Ribonucleic acid (RNA) molecules fold into complex, highly dynamic three-dimensional conformational structures that govern their biological activities. Chemical probing methods, such as SHAPE (selective 2’-hydroxyl acylation analyzed by primer extension), provide structural insights in the form of one-dimensional (1D) nucleotide reactivity profiles. However, mapping these one-dimensional profiles back to the underlying dynamic structures remains a key challenge, as traditional analyses rely on a static view based on three-dimensional (3D) high-resolution structures from X-ray crystallography or NMR, rather than accounting for the dynamic nature of the system. In this Application Note, we introduce MARS-RNA (MD Analysis for Reactivity and Structure), an automated pipeline that extracts and integrates multi-scale structural and geometric features from RNA Molecular Dynamics (MD) trajectories, combining them with secondary (2D) and 3D annotations from X3DNA-DSSR to identify features that correlate with experimental reactivity. MARS-RNA processes raw GROMACS trajectories, performs frame-by-frame structural annotation, calculates spatial centroids and physical distance fluctuations, computes Pearson/Spearman correlation coefficients against SHAPE data, and pre-processes results for machine learning pipelines. We show its value on the RNA 3′-UTR (PDB ID: 1AUD, chain A), by highlighting several single correlation with SHAPE reactivity.

Nucleophosmin (NPM1) is a nucleolar protein commonly mutated in ~30% of newly diagnosed acute myeloid leukemia (AML) cases. These mutations occur in the terminal exon of the NPM1 gene, affecting the C-terminal DNA-binding domain of the protein and causing its delocalization to the cytoplasm-a hallmark of NPM1-mutated AML. NPM1 shuttling to the nucleoplasm is tightly regulated by posttranslational modifications, such as phosphorylation of Ser254, Ser260, and Tyr271 of the DNA-binding domain. However, the structural mechanisms underlying this process remain unclear. In this work, we show that Ser-to-Asp (S254D-S260D) and Tyr-to-pCMF (para-carboxymethyl phenylalanine) (Y271pCMF) phosphomimetic mutations induce significant structural and dynamical rearrangements, as well as drastic modifications in electrostatic surface potential. These changes compromise recognition of a G-quadruplex sequence from the c-MYC promoter by reducing DNA-binding affinity, reshape histone capturing dynamics, and fade charge segregation in the histone-binding domain. Combination of such substitutions in a triple phosphomimetic variant (S254D-S260D-Y271pCMF) further destabilizes the domain's structure and triggers protein aggregation. Altogether, these findings suggest that phosphorylation of Ser254, Ser260, and Tyr271 of the C-end DNA-binding domain weakens both DNA affinity and charge block-driven liquid-liquid phase separation, offering a molecular explanation for the delocalization of NPM1 outside of the nucleolus.

Methyltransferases (MTases) are enzymes that methylate biomolecules like proteins, DNA, RNA, lipids, and small molecules, mostly using S-adenosyl-L-methionine (SAM) as a methyl donor. MTases have emerged as promising drug targets, and SAM analogues are widely employed to investigate their involvement in diseases and to develop effective drug therapies. We designed and synthesized stable SAM analogues with a squaramide moiety mimicking the methionine side chain. These compounds were tested on the two human m⁶A RNA MTases METTL3/14 and METTL16. While these SAM analogues failed to support catalytic activity, they exhibited potent inhibitory effects on the METTL3/14 activity. Surprisingly, some of these compounds demonstrated remarkable potency (KI = 3 nM) and specificity, likely attributed to the unique properties of the squaramide motif. Docking studies showed they bind METTL3/14 cofactor pocket similarly to SAM, allowing us to make new hypothesis on the catalytic mechanism. Our synthetic method expands the structural diversity of SAM analogues, providing a foundation for developing selective RNA MTase inhibitors. SAM-dependent methyltransferases (MTases) are crucial enzymes involved in various biological processes and are considered promising drug targets. Here, the authors synthesize SAM analogues with a squaramide moiety mimicking the methionine side chain, demonstrating potent and specific inhibitory effects on RNA MTase METTL3/14 activity.

