Alpha-2-macroglobulin prevents platelet aggregation induced by brain-derived neurotrophic factor.

The brain-derived neurotrophic factor (BDNF) has been recently shown to have activating effects in isolated platelets. However, BDNF circulates in plasma and a mechanism to preclude constant activation of platelets appears necessary. Hence, we investigated the mechanism regulating BDNF bioavailability in blood. Protein-protein interactions were predicted by molecular docking and validated through immunoprecipitation. Platelet aggregation was assessed using light transmission aggregometry with washed platelets in response to classical agonists or BDNF, in the absence or presence of alpha-2-macroglobulin (α2M), and in platelet-rich plasma. BDNF signaling was assessed with phospho-blots. As little as 25% autologous plasma was sufficient to completely abolish platelet aggregation in response to BDNF. Docking predicted two forms of BDNF binding to native or activated α2M, in parallel and perpendicular arrangements, and the model suggested that the BDNF-α2M complex cannot bind to the high-affinity BDNF receptor, tropomyosin receptor kinase B (TrkB). Experimentally, native and activated α2M formed stable complexes with BDNF preventing BDNF-induced TrkB activation and signal transduction. Both native and activated α2M inhibited BDNF induced-platelet aggregation in a concentration-dependent manner with comparable half-maximal inhibitory concentrations (IC50≈ 125-150 nM). Our study implicates α2M as a physiological regulator of BDNF bioavailability, and as an inhibitor of BDNF-induced platelet activation in blood.

RNA folding pathways from all-atom simulations with a variationally improved history-dependent bias.

Atomically detailed simulations of RNA folding have proven very challenging in view of the difficulties of developing realistic force fields and the intrinsic computational complexity of sampling rare conformational transitions. As a step forward in tackling these issues, we extend to RNA an enhanced path-sampling method previously successfully applied to proteins. In this scheme, the information about the RNA's native structure is harnessed by a soft history-dependent biasing force promoting the generation of productive folding trajectories in an all-atom force field with explicit solvent. A rigorous variational principle is then applied to minimize the effect of the bias. Here, we report on an application of this method to RNA molecules from 20 to 47 nucleotides long and increasing topological complexity. By comparison with analog simulations performed on small proteins with similar size and architecture, we show that the RNA folding landscape is significantly more frustrated, even for relatively small chains with a simple topology. The predicted RNA folding mechanisms are found to be consistent with the available experiments and some of the existing coarse-grained models. Due to its computational performance, this scheme provides a promising platform to efficiently gather atomistic RNA folding trajectories, thus retain the information about the chemical composition of the sequence.

Soluble endoglin reduces thrombus formation and platelet aggregation via interaction with αIIbß3 integrin.

BACKGROUND: The circulating form of human endoglin (sEng) is a cleavage product of membrane-bound endoglin present on endothelial cells. Because sEng encompasses an RGD motif involved in integrin binding, we hypothesized that sEng would be able to bind integrin αIIbß3, thereby compromising platelet binding to fibrinogen and thrombus stability. METHODS: In vitro human platelet aggregation, thrombus retraction, and secretion-competition assays were performed in the presence of sEng. Surface plasmon resonance (SPR) binding and computational (docking) analyses were carried out to evaluate protein-protein interactions. A transgenic mouse overexpressing human sEng (hsEng+) was used to measure bleeding/rebleeding, prothrombin time (PT), blood stream, and embolus formation after FeCl3-induced injury of the carotid artery. RESULTS: Under flow conditions, supplementation of human whole blood with sEng led to a smaller thrombus size. sEng inhibited platelet aggregation and thrombus retraction, interfering with fibrinogen binding, but did not affect platelet activation. SPR binding studies demonstrated that the specific interaction between αIIbß3 and sEng and molecular modeling showed a good fitting between αIIbß3 and sEng structures involving the endoglin RGD motif, suggesting the possible formation of a highly stable αIIbß3/sEng. hsEng+ mice showed increased bleeding time and number of rebleedings compared to wild-type mice. No differences in PT were denoted between genotypes. After FeCl3 injury, the number of released emboli in hsEng+ mice was higher and the occlusion was slower compared to controls. CONCLUSIONS: Our results demonstrate that sEng interferes with thrombus formation and stabilization, likely via its binding to platelet αIIbß3, suggesting its involvement in primary hemostasis control.

