustments necessary to achieve high splicing fidelity. Here, molecular dynamics (MD) simulations of an 800 000 atom model of SPL C complex from yeast Saccharomyces cerevisiae and community network analysis enabled us to decrypt the complexity of this huge molecular machine, by identifying the key channels of information transfer across long distances separating key protein components. The reported study represents an unprecedented attempt in dissecting cross-communication pathways within one of the most complex machines of eukaryotic cells, supporting the critical role of Clf1 and Cwc2 splicing cofactors and specific domains of the Prp8 protein as signal conveyors for pre-mRNA maturation. Our findings provide fundamental advances into mechanistic aspects of SPL, providing a conceptual basis for controlling the SPL via small-molecule modulators able to tackle splicing-associated diseases by altering/obstructing information-exchange paths.

Recruiting Mechanism and Functional Role of a Third Metal Ion in the Enzymatic Activity of 5' Structure-Specific Nucleases

Enzymes of the 5′ structure-specific nuclease family are crucial for DNA repair, replication, and recombination. One such enzyme is the human exonuclease 1 (hExo1) metalloenzyme, which cleaves DNA strands, acting primarily as a processive 5′-3′ exonuclease and secondarily as a 5′-flap endonuclease. Recently, in crystallo reaction intermediates have elucidated how hExo1 exerts hydrolysis of DNA phosphodiester bonds. These hExo1 structures show a third metal ion intermittently bound close to the two-metal-ion active site, to which recessed ends or 5′-flap substrates bind. Evidence of this third ion has been observed in several nucleic-acid-processing metalloenzymes. However, there is still debate over what triggers the (un)binding of this transient third ion during catalysis and whether this ion has a catalytic function. Using extended molecular dynamics and enhanced sampling free-energy simulations, we observed that the carboxyl side chain of Glu89 (located along the arch motif in hExo1) flips frequently from the reactant state to the product state. The conformational flipping of Glu89 allows one metal ion to be recruited from the bulk and promptly positioned near the catalytic center. This is in line with the structural evidence. Additionally, our simulations show that the third metal ion assists the departure, through the mobile arch, of the nucleotide monophosphate product from the catalytic site. Structural comparisons of nuclease enzymes suggest that this Glu(Asp)-mediated mechanism for third ion recruitment and nucleic acid hydrolysis may be shared by other 5′ structure-specific nucleases.

Molecular Mechanism of Brassinosteroid Perception by the Plant Growth Receptor BRI1

Brassinosteroids (BRs) are essential phytohormones, which bind to the plant receptor, BRI1, to regulate various physiological processes. The molecular mechanism of the perception of BRs by the ectodomain of BRI1 remains not fully understood. It also remains elusive why a substantial difference in biological activity exists between the BRs. In this work, we study the binding mechanisms of the two most bioactive BRs, brassinolide (BLD) and castasterone (CAT), using molecular dynamics simulations. We report free-energy landscapes of the binding processes of both ligands, as well as detailed ligand binding pathways. Our results suggest that CAT has a lower binding affinity compared to BLD due to its inability to form hydrogen-bonding interactions with a tyrosine residue in the island domain of BRI1. We uncover a conserved nonproductive binding state for both BLD and CAT, which is more stable for CAT and may further contribute to the bioactivity difference. Finally, we validate past observations about the conformational restructuring and ordering of the island domain upon BLD binding. Overall, this study provides new insights into the fundamental mechanism of the perception of the two most bioactive BRs, which may create new avenues for genetic and agrochemical control of their signaling cascade.

Three-Dimensional Structure of RNA Monomeric G-Quadruplex Containing ALS and FTD Related G4C2 Repeat and Its Binding with TMPyP4 Probed by Homology Modeling based on Experimental Constraints and Molecular Dynamics Simulations

The G-quadruplex-forming hexanucleotide repeat expansion (HRE), d(G4C2)_n, within the human C9orf72 gene is the root cause for familial amyotrophic lateral sclerosis-frontotemporal dementia (ALS-FTD). A recent study has shown that TMPyP4 has good potential to work as a RNA G-quadruplex binder in treating ALS and FTD. Although the high-resolution structure of the monomeric DNA antiparallel G-quadruplex form of the monomeric hexanucleotide repeat was recently solved, the RNA parallel G-quadruplex structure and its complex with TMPyP4 are not available yet. In this study, we first constructed the homology model for the parallel monomeric RNA G-quadruplex of r(G4C2)₃G4 based on experimental constraints and the parallel monomeric G-quadruplex DNA crystal structure. Although the G-tetra core of the homology model was stable observed in 15 μs molecular dynamics (MD) simulations, we observed that the loops adopt additional conformations besides the initial crystal conformation, where TMPyP4 binding was found to reduce the loop fluctuation of the RNA monomeric G-quadruplex. Next, we probed the elusive binding behavior of TMPyP4 to the RNA monomeric G-quadruplex. Encouragingly, the binding modes observed are similar to the modes observed in two experimental complexes of a parallel DNA G-quadruplex with TMPyP4. We also constructed a Markov state model to provide insights into the binding pathways. Together, the findings from our study may assist future development of G-quadruplex-specific ligands in the treatment of neurodegenerative diseases like ALS and FTD.

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

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