Ribonucleic acid (RNA) molecules play a crucial role in nearly every cellular process, with their function closely tied to their three-dimensional (3D) structure. As a result, determining the precise 3D structure of RNAs is essential to understanding their biological functions. However, obtaining high-resolution 3D structures remains a significant challenge with traditional biophysical techniques. To address this, chemical probing methods such as SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension) have gained widespread popularity. SHAPE reactivities have been introduced in 2D RNA predictors as soft constraints on nucleotide base pairing, although the acylation reaction involves the ribose moiety. Little is known about the physical chemistry behind this reaction, leaving several reactivities unexplained. In this context, our aim is to unveil the complex relationship between the local structure of RNA, its dynamics, and the SHAPE chemical reactivity. In this study, using a multiscale approach based on biased molecular dynamics simulations and quantum mechanics/molecular mechanics (QM/MM) calculations on the well characterized GAAA RNA tetraloop, we provide new molecular insights on the prereactive complex and its binding mode. Our findings emphasize the critical role of the local environment in facilitating the recruitment and proper accommodation of the SHAPE probe. All-atom umbrella sampling (US) molecular dynamics (MD) simulations underscored the significance of the binding angle in forming the prereactive complex, which was thoroughly analyzed using geometrical descriptors. In US QM/MM simulations, we used different initial structures to demonstrate the effect of favorable binding on the acylation reaction by characterizing the first step. Moreover, we investigated the deprotonation of the hydroxyl and its role in the acylation reaction, highlighting the role of the local environment and the probe proximity in this process. Our results suggest that the formation of oxyanion prior to the binding is not required to initiate the chemical reaction.

Facing the current challenges posed by human health diseases requires the understanding of cell machinery at a molecular level. The interplay between proteins and RNA is key for any physiological phenomenon, as well protein-RNA interactions. To understand these interactions, many experimental techniques have been developed, spanning a very wide range of spatial and temporal resolutions. In particular, the knowledge of tridimensional structures of protein-RNA complexes provides structural, mechanical, and dynamical pieces of information essential to understand their functions. To get insights into the dynamics of protein-RNA complexes, we carried out all-atom molecular dynamics simulations in explicit solvent on nine different protein-RNA complexes with different functions and interface size by taking into account the bound and unbound forms. First, we characterized structural changes upon binding and, for the RNA part, the change in the puckering. Second, we extensively analyzed the interfaces, their dynamics and structural properties, and the structural waters involved in the binding, as well as the contacts mediated by them. Based on our analysis, the interfaces rearranged during the simulation time showing alternative and stable residue-residue contacts with respect to the experimental structure.

Water molecules are essential to determine the structure of nucleic acids and mediate their interactions with other biomolecules. Here, we characterize the hydration dynamics of analogous DNA and RNA double helices with unprecedented resolution and elucidate the molecular origin of their differences: localization of the slowest hydration water molecules---in the groove in DNA, next to phosphates in RNA--- and a markedly distinct hydration dynamics of the two phosphate oxygen atoms OR and OS in RNA. Using our Extended Jump Model for water reorientation, we assess the relative importance of previously proposed factors, including the local topography, water bridges and the presence of ions. We show that the slow hydration dynamics at RNA OR sites is not due to bridging water molecules, but is caused by both a larger excluded volume and a stronger initial H-bond next to OR, which can be linked to different phosphate orientations in A-form double helical RNA.

Combining enhanced sampling molecular dynamics simulations with dynamic QM/MMMD exploration of the mechanisms, we shed light at the molecular level on the maturation process of 5S rRNA in B. subtilis, performed by the M5 enzyme. Providing a small displacement of the scissile phosphate and the use of adequate force fields, the structure of the experimentally reconstructed complex is stable, with small conformational fluctuations of the interface. Enhanced sampling is critical to reveal the full extent of the conformational variability of the rRNA:M5 interface, which we show critically impacts the active site structure by modulating the distance and orientation between key reactive residues. This rich conformational landscape thus suggests a variety of possible reaction mechanisms, that depend on the active site pre-organization. Comprehensive characterization of the different possible mechanisms from each conformational basin suggests that the most favorable reaction route would involve deprotonation of the nucleophilic water by the active site Glu96 and reprotonation of the 3′ leaving group by a Mg2+-bound water. Contrary to other RNases, M5 activity does not rely on a bifurcated aspartate between the 2 active site cations, nor on the release of initially frustrated hydration shells.

We investigated the capability of internal normal modes to reproduce RNA flexibility and predict observed RNA conformational changes and, notably, those induced by the formation of RNA-protein and RNA-ligand complexes. Here, we extended our iNMA approach developed for proteins to study RNA molecules using a simplified representation of the RNA structure and its potential energy. Three data sets were also created to investigate different aspects. Despite all the approximations, our study shows that iNMA is a suitable method to take into account RNA flexibility and describe its conformational changes opening the route to its applicability in any integrative approach where these properties are crucial.