Investigating the structural changes due to adenosine methylation of the Kaposi's sarcoma-associated herpes virus ORF50 transcript.

Kaposi's sarcoma-associated herpes virus (KSHV) is a human oncovirus. KSHV relies on manipulating the host cell N6-methyl adenosine (m6A) RNA modification pathway to enhance virus replication. Methylation within a RNA stem loop of the open reading frame 50 (ORF50) increases transcript stability via the recruitment of the m6A reader, SND1. In this contribution we explore the energy landscapes of the unmethylated and methylated RNA stem loops of ORF50 to investigate the effect of methylation on the structure of the stem loop. We observe a significant shift upon methylation between an open and closed configuration of the top of the stem loop. In the unmethylated stem loop the closed configuration is much lower in energy, and, as a result, exhibits higher occupancy.

Computer-aided comprehensive explorations of RNA structural polymorphism through complementary simulation methods.

While RNA folding was originally seen as a simple problem to solve, it has been shown that the promiscuous interactions of the nucleobases result in structural polymorphism, with several competing structures generally observed for non-coding RNA. This inherent complexity limits our understanding of these molecules from experiments alone, and computational methods are commonly used to study RNA. Here, we discuss three advanced sampling schemes, namely Hamiltonian-replica exchange molecular dynamics (MD), ratchet-and-pawl MD and discrete path sampling, as well as the HiRE-RNA coarse-graining scheme, and highlight how these approaches are complementary with reference to recent case studies. While all computational methods have their shortcomings, the plurality of simulation methods leads to a better understanding of experimental findings and can inform and guide experimental work on RNA polymorphism.

Biasing RNA Coarse-Grained Folding Simulations with Small-Angle X-ray Scattering Data.

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.

Endoglin Is an Endothelial Housekeeper against Inflammation: Insight in ECFC-Related Permeability through LIMK/Cofilin Pathway.

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.

Induced forms of α2-macroglobulin neutralize heparin and direct oral anticoagulant effects.

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.

RNA Modeling with the Computational Energy Landscape Framework.

The recent advances in computational abilities, such as the enormous speed-ups provided by GPU computing, allow for large scale computational studies of RNA molecules at an atomic level of detail. As RNA molecules are known to adopt multiple conformations with comparable energies, but different two-dimensional structures, all-atom models are necessary to better describe the structural ensembles for RNA molecules. This point is important because different conformations can exhibit different functions, and their regulation or mis-regulation is linked to a number of diseases. Problematically, the energy barriers between different conformational ensembles are high, resulting in long time scales for interensemble transitions. The computational potential energy landscape framework was designed to overcome this problem of broken ergodicity by use of geometry optimization. Here, we describe the algorithms used in the energy landscape explorations with the OPTIM and PATHSAMPLE programs, and how they are used in biomolecular simulations. We present a recent case study of the 5'-hairpin of RNA 7SK to illustrate how the method can be applied to interpret experimental results, and to obtain a detailed description of molecular properties.

Structural transitions in the RNA 7SK 5' hairpin and their effect on HEXIM binding.

7SK RNA, as part of the 7SK ribonucleoprotein complex, is crucial to the regulation of transcription by RNA-polymerase II, via its interaction with the positive transcription elongation factor P-TEFb. The interaction is induced by binding of the protein HEXIM to the 5' hairpin (HP1) of 7SK RNA. Four distinct structural models have been obtained experimentally for HP1. Here, we employ computational methods to investigate the relative stability of these structures, transitions between them, and the effects of mutations on the observed structural ensembles. We further analyse the results with respect to mutational binding assays, and hypothesize a mechanism for HEXIM binding. Our results indicate that the dominant structure in the wild type exhibits a triplet involving the unpaired nucleotide U40 and the base pair A43-U66 in the GAUC/GAUC repeat. This conformation leads to an open major groove with enough potential binding sites for peptide recognition. Sequence mutations of the RNA change the relative stability of the different structural ensembles. Binding affinity is consequently lost if these changes alter the dominant structure.

The interplay between molecular flexibility and RNA chemical probing reactivities analyzed at the nucleotide level via an extensive molecular dynamics study.