Adenylyl cyclases (ACs) play a key role in many signaling cascades. ACs catalyze the production of cyclic AMP from ATP and this function is stimulated or inhibited by the binding of their cognate stimulatory or inhibitory Gα subunits, respectively. Here we used simulation tools to uncover the molecular and subcellular mechanisms of AC function, with a focus on the AC5 isoform, extensively studied experimentally. First, quantum mechanical/molecular mechanical free energy simulations were used to investigate the enzymatic reaction and its changes upon point mutations. Next, molecular dynamics simulations were employed to assess the catalytic state in the presence or absence of Gα subunits. This led to the identification of an inactive state of the enzyme that is present whenever an inhibitory Gα is associated, independent of the presence of a stimulatory Gα. In addition, the use of coevolution‐guided multiscale simulations revealed that the binding of Gα subunits reshapes the free‐energy landscape of the AC5 enzyme by following the classical population‐shift paradigm. Finally, Brownian dynamics simulations provided forward rate constants for the binding of Gα subunits to AC5, consistent with the ability of the protein to perform coincidence detection effectively. Our calculations also pointed to strong similarities between AC5 and other AC isoforms, including AC1 and AC6. Findings from the molecular simulations were used along with experimental data as constraints for systems biology modeling of a specific AC5‐triggered neuronal cascade to investigate how the dynamics of downstream signaling depend on initial receptor activation.

Protein-protein interactions are at the basis of many protein functions, and the knowledge of 3D structures of protein-protein complexes provides structural, mechanical and dynamical pieces of information essential to understand these functions. Protein-protein interfaces can be seen as stable, organized regions where residues from different partners form non-covalent interactions that are responsible for interaction specificity and strength. They are commonly described as a peripheral region, whose role is to protect the core region that concentrates the most contributing interactions, from the solvent. To get insights into the dynamics of protein-protein complexes, we carried out all-atom molecular dynamics simulations in explicit solvent on eight different protein-protein complexes of different functional class and interface size by taking into account the bound and unbound forms. On the one hand, we characterized structural changes upon binding of the proteins, and on the other hand we extensively analyzed the interfaces and the structural waters involved in the binding. Based on our analysis, in 6 cases out of 8, the interfaces rearranged during the simulation time, in stable and long-lived substates with alternative residue-residue contacts. These rearrangements are not restricted to side-chain fluctuations in the periphery but also affect the core interface. Finally, the analysis of the waters at the interface and involved in the binding pointed out the importance to take into account their role in the estimation of the interaction strength.

Endoglin (Eng) is an endothelial cell (EC) transmembrane glycoprotein involved in adhesion and angiogenesis. Eng mutations result in vessel abnormalities as observed in hereditary hemorrhagic telangiectasia of type 1. The role of Eng was investigated in endothelial functions and permeability under inflammatory conditions, focusing on the actin dynamic signaling pathway. Endothelial Colony-Forming Cells (ECFC) from human cord blood and mouse lung/aortic EC (MLEC, MAEC) from Eng+/+ and Eng+/− mice were used. ECFC silenced for Eng with Eng-siRNA and ctr-siRNA were used to test tubulogenesis and permeability +/− TNFα and +/− LIM kinase inhibitors (LIMKi). In silico modeling of TNFα–Eng interactions was carried out from PDB IDs 5HZW and 5HZV. Calcium ions (Ca2+) flux was studied by Oregon Green 488 in epifluorescence microscopy. Levels of cofilin phosphorylation and tubulin post-translational modifications were evaluated by Western blot. F-actin and actin–tubulin distribution/co-localization were evaluated in cells by confocal microscopy. Eng silencing in ECFCs resulted in a decrease of cell sprouting by 50 ± 15% (p < 0.05) and an increase in pseudo-tube width (41 ± 4.5%; p < 0.001) compared to control. Upon TNFα stimulation, ECFC Eng–siRNA displayed a significant higher permeability compared to ctr-siRNA (p < 0.01), which is associated to a higher Ca2+ mobilization (p < 0.01). Computational analysis suggested that Eng mitigated TNFα activity. F-actin polymerization was significantly increased in ECFC Eng-siRNA, MAEC+/−, and MLEC+/− compared to controls (p < 0.001, p < 0.01, and p < 0.01, respectively) as well as actin/tubulin distribution (p < 0.01). Furthermore, the inactive form of cofilin (P-cofilin at Ser3) was significantly decreased by 36.7 ± 4.8% in ECFC Eng-siRNA compared to ctr-siRNA (p < 0.001). Interestingly, LIMKi reproduced the absence of Eng on TNFα-induced ECFC-increased permeability. Our data suggest that Eng plays a critical role in the homeostasis regulation of endothelial cells under inflammatory conditions (TNFα), and loss of Eng influences ECFC-related permeability through the LIMK/cofilin/actin rearrangement-signaling pathway.

As more sequencing data accumulate and novel puzzling genetic regulations are discovered, the need for accurate automated modeling of RNA structure increases. RNA structure modeling from chemical probing experiments has made tremendous progress, however accurately predicting large RNA structures is still challenging for several reasons: RNA are inherently flexible and often adopt many energetically similar structures, which are not reliably distinguished by the available, incomplete thermodynamic model. Moreover, computationally, the problem is aggravated by the relevance of pseudoknots and non-canonical base pairs, which are hardly predicted efficiently. To identify nucleotides involved in pseudoknots and non-canonical interactions, we scrutinized the SHAPE reactivity of each nucleotide of the 188 nt long lariat-capping ribozyme under multiple conditions. Reactivities analyzed in the light of the X-ray structure were shown to report accurately the nucleotide status. Those that seemed paradoxical were rationalized by the nucleotide behavior along molecular dynamic simulations. We show that valuable information on intricate interactions can be deduced from probing with different reagents, and in the presence or absence of Mg2+. Furthermore, probing at increasing temperature was remarkably efficient at pointing to non-canonical interactions and pseudoknot pairings. The possibilities of following such strategies to inform structure modeling software are discussed.

RNA molecules can easily adopt alternative structures in response to different environmental conditions. As a result, a molecule's energy landscape is rough and can exhibit a multitude of deep basins. In the absence of a high-resolution structure, small-angle X-ray scattering data (SAXS) can narrow down the conformational space available to the molecule and be used in conjunction with physical modeling to obtain high-resolution putative structures to be further tested by experiments. Because of the low resolution of these data, it is natural to implement the integration of SAXS data into simulations using a coarse-grained representation of the molecule, allowing for much wider searches and faster evaluation of SAXS theoretical intensity curves than with atomistic models. We present here the theoretical framework and the implementation of a simulation approach based on our coarse-grained model HiRE-RNA combined with SAXS evaluations "on-the-fly" leading the simulation toward conformations agreeing with the scattering data, starting from partially folded structures as the ones that can easily be obtained from secondary structure prediction-based tools. We show on three benchmark systems how our approach can successfully achieve high-resolution structures with remarkable similarity with the native structure recovering not only the overall shape, as imposed by SAXS data, but also the details of initially missing base pairs.

Transcription factors regulate gene activity by binding specific regions of genomic DNA thanks to a subtle interplay of specific and nonspecific interactions that is challenging to quantify. Here, we exploit Reflective Phantom Interface (RPI), a label-free biosensor based on optical reflectivity, to investigate the binding of the N-terminal domain of Gal4, a well-known gene regulator, to double-stranded DNA fragments containing or not its consensus sequence. The analysis of RPI-binding curves provides interaction strength and kinetics and their dependence on temperature and ionic strength. We found that the binding of Gal4 to its cognate site is stronger, as expected, but also markedly slower. We performed a combined analysis of specific and nonspecific binding—equilibrium and kinetics—by means of a simple model based on nested potential wells and found that the free energy gap between specific and nonspecific binding is of the order of one kcal/mol only. We investigated the origin of such a small value by performing all-atom molecular dynamics simulations of Gal4–DNA interactions. We found a strong enthalpy–entropy compensation, by which the binding of Gal4 to its cognate sequence entails a DNA bending and a striking conformational freezing, which could be instrumental in the biological function of Gal4.

Normal mode analysis (NMA) is a fast and inexpensive approach that is largely used to gain insight into functional protein motions, and more recently to create conformations for further computational studies. However, when the protein structure is unknown, the use of computational models is necessary. Here, we analyze the capacity of NMA in internal coordinate space to predict protein motion, its intrinsic flexibility, and atomic displacements, using protein models instead of native structures, and the possibility to use it for model refinement. Our results show that NMA is quite insensitive to modeling errors, but that calculations are strictly reliable only for very accurate models. Our study also suggests that internal NMA is a more suitable tool for the improvement of structural models, and for integrating them with experimental data or in other computational techniques, such as protein docking or more refined molecular dynamics simulations.