Determination of the tridimensional structure of ribonucleic acid molecules is fundamental for understanding their function in the cell. A common method to investigate RNA structures of large molecules is the use of chemical probes such as SHAPE (2'-hydroxyl acylation analyzed by primer extension) reagents, DMS (dimethyl sulfate) and CMCT (1-cyclohexyl-3-(2-morpholinoethyl) carbodiimide metho-p-toluene sulfate), the reaction of which is dependent on the local structural properties of each nucleotide. In order to understand the interplay between local flexibility, sugar pucker, canonical pairing and chemical reactivity of the probes, we performed all-atom molecular dynamics simulations on a set of RNA molecules for which both tridimensional structure and chemical probing data are available and we analyzed the correlations between geometrical parameters and the chemical reactivity. Our study confirms that SHAPE reactivity is guided by the local flexibility of the different chemical moieties but suggests that a combination of multiple parameters is needed to better understand the implications of the reactivity at the molecular level. This is also the case for DMS and CMCT for which the reactivity appears to be more complex than commonly accepted.

Protein-RNA complexation driven by the charge regulation mechanism.

Electrostatic interactions play a pivotal role in many (bio)molecular association processes. The molecular organization and function in biological systems are largely determined by these interactions from pure Coulombic contributions to more peculiar mesoscopic forces due to ion-ion correlation and proton fluctuations. The latter is a general electrostatic mechanism that gives attraction particularly at low electrolyte concentrations. This charge regulation mechanism due to titrating amino acid and nucleotides residues is discussed here in a purely electrostatic framework. By means of constant-pH Monte Carlo simulations based on a fast coarse-grained titration proton scheme, a new computer molecular model was devised to study protein-RNA interactions. The complexation between the RNA silencing suppressor p19 viral protein and the 19-bp small interfering RNA was investigated at different solution pH and salt conditions. The outcomes illustrate the importance of the charge regulation mechanism that enhances the association between these macromolecules in a similar way as observed for other protein-polyelectrolyte systems typically found in colloidal science. Due to the highly negative charge of RNA, the effect is more pronounced in this system as predicted by the Kirkwood-Shumaker theory. Our results contribute to the general physico-chemical understanding of macromolecular complexation and shed light on the extensive role of RNA in the cell's life.

Multifunctional energy landscape for a DNA G-quadruplex: An evolved molecular switch.

We explore the energy landscape for a four-fold telomere repeat, obtaining interconversion pathways between six experimentally characterised G-quadruplex topologies. The results reveal a multi-funnel system, with a variety of intermediate configurations and misfolded states. This organisation is identified with the intrinsically multi-functional nature of the system, suggesting a new paradigm for the classification of such biomolecules and clarifying issues regarding apparently conflicting experimental results.

What Can Human-Guided Simulations Bring to RNA Folding?

Inspired by the recent success of scientific-discovery games for predicting protein tertiary and RNA secondary structures, we have developed an open software for coarse-grained RNA folding simulations, guided by human intuition. To determine the extent to which interactive simulations can accurately predict 3D RNA structures of increasing complexity and lengths (four RNAs with 22-47 nucleotides), an interactive experiment was conducted with 141 participants who had very little knowledge of nucleic acids systems and computer simulations, and had received only a brief description of the important forces stabilizing RNA structures. Their structures and full trajectories have been analyzed statistically and compared to standard replica exchange molecular dynamics simulations. Our analyses show that participants gain easily chemical intelligence to fold simple and nontrivial topologies, with little computer time, and this result opens the door for the use of human-guided simulations to RNA folding. Our experiment shows that interactive simulations have better chances of success when the user widely explores the conformational space. Interestingly, providing on-the-fly feedback of the root mean square deviation with respect to the experimental structure did not improve the quality of the proposed models.

Fast coarse-grained model for RNA titration.

A new numerical scheme for RNA (ribonucleic acid) titration based on the Debye-Hückel framework for the salt description is proposed in an effort to reduce the computational costs for further applications to study protein-RNA systems. By means of different sets of Monte Carlo simulations, we demonstrated that this new scheme is able to correctly reproduce the experimental titration behavior and salt pKa shifts. In comparison with other theoretical approaches, similar or even better outcomes are achieved at much lower computational costs. The model was tested on the lead-dependent ribozyme, the branch-point helix, and the domain 5 from Azotobacter vinelandii Intron 5.

The crystal structure of the 5΄ functional domain of the transcription riboregulator 7SK.