Alpha2-macroglobulin (α2M) is a physiological macromolecule that facilitates the clearance of many proteinases, cytokines and growth factors in human. Here, we explored the effect of induced forms of α2M on anticoagulant drugs. Gla-domainless factor Xa (GDFXa) and methylamine (MA)-induced α2M were prepared and characterized by electrophoresis, immunonephelometry, chromogenic, clot waveform and rotational thromboelastometry assays. Samples from healthy volunteers and anticoagulated patients were included. In vivo neutralization of anticoagulants was evaluated in C57Bl/6JRj mouse bleeding-model. Anticoagulant binding sites on induced α2M were depicted by computer-aided energy minimization modeling. GDFXa-induced α2M neutralized dabigatran and heparins in plasma and whole blood. In mice, a single IV dose of GDFXa-induced α2M following anticoagulant administration significantly reduced blood loss and bleeding time. Being far easier to prepare, we investigated the efficacy of MA-induced α2M. It neutralized rivaroxaban, apixaban, dabigatran and heparins in spiked samples in a concentration-dependent manner and in samples from treated patients. Molecular docking analysis evidenced the ability of MA-induced α2M to bind non-covalently these compounds via some deeply buried binding sites. Induced forms of α2M have the potential to neutralize direct oral anticoagulants and heparins, and might be developed as a universal antidote in case of major bleeding or urgent surgery.

The RNA helicase (non-structural protein 13, NSP13) of SARS-CoV-2 is essential for viral replication, and it is highly conserved among the coronaviridae family, thus a prominent drug target to treat COVID-19. We present here structural models and dynamics of the helicase in complex with its native substrates based on thorough analysis of homologous sequences and existing experimental structures. We performed and analysed microseconds of molecular dynamics (MD) simulations, and our model provides valuable insights to the binding of the ATP and ssRNA at the atomic level. We identify the principal motions characterising the enzyme and highlight the effect of the natural substrates on this dynamics. Furthermore, allosteric binding sites are suggested by our pocket analysis. Our obtained structural and dynamical insights are important for subsequent studies of the catalytic function and for the development of specific inhibitors at our characterised binding pockets for this promising COVID-19 drug target.

The biological light-harvesting process offers an unlimited source of inspiration. The high level of control, adaptation capability, and efficiency challenge humankind to create artificial biomimicking nanoarchitectures with the same performances to respond to our energy needs. Here, in the extensive search for design principles at the base of efficient artificial light harvesters, an approach based on self-assembly of pigment-peptide conjugates is proposed. The solvent-driven and controlled aggregation of the peptide moieties promotes the formation of a dense network of interacting pigments, giving rise to an excitonic network characterized by intense and spectrally wide absorption bands. The ultrafast dynamics of the nanosystems studied through two-dimensional electronic spectroscopy reveals that the excitation energy is funneled in an ultrafast time range (hundreds of femtoseconds) to a manifold of long-living dark states, thus suggesting the considerable potentiality of the systems as efficient harvesters.

ABSTRACT Having claimed over 1 million lives worldwide to date, the ongoing COVID-19 pandemic has created one of the biggest challenges to develop an effective drug to treat infected patients. Among all the proteins expressed by the virus, RNA helicase is a fundamental protein for viral replication, and it is highly conserved among the coronaviridae family. To date, there is no high-resolution structure of helicase bound with ATP and RNA. We present here structural insights and molecular dynamics (MD) simulation results of the SARS-CoV-2 RNA helicase both in its apo form and in complex with its natural substrates. Our structural information of the catalytically competent helicase complex provides valuable insights for the mechanism and function of this enzyme at the atomic level, a key to develop specific inhibitors for this potential COVID-19 drug target.

The tripartite multidrug efflux system MexAB-OprM is a major actor in Pseudomonas aeruginosa antibiotic resistance by exporting a large variety of antimicrobial compounds. Crystal structures of MexB and of its Escherichia coli homolog AcrB had revealed asymmetric trimers depicting a directional drug pathway by a conformational interconversion (from Loose and Tight binding pockets to Open gate (LTO) for drug exit). It remains unclear how MexB acquires its LTO form. Here by performing functional and cryo-EM structural investigations of MexB at various stages of the assembly process, we unveil that MexB inserted in lipid membrane is not set for active transport because it displays an inactive LTC form with a Closed exit gate. In the tripartite complex, OprM and MexA form a corset-like platform that converts MexB into the active form. Our findings shed new light on the resistance nodulation cell division (RND) cognate partners which act as allosteric factors eliciting the functional drug extrusion.