In vertebrates, the 7SK RNA forms the scaffold of a complex, which regulates transcription pausing of RNA-polymerase II. By binding to the HEXIM protein, the complex comprising proteins LARP7 and MePCE captures the positive transcription elongation factor P-TEFb and prevents phosphorylation of pausing factors. The HEXIM-binding site embedded in the 5΄-hairpin of 7SK (HP1) encompasses a short signature sequence, a GAUC repeat framed by single-stranded uridines. The present crystal structure of HP1 shows a remarkably straight helical stack involving several unexpected triples formed at a central region. Surprisingly, two uridines of the signature sequence make triple interactions in the major groove of the (GAUC)2. The third uridine is turned outwards or inward, wedging between the other uridines, thus filling the major groove. A molecular dynamics simulation indicates that these two conformations of the signature sequence represent stable alternatives. Analyses of the interaction with the HEXIM protein confirm the importance of the triple interactions at the signature sequence. Altogether, the present structural analysis of 7SK HP1 highlights an original mechanism of swapping bases, which could represent a possible '7SK signature' and provides new insight into the functional importance of the plasticity of RNA.

Coarse-Grained Simulations Complemented by Atomistic Molecular Dynamics Provide New Insights into Folding and Unfolding of Human Telomeric G-Quadruplexes.

G-quadruplexes are the most important noncanonical DNA architectures. Many quadruplex-forming sequences, including the human telomeric sequence d(GGGTTA)n, have been investigated due to their implications in cancer and other diseases, and because of their potential in DNA-based nanotechnology. Despite the availability of atomistic structural studies of folded G-quadruplexes, their folding pathways remain mysterious, and mutually contradictory models of folding coexist in the literature. Recent experiments convincingly demonstrated that G-quadruplex folding often takes days to reach thermodynamic equilibrium. Based on atomistic simulations of diverse classes of intermediates in G-quadruplex folding, we have suggested that the folding is an extremely multipathway process combining a kinetic partitioning mechanism with conformational diffusion. However, complete G-quadruplex folding is far beyond the time scale of atomistic simulations. Here we use high-resolution coarse-grained simulations to investigate potential unfolding intermediates, whose structural dynamics are then further explored with all-atom simulations. This multiscale approach indicates how various pathways are interconnected in a complex network. Spontaneous conversions between different folds are observed. We demonstrate the inability of simple order parameters, such as radius of gyration or the number of native H-bonds, to describe the folding landscape of the G-quadruplexes. Our study also provides information relevant to further development of the coarse-grained force field.

Electrostatics analysis of the mutational and pH effects of the N-terminal domain self-association of the major ampullate spidroin.

Spider silk is a fascinating material combining mechanical properties such as maximum strength and high toughness comparable or better than man-made materials, with biocompatible degradability characteristics. Experimental measurements have shown that pH triggers the dimer formation of the N-terminal domain (NTD) of the major ampullate spidroin 1 (MaSp 1). A coarse-grained model accounting for electrostatics, van der Waals and pH-dependent charge-fluctuation interactions, by means of Monte Carlo simulations, gave us a more comprehensive view of the NTD dimerization process. A detailed analysis of the electrostatic properties and free energy derivatives for the NTD homoassociation was carried out at different pH values and salt concentrations for the protein wild type and for several mutants. We observed an enhancement of dipole-dipole interactions at pH 6 due to the ionization of key amino acids, a process identified as the main driving force for dimerization. Analytical estimates based on the DVLO theory framework corroborate our findings. Molecular dynamics simulations using the OPEP coarse-grained force field for proteins show that the mutant E17Q is subject to larger structural fluctuations when compared to the wild type. Estimates of the association rate constants for this mutant were evaluated by the Debye-Smoluchowski theory and are in agreement with the experimental data when thermally relaxed structures are used instead of the crystallographic data. Our results can contribute to the design of new mutants with specific association properties.

Coarse-Grained HiRE-RNA Model for ab Initio RNA Folding beyond Simple Molecules, Including Noncanonical and Multiple Base Pairings.

HiRE-RNA is a coarse-grained model for RNA structure prediction and the dynamical study of RNA folding. Using a reduced set of particles and detailed interactions accounting for base-pairing and stacking, we show that noncanonical and multiple base interactions are necessary to capture the full physical behavior of complex RNAs. In this paper, we give a full account of the model and present results on the folding, stability, and free energy surfaces of 16 systems with 12 to 76 nucleotides of increasingly complex architectures, ranging from monomers to dimers, using a total of 850 µs of simulation time.